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docs/reference/graphql/enum/TagsResolution.md | 21 + .../graphql/enum/WatchRuleNotificationType.md | 36 + .../graphql/enum/WatchRuleResourceLevel.md | 20 + docs/reference/graphql/enum/WatchRuleState.md | 20 + docs/reference/graphql/enum/index.md | 6 + docs/reference/graphql/index.md | 25 + .../graphql/input/ActivateGrantInput.md | 25 + .../graphql/input/AttachSmartFolderInput.md | 22 + .../graphql/input/CreateFavoriteInput.md | 21 + .../input/CreateGoogleDirectoryInput.md | 29 + .../graphql/input/CreateGrantInput.md | 30 + .../graphql/input/CreateGroupProfileInput.md | 24 + .../graphql/input/CreateLdapDirectoryInput.md | 52 ++ .../input/CreateLocalDirectoryInput.md | 26 + .../CreateLocalDirectoryUserPasswordInput.md | 21 + .../graphql/input/CreatePolicySettingInput.md | 30 + .../input/CreateProfileAwsAccessKeyInput.md | 21 + .../graphql/input/CreateProfileInput.md | 31 + .../graphql/input/CreateProfileSshKeyInput.md | 22 + .../graphql/input/CreateResourceInput.md | 26 + .../graphql/input/CreateSamlDirectoryInput.md | 40 ++ .../graphql/input/CreateSmartFolderInput.md | 26 + .../input/CreateTurbotDirectoryInput.md | 27 + .../graphql/input/CreateWatchInput.md | 25 + .../graphql/input/CreateWatchRuleInput.md | 25 + .../graphql/input/DeactivateGrantInput.md | 21 + .../graphql/input/DeleteFavoriteInput.md | 21 + .../input/DeleteGoogleDirectoryInput.md | 21 + .../graphql/input/DeleteGrantInput.md | 21 + .../graphql/input/DeleteGroupProfileInput.md | 21 + .../graphql/input/DeleteLdapDirectoryInput.md | 21 + .../input/DeleteLocalDirectoryInput.md | 21 + .../graphql/input/DeletePolicySettingInput.md | 21 + .../input/DeleteProfileAccessKeyInput.md | 21 + .../input/DeleteProfileAwsAccessKeyInput.md | 22 + .../graphql/input/DeleteProfileInput.md | 21 + .../graphql/input/DeleteProfileSshKeyInput.md | 21 + .../graphql/input/DeleteResourceInput.md | 22 + .../graphql/input/DeleteSamlDirectoryInput.md | 21 + .../graphql/input/DeleteSmartFolderInput.md | 21 + .../input/DeleteTurbotDirectoryInput.md | 21 + .../graphql/input/DeleteWatchInput.md | 21 + .../graphql/input/DeleteWatchRuleInput.md | 21 + .../graphql/input/DetachSmartFolderInput.md | 22 + .../reference/graphql/input/GetItemOptions.md | 21 + .../graphql/input/IdentitySearchInput.md | 23 + .../graphql/input/InstallModInput.md | 24 + .../graphql/input/PutResourceInput.md | 25 + .../input/PutSmartFolderAttachmentsInput.md | 22 + .../reference/graphql/input/RunActionInput.md | 22 + .../graphql/input/RunControlInput.md | 21 + .../reference/graphql/input/RunPolicyInput.md | 21 + .../graphql/input/TerminateProcessInput.md | 21 + .../graphql/input/UninstallModInput.md | 21 + .../input/UpdateGoogleDirectoryInput.md | 29 + .../graphql/input/UpdateGrantInput.md | 24 + .../graphql/input/UpdateGroupProfileInput.md | 23 + .../graphql/input/UpdateLdapDirectoryInput.md | 50 ++ .../input/UpdateLocalDirectoryInput.md | 26 + .../UpdateLocalDirectoryUserPasswordInput.md | 22 + .../graphql/input/UpdatePolicySettingInput.md | 29 + .../input/UpdateProfileAccessKeyInput.md | 22 + .../input/UpdateProfileAwsAccessKeyInput.md | 23 + .../graphql/input/UpdateProfileInput.md | 29 + .../graphql/input/UpdateProfileSshKeyInput.md | 22 + .../graphql/input/UpdateResourceInput.md | 26 + .../graphql/input/UpdateSamlDirectoryInput.md | 40 ++ .../graphql/input/UpdateSmartFolderInput.md | 26 + .../input/UpdateTurbotDirectoryInput.md | 26 + .../graphql/input/UpdateWatchInput.md | 25 + .../graphql/input/UpdateWatchRuleInput.md | 25 + .../reference/graphql/input/UploadModInput.md | 23 + .../graphql/input/UploadModPackageInput.md | 24 + .../graphql/input/UploadModSchemaInput.md | 22 + .../graphql/input/UpsertResourceInput.md | 26 + docs/reference/graphql/input/index.md | 6 + .../graphql/mutation/activateGrant.md | 18 + .../graphql/mutation/attachSmartFolders.md | 18 + .../graphql/mutation/createFavorite.md | 18 + .../graphql/mutation/createGoogleDirectory.md | 18 + .../reference/graphql/mutation/createGrant.md | 18 + .../graphql/mutation/createGroupProfile.md | 18 + .../graphql/mutation/createLdapDirectory.md | 18 + .../graphql/mutation/createLocalDirectory.md | 18 + .../createLocalDirectoryUserPassword.md | 18 + .../graphql/mutation/createPolicySetting.md | 18 + .../graphql/mutation/createProfile.md | 18 + .../mutation/createProfileAccessKey.md | 18 + .../mutation/createProfileAwsAccessKey.md | 18 + .../graphql/mutation/createProfileSshKey.md | 18 + .../graphql/mutation/createResource.md | 18 + .../graphql/mutation/createSamlDirectory.md | 18 + .../graphql/mutation/createSmartFolder.md | 18 + .../graphql/mutation/createTurbotDirectory.md | 18 + .../reference/graphql/mutation/createWatch.md | 18 + .../graphql/mutation/createWatchRule.md | 18 + .../graphql/mutation/deactivateGrant.md | 18 + .../graphql/mutation/deleteFavorite.md | 18 + .../graphql/mutation/deleteGoogleDirectory.md | 18 + .../reference/graphql/mutation/deleteGrant.md | 18 + .../graphql/mutation/deleteGroupProfile.md | 18 + .../graphql/mutation/deleteLdapDirectory.md | 18 + .../graphql/mutation/deleteLocalDirectory.md | 18 + .../graphql/mutation/deletePolicySetting.md | 18 + .../graphql/mutation/deleteProfile.md | 18 + .../mutation/deleteProfileAccessKey.md | 18 + .../mutation/deleteProfileAwsAccessKey.md | 18 + .../graphql/mutation/deleteProfileSshKey.md | 18 + .../graphql/mutation/deleteResource.md | 18 + .../graphql/mutation/deleteSamlDirectory.md | 18 + .../graphql/mutation/deleteSmartFolder.md | 18 + .../graphql/mutation/deleteTurbotDirectory.md | 18 + .../reference/graphql/mutation/deleteWatch.md | 18 + .../graphql/mutation/deleteWatchRule.md | 18 + .../graphql/mutation/detachSmartFolders.md | 18 + docs/reference/graphql/mutation/index.md | 6 + docs/reference/graphql/mutation/installMod.md | 18 + .../reference/graphql/mutation/putResource.md | 18 + .../mutation/putSmartFolderAttachments.md | 18 + docs/reference/graphql/mutation/runAction.md | 18 + docs/reference/graphql/mutation/runControl.md | 18 + docs/reference/graphql/mutation/runPolicy.md | 18 + .../graphql/mutation/terminateProcess.md | 18 + .../graphql/mutation/uninstallMod.md | 18 + .../graphql/mutation/updateGoogleDirectory.md | 18 + .../reference/graphql/mutation/updateGrant.md | 18 + .../graphql/mutation/updateGroupProfile.md | 18 + .../graphql/mutation/updateLdapDirectory.md | 18 + .../graphql/mutation/updateLocalDirectory.md | 18 + .../updateLocalDirectoryUserPassword.md | 18 + .../graphql/mutation/updatePolicySetting.md | 18 + .../graphql/mutation/updateProfile.md | 18 + .../mutation/updateProfileAccessKey.md | 18 + .../mutation/updateProfileAwsAccessKey.md | 18 + .../graphql/mutation/updateProfileSshKey.md | 18 + .../graphql/mutation/updateResource.md | 18 + .../graphql/mutation/updateSamlDirectory.md | 18 + .../graphql/mutation/updateSmartFolder.md | 18 + .../graphql/mutation/updateTurbotDirectory.md | 18 + .../reference/graphql/mutation/updateWatch.md | 18 + .../graphql/mutation/updateWatchRule.md | 18 + docs/reference/graphql/mutation/uploadMod.md | 18 + .../graphql/mutation/upsertResource.md | 18 + docs/reference/graphql/object/Action.md | 23 + docs/reference/graphql/object/ActionType.md | 33 + .../graphql/object/ActionTypeList.md | 23 + docs/reference/graphql/object/ActionTypes.md | 23 + docs/reference/graphql/object/ActiveGrant.md | 28 + .../graphql/object/ActiveGrantList.md | 23 + docs/reference/graphql/object/ActiveGrants.md | 23 + docs/reference/graphql/object/Actor.md | 24 + docs/reference/graphql/object/Aws.md | 25 + .../graphql/object/AwsCredentials.md | 24 + docs/reference/graphql/object/Control.md | 33 + .../graphql/object/ControlCategories.md | 23 + .../graphql/object/ControlCategory.md | 36 + .../graphql/object/ControlCategoryList.md | 23 + docs/reference/graphql/object/ControlList.md | 23 + .../graphql/object/ControlListMetadata.md | 22 + .../graphql/object/ControlListStats.md | 22 + docs/reference/graphql/object/ControlStats.md | 27 + .../ControlSummariesByControlCategory.md | 23 + .../object/ControlSummariesByControlType.md | 23 + .../object/ControlSummariesByResource.md | 23 + .../ControlSummariesByResourceCategory.md | 23 + .../object/ControlSummariesByResourceType.md | 23 + .../object/ControlSummaryByControlCategory.md | 22 + .../ControlSummaryByControlCategoryList.md | 23 + .../object/ControlSummaryByControlType.md | 22 + .../object/ControlSummaryByControlTypeList.md | 23 + .../object/ControlSummaryByResource.md | 22 + .../ControlSummaryByResourceCategory.md | 22 + .../ControlSummaryByResourceCategoryList.md | 23 + .../object/ControlSummaryByResourceList.md | 23 + .../object/ControlSummaryByResourceType.md | 22 + .../ControlSummaryByResourceTypeList.md | 23 + .../graphql/object/ControlSummaryListStats.md | 22 + docs/reference/graphql/object/ControlType.md | 39 ++ .../graphql/object/ControlTypeList.md | 23 + docs/reference/graphql/object/ControlTypes.md | 23 + .../object/ControlUsageByControlType.md | 22 + .../object/ControlUsageByControlTypeList.md | 23 + .../object/ControlUsageListMetadata.md | 22 + .../graphql/object/ControlUsageListStats.md | 23 + .../graphql/object/ControlUsageStats.md | 26 + .../object/ControlUsagesByControlType.md | 23 + docs/reference/graphql/object/Controls.md | 23 + .../object/ControlsByControlCategories.md | 23 + .../object/ControlsByControlCategory.md | 22 + .../object/ControlsByControlCategoryList.md | 23 + .../graphql/object/ControlsByControlType.md | 22 + .../object/ControlsByControlTypeList.md | 23 + .../graphql/object/ControlsByControlTypes.md | 23 + .../graphql/object/ControlsByResource.md | 22 + .../object/ControlsByResourceCategories.md | 23 + .../object/ControlsByResourceCategory.md | 22 + .../object/ControlsByResourceCategoryList.md | 23 + .../graphql/object/ControlsByResourceList.md | 23 + .../graphql/object/ControlsByResourceType.md | 22 + .../object/ControlsByResourceTypeList.md | 23 + .../graphql/object/ControlsByResourceTypes.md | 23 + .../graphql/object/ControlsByResources.md | 23 + .../graphql/object/DirectorySearch.md | 24 + .../graphql/object/DirectorySearchMetadata.md | 23 + docs/reference/graphql/object/Favorite.md | 27 + docs/reference/graphql/object/FavoriteList.md | 23 + docs/reference/graphql/object/Favorites.md | 23 + .../graphql/object/GoogleDirectory.md | 28 + docs/reference/graphql/object/Grant.md | 33 + docs/reference/graphql/object/GrantList.md | 23 + docs/reference/graphql/object/Grants.md | 23 + .../object/GraphqlResourceTypeMetadata.md | 22 + .../graphql/object/IdentitiesSearch.md | 23 + docs/reference/graphql/object/Identity.md | 25 + .../object/IdentityPermissionGrouping.md | 23 + .../object/IdentityPermissionsSummaries.md | 23 + .../object/IdentityPermissionsSummary.md | 26 + .../object/IdentityPermissionsSummaryList.md | 23 + .../graphql/object/IdentitySearchList.md | 23 + .../reference/graphql/object/LdapDirectory.md | 44 ++ docs/reference/graphql/object/ListMetadata.md | 22 + docs/reference/graphql/object/ListPaging.md | 23 + docs/reference/graphql/object/ListStats.md | 21 + .../graphql/object/LocalDirectory.md | 25 + .../object/LocalDirectoryUserPassword.md | 21 + docs/reference/graphql/object/Mod.md | 36 + .../graphql/object/ModUninstallResult.md | 21 + .../graphql/object/ModUploadResult.md | 28 + docs/reference/graphql/object/ModVersion.md | 34 + .../graphql/object/ModVersionDownloadUrls.md | 22 + .../graphql/object/ModVersionList.md | 23 + .../graphql/object/ModVersionSearch.md | 23 + .../graphql/object/ModVersionSearchList.md | 23 + .../graphql/object/ModVersionSearches.md | 23 + docs/reference/graphql/object/ModVersions.md | 23 + docs/reference/graphql/object/Mutation.md | 86 +++ docs/reference/graphql/object/Notification.md | 44 ++ .../graphql/object/NotificationList.md | 23 + .../object/NotificationListMetadata.md | 22 + .../graphql/object/NotificationListStats.md | 21 + .../reference/graphql/object/Notifications.md | 23 + docs/reference/graphql/object/Osquery.md | 21 + .../graphql/object/PermissionLevel.md | 30 + .../graphql/object/PermissionLevelList.md | 23 + .../graphql/object/PermissionLevels.md | 23 + .../graphql/object/PermissionType.md | 30 + .../graphql/object/PermissionTypeList.md | 23 + .../graphql/object/PermissionTypes.md | 23 + .../graphql/object/PermissionsByIdentity.md | 23 + .../graphql/object/PermissionsByResource.md | 23 + .../object/PermissionsDetailByIdentity.md | 23 + .../object/PermissionsDetailByIdentityList.md | 23 + .../object/PermissionsDetailByResource.md | 23 + .../object/PermissionsDetailByResourceList.md | 23 + .../object/PermissionsDetailsByIdentity.md | 23 + .../object/PermissionsDetailsByResource.md | 23 + docs/reference/graphql/object/Policies.md | 23 + docs/reference/graphql/object/PolicyDetail.md | 29 + .../graphql/object/PolicyDetailList.md | 23 + .../reference/graphql/object/PolicyDetails.md | 23 + .../graphql/object/PolicyHierarchies.md | 23 + .../graphql/object/PolicyHierarchy.md | 23 + .../graphql/object/PolicyHierarchyList.md | 23 + docs/reference/graphql/object/PolicyList.md | 23 + .../reference/graphql/object/PolicySetting.md | 41 ++ .../graphql/object/PolicySettingList.md | 23 + .../object/PolicySettingListMetadata.md | 22 + .../graphql/object/PolicySettingListStats.md | 22 + .../graphql/object/PolicySettingStats.md | 22 + ...PolicySettingSummariesByControlCategory.md | 23 + .../PolicySettingSummariesByPolicyType.md | 23 + .../PolicySettingSummariesByResource.md | 23 + .../PolicySettingSummariesByResourceType.md | 23 + .../PolicySettingSummaryByControlCategory.md | 22 + ...licySettingSummaryByControlCategoryList.md | 23 + .../PolicySettingSummaryByPolicyType.md | 22 + .../PolicySettingSummaryByPolicyTypeList.md | 23 + .../object/PolicySettingSummaryByResource.md | 22 + .../PolicySettingSummaryByResourceList.md | 23 + .../PolicySettingSummaryByResourceType.md | 22 + .../PolicySettingSummaryByResourceTypeList.md | 23 + .../object/PolicySettingSummaryListStats.md | 22 + .../graphql/object/PolicySettings.md | 23 + .../PolicySettingsByControlCategories.md | 23 + .../object/PolicySettingsByControlCategory.md | 22 + .../PolicySettingsByControlCategoryList.md | 23 + .../object/PolicySettingsByPolicyType.md | 22 + .../object/PolicySettingsByPolicyTypeList.md | 23 + .../object/PolicySettingsByPolicyTypes.md | 23 + .../object/PolicySettingsByResource.md | 22 + .../object/PolicySettingsByResourceList.md | 23 + .../object/PolicySettingsByResourceType.md | 22 + .../PolicySettingsByResourceTypeList.md | 23 + .../object/PolicySettingsByResourceTypes.md | 23 + .../object/PolicySettingsByResources.md | 23 + docs/reference/graphql/object/PolicyStats.md | 26 + docs/reference/graphql/object/PolicyType.md | 47 ++ .../graphql/object/PolicyTypeList.md | 23 + docs/reference/graphql/object/PolicyTypes.md | 23 + docs/reference/graphql/object/PolicyValue.md | 40 ++ .../graphql/object/PolicyValueList.md | 23 + .../graphql/object/PolicyValueListMetadata.md | 22 + .../graphql/object/PolicyValueListStats.md | 22 + .../graphql/object/PolicyValueStats.md | 25 + docs/reference/graphql/object/PolicyValues.md | 23 + docs/reference/graphql/object/Process.md | 32 + .../graphql/object/ProcessHistory.md | 23 + .../graphql/object/ProcessHistoryItem.md | 26 + docs/reference/graphql/object/ProcessList.md | 23 + docs/reference/graphql/object/ProcessLog.md | 24 + .../graphql/object/ProcessLogList.md | 23 + docs/reference/graphql/object/ProcessLogs.md | 23 + docs/reference/graphql/object/Processes.md | 23 + .../graphql/object/ProfileAccessKey.md | 24 + .../graphql/object/ProfileAccessKeyList.md | 23 + .../graphql/object/ProfileAccessKeys.md | 23 + .../graphql/object/ProfileAccount.md | 22 + .../graphql/object/ProfileAccountList.md | 23 + .../graphql/object/ProfileAccounts.md | 23 + .../graphql/object/ProfileAwsAccessKey.md | 24 + .../graphql/object/ProfileAwsAccessKeyList.md | 23 + .../graphql/object/ProfileAwsAccessKeys.md | 23 + .../graphql/object/ProfileInformation.md | 22 + .../reference/graphql/object/ProfileSshKey.md | 24 + .../graphql/object/ProfileSshKeyList.md | 23 + .../graphql/object/ProfileSshKeys.md | 23 + docs/reference/graphql/object/Resource.md | 51 ++ .../graphql/object/ResourceCategories.md | 23 + .../graphql/object/ResourceCategory.md | 35 + .../graphql/object/ResourceCategoryList.md | 23 + docs/reference/graphql/object/ResourceList.md | 23 + .../graphql/object/ResourceListMetadata.md | 22 + .../graphql/object/ResourceListStats.md | 22 + .../object/ResourcePermissionGrouping.md | 23 + .../object/ResourcePermissionsSummaries.md | 23 + .../object/ResourcePermissionsSummary.md | 26 + .../object/ResourcePermissionsSummaryList.md | 23 + .../reference/graphql/object/ResourceStats.md | 22 + .../object/ResourceSummariesByResource.md | 23 + .../ResourceSummariesByResourceCategory.md | 23 + .../object/ResourceSummariesByResourceType.md | 23 + .../object/ResourceSummaryByResource.md | 22 + .../ResourceSummaryByResourceCategory.md | 22 + .../ResourceSummaryByResourceCategoryList.md | 23 + .../object/ResourceSummaryByResourceList.md | 23 + .../object/ResourceSummaryByResourceType.md | 22 + .../ResourceSummaryByResourceTypeList.md | 23 + .../object/ResourceSummaryListStats.md | 23 + docs/reference/graphql/object/ResourceTag.md | 24 + .../graphql/object/ResourceTagList.md | 23 + docs/reference/graphql/object/ResourceTags.md | 23 + docs/reference/graphql/object/ResourceType.md | 39 ++ .../graphql/object/ResourceTypeList.md | 23 + .../reference/graphql/object/ResourceTypes.md | 23 + docs/reference/graphql/object/Resources.md | 23 + .../graphql/object/ResourcesByResource.md | 22 + .../object/ResourcesByResourceCategories.md | 23 + .../object/ResourcesByResourceCategory.md | 22 + .../object/ResourcesByResourceCategoryList.md | 23 + .../graphql/object/ResourcesByResourceList.md | 23 + .../graphql/object/ResourcesByResourceType.md | 22 + .../object/ResourcesByResourceTypeList.md | 23 + .../object/ResourcesByResourceTypes.md | 23 + .../graphql/object/ResourcesByResources.md | 23 + .../graphql/object/RunnableDependencies.md | 24 + .../graphql/object/RunnableDependencyData.md | 23 + .../reference/graphql/object/SamlDirectory.md | 36 + docs/reference/graphql/object/Secret.md | 21 + docs/reference/graphql/object/SmartFolder.md | 25 + .../object/StackResourceLifecycleMetadata.md | 22 + .../object/TerraformResourceTypeMetadata.md | 26 + docs/reference/graphql/object/TrunkItem.md | 21 + .../reference/graphql/object/TrunkItemList.md | 23 + docs/reference/graphql/object/TrunkItems.md | 24 + .../graphql/object/TurbotActionMetadata.md | 33 + .../object/TurbotActionTypeMetadata.md | 35 + .../object/TurbotActiveGrantMetadata.md | 36 + .../object/TurbotControlCategoryMetadata.md | 30 + .../graphql/object/TurbotControlMetadata.md | 40 ++ .../object/TurbotControlTypeMetadata.md | 33 + .../graphql/object/TurbotDirectory.md | 26 + .../graphql/object/TurbotFavoriteMetadata.md | 35 + .../graphql/object/TurbotGrantMetadata.md | 31 + ...TurbotIdentityPermissionsDetailMetadata.md | 42 ++ .../object/TurbotNotificationMetadata.md | 53 ++ .../object/TurbotPermissionMetadata.md | 34 + .../object/TurbotPolicyHierarchyMetadata.md | 30 + .../object/TurbotPolicySettingMetadata.md | 32 + .../object/TurbotPolicyTypeMetadata.md | 38 ++ .../object/TurbotPolicyValueMetadata.md | 42 ++ .../TurbotProcessHistoryItemMetadata.md | 34 + .../object/TurbotProcessLogMetadata.md | 29 + .../graphql/object/TurbotProcessMetadata.md | 33 + .../object/TurbotResourceCategoryMetadata.md | 30 + .../graphql/object/TurbotResourceMetadata.md | 45 ++ .../TurbotResourceNavigationNodeMetadata.md | 23 + ...TurbotResourcePermissionsDetailMetadata.md | 42 ++ .../object/TurbotResourceTagMetadata.md | 26 + .../object/TurbotResourceTypeMetadata.md | 33 + .../graphql/object/TurbotSecretMetadata.md | 21 + .../graphql/object/TurbotTrunkMetadata.md | 24 + .../graphql/object/TurbotWatchMetadata.md | 34 + .../graphql/object/TurbotWatchRuleMetadata.md | 33 + docs/reference/graphql/object/Watch.md | 26 + docs/reference/graphql/object/WatchList.md | 23 + docs/reference/graphql/object/WatchRule.md | 23 + .../reference/graphql/object/WatchRuleList.md | 23 + docs/reference/graphql/object/WatchRules.md | 23 + docs/reference/graphql/object/Watches.md | 23 + docs/reference/graphql/object/Webhook.md | 22 + .../reference/graphql/object/WorkspaceInfo.md | 22 + docs/reference/graphql/object/index.md | 6 + docs/reference/graphql/query/actionTypes.md | 20 + docs/reference/graphql/query/activeGrant.md | 22 + .../graphql/query/activeGrantList.md | 20 + docs/reference/graphql/query/activeGrants.md | 20 + docs/reference/graphql/query/aws.md | 18 + docs/reference/graphql/query/constant.md | 18 + .../graphql/query/constantInteger.md | 18 + docs/reference/graphql/query/control.md | 22 + .../graphql/query/controlCategories.md | 20 + .../graphql/query/controlCategory.md | 22 + .../graphql/query/controlCategoryList.md | 20 + docs/reference/graphql/query/controlList.md | 20 + .../controlSummariesByControlCategory.md | 20 + .../query/controlSummariesByControlType.md | 20 + .../query/controlSummariesByResource.md | 20 + .../controlSummariesByResourceCategory.md | 20 + .../query/controlSummariesByResourceType.md | 20 + docs/reference/graphql/query/controlType.md | 22 + .../graphql/query/controlTypeList.md | 20 + docs/reference/graphql/query/controlTypes.md | 20 + .../query/controlUsagesByControlType.md | 20 + .../reference/graphql/query/controlVersion.md | 22 + docs/reference/graphql/query/controls.md | 20 + .../query/controlsByControlCategoryList.md | 20 + .../query/controlsByControlTypeList.md | 20 + .../query/controlsByResourceCategoryList.md | 20 + .../graphql/query/controlsByResourceList.md | 20 + .../query/controlsByResourceTypeList.md | 20 + 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images/turbot_new_tenant.png create mode 100644 images/update-cal-policy.png create mode 100644 images/update-folder.png create mode 100644 images/users.png create mode 100644 images/values-detail.png create mode 100644 images/values-record.png create mode 100644 images/workspace-usage.png diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml new file mode 100644 index 00000000..dda0c402 --- /dev/null +++ b/.github/workflows/deploy.yml @@ -0,0 +1,14 @@ +name: Trigger Vercel deploy (prod) + +on: + # push: + # branches: + # - main + workflow_dispatch: +jobs: + trigger-vercel-deploy: + runs-on: ubuntu-latest + steps: + - name: Trigger Vercel deploy + run: | + curl -X POST ${{ secrets.VERCEL_DEPLOY_LINK_PROD }} diff --git a/.github/workflows/trigger-turbot-com.yml b/.github/workflows/trigger-turbot-com.yml new file mode 100644 index 00000000..d3e34318 --- /dev/null +++ b/.github/workflows/trigger-turbot-com.yml @@ -0,0 +1,51 @@ +name: Trigger the guardrails preview build in turbot.com + +on: + workflow_dispatch: + + # push: + # branches-ignore: + # - "main" + + # pull_request: + # types: [opened] + +env: + PREVIEW_LINK: turbot-com-git-docs-guardrails + PREVIEW_DOMAIN: turbot.vercel.app + +jobs: + update: + runs-on: ubuntu-latest + if: ${{ github.event_name == 'push' }} + steps: + - name: Repository Dispatch + uses: peter-evans/repository-dispatch@v2 + with: + token: ${{ secrets.GH_PAT }} + repository: turbot/turbot.com + event-type: build-guardrails-docs-preview + client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "ref_name": "${{ github.ref_name }}"}' + + comment-link: + runs-on: ubuntu-latest + timeout-minutes: 5 + if: ${{ github.event_name == 'pull_request' && github.event.action == 'opened' }} + steps: + + - name: Convert head branch special characters to hyphens + id: sanitize_branch + run: | + sanitized_branch=$(echo "${{ github.event.pull_request.head.ref }}" | sed 's/[^a-zA-Z0-9]/-/g') + echo "Sanitized head branch: $sanitized_branch" + echo "::set-output name=sanitized_branch::$sanitized_branch" + + - uses: actions/github-script@v7 + with: + script: | + github.rest.issues.createComment({ + issue_number: context.issue.number, + owner: context.repo.owner, + repo: context.repo.repo, + body: 'Preview link: [https://${{ env.PREVIEW_LINK }}-${{ steps.sanitize_branch.outputs.sanitized_branch }}-${{ env.PREVIEW_DOMAIN }}](https://${{ env.PREVIEW_LINK }}-${{ steps.sanitize_branch.outputs.sanitized_branch }}-${{ env.PREVIEW_DOMAIN }}/)' + }) \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 00000000..236ac28a --- /dev/null +++ b/LICENSE @@ -0,0 +1,402 @@ +Attribution-NonCommercial-NoDerivatives 4.0 International + +======================================================================= + +Creative Commons Corporation ("Creative Commons") is not a law firm and +does not provide legal services or legal advice. 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zT_Q>6Co_T2%p|JY(byb|$^J!h|Ho&m?@9+h-gm9;HvH4e+^z@1k4N`*zD387W;b|W zRDVg~AA=Ttx(CO7PMz}9|L~)Uy7Er>*Sh2xj8pFH>wsUge+;Os`U^& +Any policy in Turbot Guardrails can use a calculated policy instead of a static value! + + +In this exercise, you will create a calculated policy to set the +`AWS > S3 > Bucket > Tags > Template` using the Turbot Guardrails Console. + +By the end of this lab, you will be able to create and test calculated policies +in the Turbot Guardrails Console. + +## Prerequisites + +- [Install the aws and aws-s3 mods](mods/install). This lab exercise uses + policies in the `aws-s3` mod, so it must be installed in your Workspace. + +- You should be familiar with the basics of + [Managing Policies](guides/managing-policies). You may want to start with the + [Policy Settings in 7 minutes](7-minute-labs/set-policy) lab. + +- You must have at least one S3 bucket that has been discovered in your + workspace. It is recommended that you create a test bucket for this lab (or + re-use the bucket you created for + [Policy Settings in 7 minutes](7-minute-labs/set-policy)) + +## Create/Edit the Policy Setting + +1. Log into the Turbot Guardrails Console as an Administrator (`Turbot/Admin` or `Turbot/Owner`), then click the **Policies** tab. +2. Click the green **New Policy Setting** button. +3. Search and select `AWS > S3 > Bucket > Tags > Template` as **Policy Type**. +4. In the **Resource** field, select the test bucket created in the + [Prerequisites](#prerequisites) setup. You can search for it by name, or + **Browse** and select it. +5. In the **Setting** section, click the link `Enable calculated mode`. Then + **Launch calculated policy builder**. This will allow you to create and test + your calculated policy. +6. By default, the test bucket that you set in the **Resource** should be set as + the **Test Resource**. + +### Define the GraphQL input query + +To get information from the CMDB to use in our policy, you need to specify a +[GraphQL](reference/graphql) Query. Copy & paste this query into the **Step 2: +Query data using GraphQL** field: + +```graphql +{ + bucket { + Name + tags + } +} +``` + +Note that the box to the right is populated with the results of your query +against the **Test Resource**. For example: + +```json +{ + "bucket": { + "Name": "turbot-bucket-version", + "tags": { + "Company": "Vandelay Industries", + "Department": "Sales", + "Cost Center": "314159" + } + } +} +``` + +### Create a template to format the results + +The `AWS > S3 > Bucket > Tags > Template` expects the tags to be formatted yaml +object as a set of `key: value` pairs. You can use a +[nunjucks](https://mozilla.github.io/nunjucks/) template to transform the query +results into the format expected by the Policy Type. + +Copy & paste this template into the **Step 3: Transform using Jinja2 Template** +field. For example: + +```yaml +Company: "Vandelay Industries" +Department: + "{% if $.bucket.tags['Department'] in ['Sales', 'IT', 'Marketing', 'HR'] %}{{ + $.bucket.tags['Department'] }}{% else %}Non-Compliant Tag{% endif %}" +Cost Center: + "{% if $.bucket.tags['Cost Center'] %}{{ $.bucket.tags['Cost Center'] }}{% + else %}Non-Compliant Tag{% endif %}" +Environment: + "{% if $.bucket.tags['Environment'] in ['Dev', 'QA', 'Prod', 'Temp'] %}{{ + $.bucket.tags['Environment'] }}{% else %}Non-Compliant Tag{% endif %}" +``` + +The template uses standard [nunjucks](https://mozilla.github.io/nunjucks/), +allowing you to use conditional logic, iterate over items, and perform complex +transformations of the data. + +Notice that the results of rendering your template with the data from the input +query are shown to the right of the template. The box at the bottom shows the +final, rendered policy value after validation against the schema for the policy +type. ![](/images/docs/guardrails/calculated-policy-test.png) + +Click **Create** to create this setting (or **Update** if you are updating an +existing setting). + +The policy value for this bucket will not be calculated. Any changes to the data +in the input query will cause this policy to be re-calculated bases on the new +values. + +Note that you created this setting on the bucket itself, thus only this bucket +will be affected. If you made the setting at a higher level in the hierarchy, it +would apply to every bucket below. For example, setting this calculated policy +at the AWS Account level would cause every S3 bucket in the account to calculate +_its own_ value, based on _its own_ data in the CMDB. + +## Expand your query + +1. Search and select `AWS > S3 > Bucket > Tags > Template` policy setting, and + click **EDIT** to update it. + +2. Update the Graphql. Make the following changes to the query. _For this + exercise, you should type these changes -- do not cut and paste_. + +```graphql +{ + // highlight-start + region { + Name + } + // highlight-end + bucket { + Name + tags + } +} +``` + + + + +![](/images/docs/guardrails/update-cal-policy.png) + +The GraphQL available in calculated policies is a super-set of the +[Turbot Guardrails GraphQL API](reference/graphql). The API is extended with dynamic +queries for the Turbot Guardrails Resource Type that automatically pivot based on the +context of the current resource. Notice in the example query that we added +`region` to the query - Guardrails assumes that we mean the `region` resource in +which _this bucket resides_. Likewise, you may use `account` and `folder` to get +information about account and folder above the bucket in the hierarchy. + +You can discover the schema for these resources via auto-complete, or by viewing +the schema definition in the **Inspect** tab of the [mod documentation](mods). +The `bucket` query refers to the +[S3 Bucket Schema](mods/turbot/aws-s3/inspect#/definitions/bucket), as an +example. + +You can also view the schema by looking at the **Explore** page on an existing +resource. Occasionally, attributes may exist in the CMDB that are not explicitly +defined in the schema definition. You can use `get` to retrieve these items. + +1. Go to the **Explore** page for your test bucket resource. Notice that there + is a `Grantee` attribute for this resource. +2. View the + [S3 Bucket Schema definition](mods/turbot/aws-s3/inspect#/definitions/bucket). + Notice that `Grantee` is not explicitly defined as an attribute. +3. To query the `Grantee` attribute, you must use a `get` query. Edit your query + as follows: + +```graphql +{ + region { + Name + } + bucket { + Name + tags + grantee: get(path: "Acl.Grants[0].Grantee") //highlight-line + } +} +``` + +4. Notice that the `grantee` is now added to your query results. + ![](/images/docs/guardrails/get-cal-policy.png) + +The combination of GraphQL and Nunjucks make calculated policies powerful and +flexible. Any Turbot Guardrails policy can be calculated, using any data in the entire +CMDB! + +## Further Reading + +- [Introduction to GraphQL](https://graphql.org/learn/) +- [Nunjucks Templating Documentation](https://mozilla.github.io/nunjucks/templating.html) +- [Turbot Guardrails GraphQL API Reference](reference/graphql) +- [Turbot Guardrails Filter Language Reference](reference/filter) +- [Managing Policies Guide](guides/managing-policies) +- [Policy Settings in 7 minutes](7-minute-labs/set-policy) +- [Mod Documentation](mods) diff --git a/docs/7-minute-labs/calc-policy/update-cal-policy.png b/docs/7-minute-labs/calc-policy/update-cal-policy.png new file mode 100644 index 0000000000000000000000000000000000000000..9d1925170bd68f69a088077dc454c6674834f943 GIT binary patch literal 236787 zcma%jWmufcwk8Sg8r(GmLgNH!T!II8cXxM(U_pXQAh^3W?kK|w*GN`4hpgo1*1fr5hWL4bS9$rDu=hJt$M zZ6PA^O;SXJ{F|elsfD!(6x7E!BYpi(l8he*4Gi@42gexbksRF=!^5K#^*eex$2xn+ zd-eOsvr@FR*YPpdd;GDzTl+f^asfwyqf%GT9^is{?-yLo%2Y>H8lI+`fOl?EmJY1Y z&{Xh0GBXr2GLVh;pcZ(BV8v(zZ&Ap#8bNtbz5MTtBXQo5AQ-Q`s|HgXqm#R0rHu8y zSH;HKMlqI#T6iys(Et~oiDsbX|7VCGf?luzevm1gsM80!-zo{$%$?87 zE11)lkcLNy;s}p1!tBo6#Qc#tg$6C9_{R04#JR5>+h`c zL5B|Nr4LRS=7WRtwSo(^*+asL#M(eJd+rww*UK=qhB3JM!opm&`t0J(R))vO&W6dr*v`;|$=$~O zZJnT?_}qEkzS@{L8<4x(Slc@BxC1HwQG(~~`(N1rO7edcakc_ds>^;O7qN3RA?ILX zXJV%0Mt=#{l9Cna5HoNz3Sf{{jKU>L*bEkv@m&-(qFRRXW;|< zUwQvko)7Ssp#CPff3C_ua^IGPABhj}f0mdZ=_VU$845}eN>Wrv+5O#dCTxm|3SQ`Z z=j6)QFz2AJg^A=jxzitW!$Up_&<7Sdf6RFwNEt3ANf_+!PfotFvI6Wque6JOa@=*? z8_zU`Yro-RyIXZ~&AhvQxz$`ct4N#t>JRfDCPV6XuLNMz-oemn1!}?f|6!u^y`I@I z_>YUTB>TUPX}KBN9{pj(B7gU9QaBCF=J7FwFI_>zax^7BUU81)gMNQ5<3A8;#-vTi`5womr$4e-^52Sjo&WtjO^?q=lRu20 z{{UQU&>;Cb89_)D%D<7ro1oki5tm!2uo`bKBnaL$0%6`a-jbjhpyDO?pTX=GAMr92 z{CffXQ$hjebb<<8i*dEW|Gw9MuF!cVl$g$%1`EyqD4M?sPL%iE_m-)cj1TdD%lw}t z`!

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this exercise, you will use the `turbot` command to query the Turbot Guardrails API, and +then build and publish your first mod. + +By the end of this lab, you will be able to run basic `turbot` CLI commands. + +## Prerequisites + +- You will need to know the URL of your Turbot Guardrails workspace(s). +- You will need your Guardrails API access keys for each workspace. If you do not have keys for your profile, you can [generate new ones](guides/iam/access-keys). + +## Install the Turbot Guardrails CLI + +- Download the latest Turbot Guardrails CLI. The latest version is available from [Turbot Guardrails CLI releases](https://github.com/turbot/guardrails-cli/releases). +- Unzip the `turbot` binary into a directory in your PATH (for example `/usr/local/bin/turbot`) +- Run `turbot --version` to verify your CLI version. + +```shell +$ turbot --version +1.29.0 +``` + +## Set up Your Turbot Credentials + +To configure the Turbot Guardrails CLI tool to connect to your workspace, run the +`turbot configure` command. When prompted, enter a profile name, then your +**Workspace URL**, **Turbot Guardrails API Access Key**, and **Turbot Guardrails API Secret Key**: + +```bash +$ turbot configure +✔ Profile name [default] … default +✔ Workspace URL … https://turbot-customer.cloud.turbot.com +✔ Turbot Access Key … ************************************ +✔ Turbot Secret Key … ************************************ +Written profile 'default' to '/Users/TestUser/.config/turbot/credentials.yml' +``` + +This command will generate a `default` profile and add it to your Turbot Guardrails +credentials file. The Turbot Guardrails Terraform provider and +[scripts in the Guardrails Samples Repo](https://github.com/turbot/guardrails-samples/tree/master/api_examples/graphql/clients) +can use the Turbot Guardrails CLI credentials file. + +### Login + +Note: This step is only necessary if you are publishing to the central Turbot Guardrails +mod repository. + +Login to the Turbot Guardrails mod registry using the `turbot login` command. + +``` +✔ Enter your turbot-dev.com username: … *********** +✔ Enter your turbot-dev.com password: … *********** +Logged in to turbot mod registry +``` + +## Query Turbot with 'turbot graphql' + +You can use the `turbot graphql` command to execute graphql queries against a +Turbot Guardrails workspace. + +1. Run the following command. This executes a query against your workspace that + returns the most recent controls in alarm or error state. + +```bash +$ turbot graphql controls --filter "state:alarm,error sort:-timestamp" +``` + +```yaml +controls: + items: + controls: + items: + - type: + uri: 'tmod:@turbot/turbot#/control/types/controlInstalled' + state: error + turbot: + id: '178116018631614' + - type: + uri: 'tmod:@turbot/aws-lex#/control/types/botDiscovery' + state: error + turbot: + id: '178116018444199' + - type: + uri: 'tmod:@turbot/aws-lex#/control/types/botDiscovery' + state: error + turbot: + id: '178116018441126' +``` + +2. Run the same command, adding an `--output` parameter to change the format the + output: + +```bash +turbot graphql controls --filter "state:alarm,error sort:-timestamp" --output '{items { turbot{timestamp} type{title} resource{trunk{title} }}}' +``` + +```yaml + - turbot: + timestamp: '2019-12-10T10:03:44.387Z' + type: + title: Control Installed + resource: + trunk: + title: Turbot > @turbot/aws-lex > Usage + - turbot: + timestamp: '2019-12-10T10:03:44.164Z' + type: + title: Discovery + resource: + trunk: + title: Turbot > vandelay_industries > 876515858155 > us-east-1 + - turbot: + timestamp: '2019-12-10T10:03:44.164Z' + type: + title: Discovery + resource: + trunk: + title: Turbot > vandelay_industries > 876515858155 > us-west-1 +``` + +3. You can run the same query by constructing the entire graphql statement and + using `--query`. + + - Create a file named `my-query.txt` and add the following GraphQL statement: + + ```graphql + { + controls(filter: "state:alarm,error sort:-timestamp") { + items { + turbot { + timestamp + } + type { + title + } + resource { + trunk { + title + } + } + } + } + } + ``` + + - Run the `turbot graphql` command, and pass the file name to the `--query` + argument: + + ```bash + turbot graphql --query my-query.txt + ``` + + ```yaml + controls: + items: + - turbot: + timestamp: "2019-12-10T10:03:44.387Z" + type: + title: Control Installed + resource: + trunk: + title: Turbot > @turbot/aws-lex > Usage + - turbot: + timestamp: "2019-12-10T10:03:44.164Z" + type: + title: Discovery + resource: + trunk: + title: Turbot > vandelay_industries > 876515858155 > us-east-1 + - turbot: + timestamp: "2019-12-10T10:03:44.164Z" + type: + title: Discovery + resource: + trunk: + title: Turbot > vandelay_industries > 876515858155 > us-west-1 + ``` + +## Build and Publish a Mod + +We have included example mods in the `example-mods` folder of the +[Turbot CLI repo](https://github.com/turbot/cli) to get you comfortable with the +Turbot CLI. + +Clone the repo: + +```bash +git clone git@github.com:turbot/cli.git +cd cli/example-mods/ssl-check/ + +``` + +### Install + +Use `turbot install` to install your mod dependencies and headers. + +```bash +$ turbot install +Installing dependencies for tmod:@turbot/ssl-check +{ + "@turbot/turbot": ">=5.0.0-alpha.1" +} +Registry: turbot.com +Refreshed the mod registry token +Acquired header URLs + +* Installing @turbot/turbot version 5.0.0 + +Installed 1 header to /Users/your_user_folder/archive/trash/cli/example-mods/ssl-check/turbot_mods +``` + +### Inspect + +Inspect and verify the structure of your mod using the `turbot inspect` command. +Make sure you are in the correct mod directory. + +```bash +$ turbot inspect + +Policy types: +Turbot > SSL Check +Turbot > SSL Check > SSL Input +Turbot > SSL Check Expiration +Turbot > SSL Expiration Warning Period + +Control types: +Turbot > SSL Check +Turbot > SSL Check Expiration + +``` + +### Test + +Run unit tests with `turbot test` + +1. Run `build.sh` to install all the npm dependencies for the mod. + +```bash +$ ./build.sh +~/archive/trash/cli/example-mods/ssl-check/functions/checkSSLExpiration ~/archive/trash/cli/example-mods/ssl-check +npm notice created a lockfile as package-lock.json. You should commit this file. +npm WARN sslCheckExpiration@1.0.0 No repository field. +npm WARN sslCheckExpiration@1.0.0 No license field. + +added 205 packages from 237 contributors and audited 522 packages in 9.025s +found 14 high severity vulnerabilities + run `npm audit fix` to fix them, or `npm audit` for details + adding: index.js (deflated 66%) + adding: package.json (deflated 35%) + adding: node_modules/ (stored 0%) + adding: node_modules/fs-constants/ (stored 0%) + adding: node_modules/fs-constants/LICENSE (deflated 41%) + adding: node_modules/fs-constants/index.js (deflated 23%) + adding: node_modules/fs-constants/README.md (deflated 48%) + adding: node_modules/fs-constants/package.json (deflated 55%) + adding: node_modules/fs-constants/browser.js (stored 0%) + adding: node_modules/asn1/ (stored 0%) + adding: node_modules/asn1/LICENSE (deflated 41%) + adding: node_modules/asn1/README.md (deflated 48%) + adding: node_modules/asn1/package.json (deflated 53%) + ... +``` + +2. Run `turbot vcr start` to run the docker container that the tests will run + against. + +```bash +$ turbot vcr start +docker run --name turbot-vcr -p 1080:1080 -d --rm jamesdbloom/mockserver +ae60438d68b8cfe563b08f15308cc1c5e63ce8a7b684c46e927a5687ef44adea +``` + +3. Run the `turbot test` command to ensure all the test cases are passing + locally. + +```bash +$ turbot test + +Policy types: +Turbot > SSL Check +Turbot > SSL Check > SSL Input +Turbot > SSL Check Expiration +Turbot > SSL Expiration Warning Period + +Control types: +Turbot > SSL Check +Turbot > SSL Check Expiration + +Control log level: warning + + + mod + ✓ is parseable + Compile mod + ✓ Mod was successfully compiled + Policy + Types + SSL Check [sslCheck] + single default + ✓ default and default template template + - default or default template template + ✓ default valid + example + ✓ #0 is valid + SSL Input [sslInput] + single default + ✓ default and default template template + - default or default template template + ✓ default valid + example + ✓ #0 is valid + SSL Check Expiration [sslCheckExpiration] + single default + ✓ default and default template template + - default or default template template + ✓ default valid + example + ✓ #0 is valid + SSL Expiration Warning Period [sslExpirationWarningPeriod] + single default + ✓ default and default template template + - default or default template template + Control + Types + SSL Check [sslCheck] + ✓ input queries use valid graphql + ✓ input queries have valid policy references + ✓ Test data validation was executed + Skip if cmdb policy set to skip + Setup + ✓ Test data valid + Inline + ✓ run + Function + ✓ run (6146ms) + Output + ✓ Validate test expectation + ✓ Assert expected output + SSL Check Expiration [sslCheckExpiration] + ✓ input queries use valid graphql + ✓ input queries have valid policy references + ✓ Test data validation was executed + Skip if cmdb policy set to skip + Setup + ✓ Test data valid + Inline + ✓ run + Function + - run + Output + ✓ Validate test expectation + ✓ Assert expected output + OK with zero warning period + Setup + ✓ Test data valid + Inline + ✓ run + Function + ✓ run (7205ms) + Output + ✓ Validate test expectation + ✓ Assert expected output + Alarm with large warning period + Setup + ✓ Test data valid + Inline + ✓ run + Function + ✓ run (7325ms) + Output + ✓ Validate test expectation + ✓ Assert expected output + Error with invalid url + Setup + ✓ Test data valid + Inline + ✓ run + Function + ✓ run (6503ms) + Output + ✓ Validate test expectation + ✓ Assert expected output + + + 42 passing (29s) + 5 pending +``` + +### Upload + +- Upload and install your mod to your turbot workspace using the `turbot up` + command. + +```bash +$ turbot up + +Policy types: +Turbot > SSL Check +Turbot > SSL Check > SSL Input +Turbot > SSL Check Expiration +Turbot > SSL Expiration Warning Period + +Control types: +Turbot > SSL Check +Turbot > SSL Check Expiration + +Running prepack script: ./build.sh +~/archive/trash/cli/example-mods/ssl-check/functions/checkSSLExpiration ~/archive/trash/cli/example-mods/ssl-check + +... + +~/archive/trash/cli/example-mods/ssl-check + +Zipping mod +Uploading mod { + dirName: '/Users/jsmyth/archive/trash/cli/example-mods/ssl-check', + parent: 'tmod:@turbot/turbot#/', + packedMod: '/Users/jsmyth/archive/trash/cli/example-mods/ssl-check/index.zip', + workspace: 'https://morales-turbot.cloud.turbot-dev.com/api/latest/graphql' +} +Mod upload started.. { parent: 'tmod:@turbot/turbot#/' } + +Build id 20191218230735220 + +Module successfully uploaded. +Mod resource page: https://morales-turbot.cloud.turbot-dev.com/resource/178871981691555 + +Check control installed controls to ensure all Lambda based controls have been installed successfully. + +Triggering mod install control ... +Check the status of your mod install here: https://morales-turbot.cloud.turbot-dev.com/control/178871982425772 +``` + +- The `turbot up` command provides a link to view the status of the mod install. + you can visit that link in the Turbot Console to verify that you mod installs + correctly. Alternately, you can query the control from the cli using the + control id from the link: + +```bash +$ turbot graphql control --id "178871982425772" +control: + type: + uri: 'tmod:@turbot/turbot#/control/types/modInstalled' + state: ok + turbot: + id: '178871982425772' +``` + +## Further Reading + +- turbot inspect +- turbot install +- turbot login +- turbot test +- turbot up diff --git a/docs/7-minute-labs/custom-mod/index.md b/docs/7-minute-labs/custom-mod/index.md new file mode 100644 index 00000000..c45c349c --- /dev/null +++ b/docs/7-minute-labs/custom-mod/index.md @@ -0,0 +1,269 @@ +--- +title: "Custom Mods" +template: Documentation +nav: + title: "Custom Mods" +--- + +# Dunder Mifflin Compliance and Control Framework deployment in 7 minutes + +| Goal | Clone the DMI Compliance and Control Framework custom mods, install, run unit tests, then build and upload to your workspace. | +|------|-------------------------------------------------------------------------------------------------------------------------------| +| Time | 7 minutes | + +## Prerequisites + +- You will need Turbot Guardrails API access keys. If you do not have keys for your + profile, you can [generate new ones](guides/iam/access-keys). +- You will need to know the URL of your Turbot Guardrails workspace(s). + +## Install the Turbot Guardrails CLI + +- Download the latest Turbot Guardrails CLI. The latest version is available + from [Turbot Guardrails Releases](releases/cli). +- Unzip the turbot binary into a directory in your PATH (for example + `/usr/local/bin/turbot`) +- Run `turbot --version` to verify your CLI version. + +## Cloning DMI custom mods + +[DMI custom mods source code](https://github.com/turbot/guardrails-cli/tree/master/example-mods/@dmi) lives inside the +[Turbot CLI Repository](https://github.com/turbot/cli). First, clone the +Guardrails Sample Repository mod project: + +```bash +git clone https://github.com/turbot/cli.git + +``` + +

+ +## Installing dmi-ccf mod + +Navigate into the `dmi-ccf` mod folder: + +```bash +cd cli/example-mods/@dmi/dmi-ccf +``` + +Install the `dmi-ccf` mod: + +```bash +turbot install +``` + + + +## Inspecting dmi-ccf mod + +To inspect and verify the structure of the mod use the +[turbot inspect command](reference/cli/commands/inspect) + +```bash +turbot inspect +``` + +## Testing dmi-ccf mod + +#### Running Unit tests + +Running all tests: + +```bash +turbot test +``` + +Running tests of a specific control: + +```bash +turbot test --control [control name] +``` + +## Uploading dmi-ccf mod + +> Hint: You don't need to upload dmi-ccf mod to a workspace in order to run the +> dmi-ccf-aws mod locally. So, you might skip to +> [dmi-ccf-aws mod installation](#Installing-dmi-ccf-aws-mod) + +
Hint: You don't need to upload dmi-ccf mod to a workspace in order to run the dmi-ccf-aws mod locally. You can skip to dmi-ccf-aws mod installation.
+ +Before deploying the mod, you first need to install its dependencies on the +workspace. + +First check mod dependencies at +[src/turbot.yml](https://github.com/turbot/cli/blob/master/example-mods/%40dmi/dmi-ccf/src/turbot.yml) +file, then follow [this guide](guides/managing-mods/install-mods) to install +them on the workspace. + +After that, run the following command to upload the mod into the workspace +defined in the local +[Turbot Guardrails CLI configuration file](reference/cli/installation#named-profiles), +usually located at `[user home]/.turbot/config.yml` + +```bash +turbot up --profile=[target workspace profile] +``` + +## Installing dmi-ccf-aws mod + +After having the dmi-ccf mod installed, we may proceed with the dmi-ccf-aws mod. + +The turbot-cli argument `--peer-path ../..` will be used here to map all the +custom mods under the +[@dmi](https://github.com/turbot/cli/tree/master/example-mods/%40dmi) folder. +This argument is needed because the dependence dmi-ccf is only available locally +inside the [@dmi](https://github.com/turbot/guardrails-cli/tree/master/example-mods/%40dmi) folder. + +```bash +turbot install --peer-path ../.. +``` + +> The turbot [install command](https://turbot.com/guardrails/docs/reference/cli/commands/install) installs a mod +> and all of its dependencies locally + +## Inspecting dmi-ccf-aws mod + +To inspect and verify the structure of the mod use the +[turbot inspect command](https://turbot.com/guardrails/docs/reference/cli/commands/inspect) + +```bash +turbot inspect --peer-path ../.. +``` + +## Testing dmi-ccf-aws mod + +#### Running Unit tests + +Running all tests: + +```bash +turbot test --peer-path ../.. +``` + +Running tests of a specific control: + +```bash +turbot test --peer-path ../.. --control [control name] +``` + +## Uploading dmi-ccf-aws mod + +Before deploying the mod, you first need to install its dependencies on the +workspace. + +First check mod dependencies at +[src/turbot.yml](https://github.com/turbot/cli/blob/master/example-mods/%40dmi/dmi-ccf-aws/src/turbot.yml) +file, then follow [this guide](guides/managing-mods/install-mods) to install +them on the workspace. + +After that, run the following command to upload the mod into the workspace +defined in the local +[Turbot CLI configuration file](https://turbot.com/guardrails/docs/reference/cli/installation#named-profiles), +usually located at `[user home]/.turbot/config.yml` + +```bash +turbot up --peer-path ../.. --profile=[target workspace profile] +``` + +## About DMI Control Framework + +At this point you should probably have the dmi-ccf and dmi-ccf-aws mods up and +running on your workspace, or at least installed locally. Now, let's learn more +about the DMI Control Framework + +### Overview + +[Dunder Mifflin Paper Company, Inc. (DMI)](https://en.wikipedia.org/wiki/Dunder_Mifflin) +is a fictional paper sales company featured in the American television series +The Office. + +DMI defines its own compliance framework to ensure security and regulatory +compliance. This compliance framework provides a set of prescriptive controls +for network and data security, user authentication and authorization, and +monitoring. + +While Turbot provides capabilities to meet most of DMI's control objectives, DMI +would like to be able to search, filter, and report on compliance to their +specific controls using the Turbot console. DMI employees are already aware of +the DMI framework, and they communicate using the terms and definitions defined +there. + +To meet this requirement, DMI has decided to write a Turbot custom mod. This mod +will leverage existing Turbot resources and CMDB data but will present the data +in the native structure of the DMI Control Framework. Note that automated +remediation ("enforce") is out of scope - these controls will be "check" mode +only (existing Turbot controls can be used to remediate the items if desired, +however) + +### The DMI Compliance and Control Framework + +The Dunder Mifflin Compliance and Control Framework (DMI CCF) is composed of a +set of generalized controls, with separate implementations (benchmarks) that +provide specific technical implementations for each technology platform. + +The DMI Control Framework is composed of the following control categories (The +sections are common to all platforms): + +1. Authentication & Access Control +2. Data Security & Encryption +3. Network Security +4. Logging & Auditing +5. Data Protection & Business Continuity + +The DMI AWS Benchmark provides implementation requirements specific to AWS. The +AWS Benchmark is divided into sections per AWS service. + +1. IAM +2. S3 +3. CloudTrail +4. RDS + +Each section contains multiple numbered control items. Each of these control +items maps back to a control category in the control framework. + +| Benchmark Item | Control Category | +|------------------------------------------------------------------|---------------------------------------| +| AWS.IAM.001 - Password policy meets complexity requirements | Authentication & Access Control | +| AWS.IAM.002 - Require MFA for console users | Authentication & Access Control | +| AWS.S3.001 - Set Default Encryption on S3 Buckets | Data Security & Encryption | +| AWS.S3.002 - Enable Versioning on S3 Buckets | Data Protection & Business Continuity | +| AWS.VPC.001 - Disallow access to management ports from 0.0.0.0/0 | Network Security | +| AWS.CloudTrail.001 - Enable Cloudtrail in All Regions | Logging & Auditing | +| AWS.RDS.001 - Enable RDS Backups with standard DB retention | Data Protection & Business Continuity | + +### Guidelines + +Each control targets the most specific resource for its purpose: For example, a +control targeting user information will target users. A control targeting +security group rule details would target the security group. + +All Custom Reporting Framework controls are based on information in the CMDB. +They must work when Turbot is limited to read only credentials for the provider. + +### Control/Policy Type Hierarchy + +The control and policy type hierarchies map each Turbot policy and control to a +DMI Control item. + +The DMI benchmark item IDs follow a consistent structure: +`{provider}.{control section}.{id number}` - for example: `AWS.IAM.001`. The +Turbot type hierarchy mirrors DMI's benchmark structure: + +- The top-level type is `Dunder Mifflin` +- The next level is the provider abbreviation +- The next level is the DMI Benchmark Section that the item belongs to: + - **Dunder Mifflin > AWS > IAM** + - **Dunder Mifflin > AWS > S3** + - **Dunder Mifflin > AWS > VPC** + - **Dunder Mifflin > AWS > CloudTrail** + - **Dunder Mifflin > AWS > RDS** +- The next level is the individual control item. As in CIS, this contains the + full control ID as well as the title. For example: + - DMI Control Item: **AWS.IAM.001 - Password policy meets complexity + requirements** haves policies and controls: **Dunder Mifflin > AWS > IAM > + AWS.IAM.001 - Password policy meets complexity requirements** + +--- + +See also +[About Dunder Mifflin Paper Company, Inc.](https://en.wikipedia.org/wiki/Dunder_Mifflin) diff --git a/docs/7-minute-labs/graphql/graphiql.png b/docs/7-minute-labs/graphql/graphiql.png new file mode 100644 index 0000000000000000000000000000000000000000..69f5d7383ceb282208d20c0f72f8ba05086cb758 GIT binary patch literal 357369 zcmeFYbyQr@?(R;bxAX0D&)NH&ci$V| z+wafUWAzxTYgNsvHLd3S&FTm1i zeHAeg5RerU5WtnSwK6m@Hvj_@4M|Y`tRg>*nxQTyX6yqc3f&$emnQ+8ErbwF{u@dR zH@hzxLGW}W$JY!Eu}Vkio8}i>vwkhq{&gHw1*L_4U)Tf|vaHe#w+pu*tMga8{j~RQ z`|BJZyrr3B$j5~oz=z^?N4E+1RrKU$Rr27xyLhNJ!R%e!o8z(2&|tG}H{QuEEP2&Q zl{MovcqZSKr;(xd+`*z*gBc)gJ+b?q!MnnMa;n^5f;dHu8L>2q+cpRoL%)0xBobI9 zBEk|_1tKUEm_x2GgPkCF3$C1ND8cGdvoaLBCVe@V8*v>Ip!$%&?1vCOUkh=9_r)N< 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b/docs/7-minute-labs/graphql/index.md @@ -0,0 +1,353 @@ +--- +title: GraphQL in 7 minutes +template: Documentation +nav: + title: GraphQL +--- + +# GraphQL in 7 minutes + +| Goal | Query Turbot Guardrails using GraphQL and learn how to explore the GraphQL API. | +| ---- |---------------------------------------------------------------------------------| +| Time | 7 minutes | + +## Overview + +[GraphQL](https://graphql.org/) is the native query language for the Turbot Guardrails API. + +In this exercise, you will explore the Turbot Guardrails GraphQL API via the GraphiQL +interface built into the Turbot Guardrails Console. + +By the end of this lab, you will be able to query the Turbot Guardrails API with GraphQL, +filter and page through results, and leverage the basic features of the GraphiQL +editor. + +## Open GraphiQL for your Turbot Guardrails Workspace + +GraphiQL is a built-in tool to explore, build and run GraphQL queries in Turbot Guardrails. + +To open the explorer, login to your Turbot Guardrails Workspace and click on **Developers** +in the top right corner. ![GraphiQL](/images/docs/guardrails/graphiql.png) + +## Run your first GraphQL query + +Copy & paste this query into GraphiQL and click run: + +```graphql +{ + resources { + items { + title + } + } +} +``` + +The JSON results will match your requested format: + +```javascript +{ + "data": { + "resources": { + "items": [ + { + "title": "my first resource" + }, + { + "title": "my second resource" + } + ] + } + } +} +``` + +## Expand your query, observing autocomplete capabilities + +Edit the query (resist the urge to copy & paste!) to request extra `turbot` +metadata about the resources: + +```graphql +{ + resources { + items { + title + // highlight-start + turbot { + id + createTimestamp + } + // highlight-end + } + } +} +``` + +While you are editing the query above, you'll see autocompletion options +appearing in the editor. Use this to try adding other fields to the results. + +## Discover inline documentation + +In addition to autocomplete, GraphiQL comes with extensive inline documentation. +Click the `< Docs` link in the top right hand corner to start exploring. + +Search for the `resources` query in the documentation, you'll see it produces a +list of the resource type `[resource]`. + +Clicking through to the resource type, you can see all the available fields. + +## Use filters to target your query + +Add a filter to the resources query to target the results. In this case, we'll +restrict results to the Turbot Guardrails Profile resource type: + +```graphql +{ + resources(filter:"resourceType:profile") { // highlight-line + items { + turbot { + id + createTimestamp + title + } + } + } +} +``` + +Find resources created in the last 6 hours: + +```graphql +{ + resources(filter:"createTimestamp:>=T-6h") { // highlight-line + items { + turbot { + id + createTimestamp + title + } + + } + } +} + +``` + +## Paging through results + +Get the first page of results, including the `next` token. Notice the filter +support for sorting and limiting results. + +```graphql +{ + resources(filter:"resourceType:profile sort:title limit:3") { // highlight-line + items { + turbot { + id + createTimestamp + title + } + } + // highlight-start + paging { + previous + next + } + // highlight-end + } +} +``` + +The result includes `paging` metadata that can be used in the next request: + +```json +{ + "data": { + "resources": { + "items": [ + { + "turbot": { + "id": "162723451277834", + "createTimestamp": "2019-06-19T10:33:40.387Z", + "title": "Batman" + } + }, + { + "turbot": { + "id": "162723451277834", + "createTimestamp": "2019-06-19T10:33:40.387Z", + "title": "Danger Mouse" + } + }, + { + "turbot": { + "id": "162674901433086", + "createTimestamp": "2019-06-18T21:23:28.429Z", + "title": "Superman" + } + } + ], + "paging": { + "previous": null + "next": "eyJzb3J0IjpbeyJ0ZXh0IjoidGl0bGUifSx7InRleHQiOiJpZCIsIm9wZXJhdG9yIjoiLSJ9XSwid2hlcmUiOlt7InBpdm90IjoidGl0bGUiLCJvcGVyYXRvciI6Ij4iLCJ2YWx1ZSI6IkNodWNrIEdhbWJsZSJ9LHsicGl2b3QiOiJpZCIsIm9wZXJhdG9yIjoiPCIsInZhbHVlIjoiMTY1MDQyODYzMjU1MTk2In1dLCJtb2RlIjoibmV4dCJ9" // highlight-line + } + } + } +} +``` + +Query the second page of results by including the `paging` parameter. You have +reached the end of the results set when `next` is returned as null. + +```graphql +{ + resources(filter:"resourceType:profile sort:title limit:3" paging:"eyJzb3J0IjpbeyJ0ZXh0IjoidGl0bGUifSx7InRleHQiOiJpZCIsIm9wZXJhdG9yIjoiLSJ9XSwid2hlcmUiOlt7InBpdm90IjoidGl0bGUiLCJvcGVyYXRvciI6Ij4iLCJ2YWx1ZSI6IkNodWNrIEdhbWJsZSJ9LHsicGl2b3QiOiJpZCIsIm9wZXJhdG9yIjoiPCIsInZhbHVlIjoiMTY1MDQyODYzMjU1MTk2In1dLCJtb2RlIjoibmV4dCJ9") { // highlight-line + items { + turbot { + id + createTimestamp + title + } + } + paging { + previous + next + } + } +} +``` + +The final page of results will have a `previous` token, but `next` is `null`: + +```json +{ + "data": { + "resources": { + "items": [ + { + "turbot": { + "id": "164235079971230", + "createTimestamp": "2019-07-06T12:37:00.283Z", + "title": "Wonder Woman" + } + } + ], + "paging": { + "previous": "eyJzb3J0IjpbeyJ0ZXh0IjoidGl0bGUifSx7InRleHQiOiJpZCIsIm9wZXJhdG9yIjoiLSJ9XSwid2hlcmUiOlt7InBpdm90IjoidGl0bGUiLCJvcGVyYXRvciI6IjwiLCJ2YWx1ZSI6IlJ1cGVzaCBQYXRpbCJ9LHsicGl2b3QiOiJpZCIsIm9wZXJhdG9yIjoiPiIsInZhbHVlIjoiMTYzMTQ1NDk2MDAyNTUxIn1dLCJtb2RlIjoicHJldmlvdXMifQ==", // highlight-line + "next": null // highlight-line + } + } + } +} +``` + +## Mutations + +Mutations allow modifications to existing Turbot resource metadata using +GraphQL. + +It is important to first start with a query to ensure the correct resource is +being acted upon. Consider an example of updating an existing mod in Turbot +using a GraphQL mutation. + +Start with the query of all installed mods to get a list of the names and +versions. + +```graphql +query InstalledMods { + resources( + filter: "resource:'tmod:@turbot/turbot#/' resourceType:tmod:@turbot/turbot#/resource/types/mod resourceTypeLevel:self sort:title limit:200" + ) { + items { + akas + version: get(path: "version") + } + } +} +``` + +An example response looks like the following: + +```json +{ + "data": { + "resources": { + "items": [ + { + "akas": ["tmod:@turbot/aws"], + "version": "5.2.0" + }, + { + "akas": ["tmod:@turbot/aws-acm"], + "version": "5.2.2" + }, + { + "akas": ["tmod:@turbot/aws-amplify"], + "version": "5.0.1" + }, + { + "akas": ["tmod:@turbot/aws-apigateway"], + "version": "5.1.0" + }, + { + "akas": ["tmod:@turbot/aws-appstream"], + "version": "5.0.0-beta.4" + }, + { + "akas": ["tmod:@turbot/aws-athena"], + "version": "5.1.1" + } + ] + } + } +} +``` + +Suppose the `tmod:@turbot/aws` mod needs to be updated. This can be done by +using the following GraphQL mutation. + +```graphql +mutation installMod { + installMod( + input: { + parent: "tmod:@turbot/turbot#/" # AKA or ID for the turbot product + org: "turbot" # Name of the organization to which mod belongs + mod: "aws" # Name of the mod + version: "5.3.0" # Desired version of mod + } + ) { + turbot { + id + } + data + } +} +``` + +The as with other GraphQL queries, the response will be json. + +```json +{ + "data": { + "installMod": { + "turbot": { + "id": "177146224838314" + }, + "data": null + } + } +} +``` + +The `id` returned is the Turbot Id for the mod resource. + +Mutations can also be used to create, change, or delete policy settings, update +local user passwords, as well as creating various Turbot resources such as a +smart folder. + +## Further Reading + +- [Turbot GraphQL API Reference](reference/graphql) +- [Turbot Filter Language Reference](reference/filter) +- [Turbot Guardrails GraphQL Examples in Samples Repo](https://github.com/turbot/guardrails-samples/tree/master/api_examples/graphql/queries) +- [Introduction to GraphQL](https://graphql.org/learn/) diff --git a/docs/7-minute-labs/index.md b/docs/7-minute-labs/index.md new file mode 100644 index 00000000..c555f065 --- /dev/null +++ b/docs/7-minute-labs/index.md @@ -0,0 +1,35 @@ +--- +title: "7-minute Labs" +template: Documentation +nav: + title: "7-minute Labs" + order: 50 +--- + +# 7-minute Labs + +All of these tutorials are designed to get you up and going immediately with simple, practical examples. Get started +fast, and learn as you go! Each lab is a core concept in Turbot Guardrails, and a firm understanding of each will enable +agile development while ensuring that the cloud is secure. Check out +the [Example Policy Configuration](guides/managing-policies/config-examples) page for detailed explanations for customer +oriented control objectives. + +
+ + +| 7-Minute Lab | Description | +|-------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| [Calculated Policies in 7 minutes](7-minute-labs/calc-policy) | Learn how to use Calculated Policies to set policy values dynamically | +| [CLI in 7 minutes](7-minute-labs/cli) | Learn how to query your workspace from the command line. Build and upload your first custom mod | +| [Custom Mod Install, Build, and Deploy](7-minute-labs/custom-mod) | Learn how to clone, install, build, and deploy a custom mod from the Guardrails Samples Repo | +| [GraphQL in 7 minutes](7-minute-labs/graphql) | Learn to query Turbot Guardrails via GraphQL, the native syntax of the Turbot Guardrails API |j +| [Policy Settings in 7 minutes](7-minute-labs/set-policy) | Learn how to create and view Policy Settings | +| [Terraform in 7 minutes](7-minute-labs/terraform) | Learn how to manage your Turbot Guardrails infrastructure as code using Terraform | + + +## Other links + +* Guardrails Samples Repo +* Turbot Guardrails Reference Pages +* Turbot Guardrails + Terraform Provider Documentation diff --git a/docs/7-minute-labs/set-policy/default-policy-value.png b/docs/7-minute-labs/set-policy/default-policy-value.png new file mode 100644 index 0000000000000000000000000000000000000000..4a12e1c7e9f90574d33ebcd0f62610f75789475e GIT binary patch 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z=)V2#Z(!2*?(J{Py*r4pYRC-P7H3mDq2d5RnHt(RudE*h)r3q%{7V$DlWL2uMvIdh z>X;-mqX(Cmc3Jw|k}=SAq`GrK4VKjSMVWTK_1`9w%Ah-W$xp{15NY+OK4B>YV1RQW zw+3(xq78X8sK#+oqN8i<*0>bHE#pV$P~E>re9aKGJo8*YH4w=L>7P(xOV(6wRxzD( zpB~fKIXztKm3iti#MKh>qq~SYz8C0`qAzR6?9>-k-{HX{Ru}l#ivaED?n(`MPn~pf z$-VHSd=EXNQ>w>PYJ@7|?$;DZOstMLk*auO*l%YmksToJ9|WP`LT3Qiderx0@bZ)4 z6a^6Co6Y4O*k3=Pf0*(+HE4|jP~nNNLen26u)Bn9Ot;I0Ph1H5c%Xe$eL9OV!Hx!a Nz{=X73PsEC{{WuqDP#Zu literal 0 HcmV?d00001 diff --git a/docs/7-minute-labs/terraform/index.md b/docs/7-minute-labs/terraform/index.md new file mode 100644 index 00000000..51e4b8db --- /dev/null +++ b/docs/7-minute-labs/terraform/index.md @@ -0,0 +1,361 @@ +--- +title: Terraform in 7 minutes +template: Documentation +nav: + title: Terraform +--- + +# Terraform in 7 minutes + +| Goal | Configure and manage Turbot Guardrails using Terraform. | +| ---- | -------------------------------------------- | +| Time | 7 minutes | + +## Overview + +The [Turbot Guardrails Terraform Provider](reference/terraform) allows you to define +infrastructure as a code to manage the full life cycle of Turbot Guardrails resources — +create new resources, manage existing ones, and destroy those no longer needed. + +In this exercise, you will use the Turbot Guardrails Terraform provider to create a new +[Smart Folder](concepts/resources/smart-folders) and set +[Policies](concepts/policies). + +By the end of this lab, you will be able to create, modify, and delete Turbot Guardrails +resources using Terraform. + +### Prerequisites + +- [Install Terraform](https://learn.hashicorp.com/terraform/getting-started/install.html). + You should have version 0.12 (at minimum) installed for this lab. +- [Install the Turbot Guardrails Terraform Provider](reference/terraform/setup). The + Turbot Guardrails Terraform provider is available via the Hashicorp provider registry. +- [Set up your Turbot Guardrails Credentials](reference/cli/installation#setup-your-turbot-credentials). +- [Install the aws-s3 mod](mods/install). This lab exercise uses policies in the + `aws-s3` mod, so it must be installed in your Workspace. + +## Creating Resources + +### Create the Configuration File + +Terraform provides a mechanism for managing infrastructure using code. +Infrastructure is described using +[Terraform HCL](https://www.terraform.io/docs/configuration/syntax.html) defined +in configuration files. + +In order to create a Turbot Guardrails resource, we need to create a configuration file. To +get started, create a local directory for your lab configuration files. Inside +your new working directory, create a configuration file. + +```bash +mkdir terraform-demo +cd terraform-demo +touch demo.tf +``` + +### Create a Smart Folder + +1. Add the following snippet to the `demo.tf` file that you created in the + previous step. + +```hcl +resource "turbot_smart_folder" "encryption" { + title = "Encryption @ ACME" + description = "Enforce encryption on a range of resource types per ACME policies." + parent = "tmod:@turbot/turbot#/" +} +``` + +2. Navigate to the `terraform-demo` folder and initialize the working directory + for Terraform: + +```bash +$ terraform init + +Initializing the backend... + +Initializing provider plugins... + +The following providers do not have any version constraints in configuration, +so the latest version was installed. + +To prevent automatic upgrades to new major versions that may contain breaking +changes, it is recommended to add version = "..." constraints to the +corresponding provider blocks in configuration, with the constraint strings +suggested below. + +* provider.turbot: version = "~> 1.0" + +Terraform has been successfully initialized! + +You may now begin working with Terraform. Try running "terraform plan" to see +any changes that are required for your infrastructure. All Terraform commands +should now work. + +If you ever set or change modules or backend configuration for Terraform, +rerun this command to reinitialize your working directory. If you forget, other +commands will detect it and remind you to do so if necessary. +``` + +The `terraform init` command will initialize the working directory containing +Terraform configuration files and install any required plugins. + +

    + +3. Next, create an execution plan to preview the changes: Terraform: + +```bash +$ terraform plan +Refreshing Terraform state in-memory prior to plan... +The refreshed state will be used to calculate this plan, but will not be +persisted to local or remote state storage. + + +------------------------------------------------------------------------ + +An execution plan has been generated and is shown below. +Resource actions are indicated with the following symbols: + + create + +Terraform will perform the following actions: + + # turbot_smart_folder.encryption will be created + + resource "turbot_smart_folder" "encryption" { + + description = "Enforce encryption on a range of resource types per ACME policies." + + id = (known after apply) + + parent = "tmod:@turbot/turbot#/" + + parent_akas = (known after apply) + + title = "Encryption @ ACME" + } + +Plan: 1 to add, 0 to change, 0 to destroy. + +------------------------------------------------------------------------ + +Note: You didn't specify an "-out" parameter to save this plan, so Terraform +can't guarantee that exactly these actions will be performed if +"terraform apply" is subsequently run. + +``` + +The `terraform plan` command provides a preview of the actions that Terraform +will take in order to configure resources per the configuration file. In this +case, a single Smart Folder resource will be added. + +4. Having reviewed the changes, apply the configuration to implement them. + Before applying the change, Terraform will show you the planned changes and + prompt you for confirmation. Review the changes and type `yes` to confirm and + apply: + +```bash +$ terraform apply + +An execution plan has been generated and is shown below. +Resource actions are indicated with the following symbols: + + create + +Terraform will perform the following actions: + + # turbot_smart_folder.encryption will be created + + resource "turbot_smart_folder" "encryption" { + + description = "Enforce encryption on a range of resource types per ACME policies." + + id = (known after apply) + + parent = "tmod:@turbot/turbot#/" + + parent_akas = (known after apply) + + title = "Encryption @ ACME" + } + +Plan: 1 to add, 0 to change, 0 to destroy. + +Do you want to perform these actions? + Terraform will perform the actions described above. + Only 'yes' will be accepted to approve. + + Enter a value: yes + +turbot_smart_folder.encryption: Creating... +turbot_smart_folder.encryption: Creation complete after 1s [id=178050816325133] + +Apply complete! Resources: 1 added, 0 changed, 0 destroyed. +``` + +After Terraform completes, a new Smart Folder named **Encryption @ ACME** will +be created in your workspace. + +### Add Encryption Policy Settings + +Now that you have created a Smart Folder, you will add Policy Settings to it. + +1. Add the highlighted code snippet to the configuration file (demo.tf), to set + the `AWS > S3 > Bucket > Encryption at Rest` and + `AWS > S3 > Bucket > Encryption in Transit` policies to the + `Encryption @ ACME` Smart Folder: + +```hcl +resource "turbot_smart_folder" "encryption" { + title = "Encryption @ ACME" + description = "Enforce encryption on a range of resource types per ACME policies." + parent = "tmod:@turbot/turbot#/" +} + +// highlight-start +resource "turbot_policy_setting" "s3_encryption_at_rest" { + resource = turbot_smart_folder.encryption.id + type = "tmod:@turbot/aws-s3#/policy/types/bucketEncryptionAtRest" + value = "Check: AWS SSE" +} + +resource "turbot_policy_setting" "s3_encryption_in_transit" { + resource = turbot_smart_folder.encryption.id + type = "tmod:@turbot/aws-s3#/policy/types/encryptionInTransit" + value = "Check: Enabled" +} +// highlight-end +``` + +2. Preview your configuration changes. Note that the output shows that 2 + resources will be added: + +```bash +terraform plan +``` + +3. Apply the configuration to add the policies to the Smart Folder. + +```bash +terraform apply +``` + +The `Encryption at Rest` and `Encryption in Transit` policy settings will be +created. View the Smart Folder in the Turbot Console to confirm. + +## Updating the configuration + +Resources that are created by Terraform can be modified by changing the +configuration and re-applying. Only the items modified in the configuration will +be updated. In this step we will update `Encryption in Transit` policy to +enforce SSL. + +1. Edit the configuration in `demo.tf`. Modify the value of + `Encryption at Rest` policy from `Check: Enabled` to `Enforce: Enabled`. + +```hcl +resource "turbot_smart_folder" "encryption" { + title = "Encryption @ ACME" + description = "Enforce encryption on a range of resource types per ACME policies." + parent = "tmod:@turbot/turbot#/" +} + +resource "turbot_policy_setting" "s3_encryption_at_rest" { + resource = turbot_smart_folder.encryption.id + type = "tmod:@turbot/aws-s3#/policy/types/bucketEncryptionAtRest" + value = "Check: AWS SSE" +} + +resource "turbot_policy_setting" "s3_encryption_in_transit" { + resource = turbot_smart_folder.encryption.id + type = "tmod:@turbot/aws-s3#/policy/types/encryptionInTransit" + // highlight-start + value = "Enforce: Enabled" + // highlight-end +} +``` + +2. Preview your configuration changes. Note that 1 resource will be updated, and + that the output shows both the old and new value: + +```bash +terraform plan +``` + +3. Apply the configuration to update the Policy Setting. + +```bash +terraform apply +``` + +## Destroying Resources + +Resources that were created via Terraform can also be destroyed with Terraform. + +1. Preview your configuration changes before destroying: + +```bash +terraform plan --destroy +``` + +The output will show the items that will be destroyed and will summarize the +planned changes: `Plan: 0 to add, 0 to change, 3 to destroy.` + +3. Destroy the resources. + +```bash +terraform destroy +``` + +This command will remove the resources that you created using Terraform from +your Turbot Workspace. You can confirm that the Smart Folder and associated +Policy Settings have been deleted in the Turbot Console. + +## Importing existing resources to a Terraform config file + +In the above scenarios, a Terraform plan is created and resources are deployed +based off the Terraform plan. However, there are many situations where a +resource either already exists or is added manually, and as such, admins will +need to add this existing resource into the Terraform state file. + +1. Determine the type of resource that exists and needs to be imported into the + Terraform state file. In this example, an account that already exists in + Turbot will be used. + +2. Create a configuration for the account to be imported within the root module. + In this example, the following code will be added to the `config.tf` file: + +```hcl +resource "turbot_resource" "060977262170" { + parent = "202874855518985" + type = "tmod:@turbot/aws#/resource/types/account" + akas = ["arn:aws:::060977262170"] + data = < +Note: The parent resource can be defined by the Turbot ID or the AKA (i.e. `tmod:@turbot/turbot#/` would be used if the parent is the root Turbot resource). The `Id` is the Turbot Id of the resource that needs to be imported into the Terraform state file. + + +3. Once configured, open a bash terminal and cd into the folder with the + Terraform `config.tf` file. Once there, run the following command: + +```bash +terraform import turbot_resource.060977262170 202875044433112 +``` + +4. The output of the console will show if the import was successful or not. If + there are any errors, verify that the syntax in the Terraform config file is + correct. Just like with YAML, spacing in Terraform files can make the + difference between a successful and unsuccessful import. + +## Further Reading + +- Explore the + [Reference Documentation](https://www.terraform.io/docs/providers/turbot/index.html) + on the official Hashicorp website for detailed information on all supported + resources and authentication. + +- Explore the [Guardrails Samples Repo](https://github.com/turbot/guardrails-samples) for example Terraform + configurations to manage your Turbot Workspace as code. diff --git a/docs/concepts/activities/index.md b/docs/concepts/activities/index.md new file mode 100644 index 00000000..c6b62ab6 --- /dev/null +++ b/docs/concepts/activities/index.md @@ -0,0 +1,64 @@ +--- +title: Resource Activities +sidebar_label: Activities +--- + +# Resource Activities + +Cloud infrastructure constantly changes to meet the demands of modern +applications. One of the fundamental assumptions of Guardrails is that the +management and governance of these applications must also be dynamic - Guardrails +responds in real time to changes in your environment to assure that your +applications continue to operate securely and reliably. The Activity page +provides visibility into the changes that are occurring in your environment. + +Activities represent significant events in the lifecycle of your +infrastructure, including: + +- History of change for a resource (e.g. my-bucket). +- A log of state changes and actions performed by a control (e.g. my-bucket + Tags). +- Changes to policy settings, and the specific policy values they update. +- Records of permission grants, activations, deactivations and revocations. + +
    Guardrails creates a Bucket created activity when it detects that a new S3 Bucket has been created. +This activity includes the bucket name, the creation time, and the person who created it, as well as detailed log information. +
    + +Guardrails maintains a history of all activities that you can search and filter, +providing an audit trail of everything that occurs in your environment. Guardrails +activities contain detailed information about who made the change, the +state/value before and after, the timestamp, and other important information. +You can use the activity pane to determine who made a change, the difference +between the before and after values, and the subsequent related events. In +addition, you can view patterns in activity to help determine impacts, systemic +problems, and other trends. + +## Activity + +Activity logs are displayed throughout the Guardrails user interface. These are +available and browsable on demand, including historical information. + +Activities may be filtered and queried using the +[Guardrails filter language](reference/filter) + +## Activity Types + +| Item | Action | Activity Type | Description | +| ---------------- | ------- | ------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| Action | Notify | `action_notify` | When a Guardrails action invokes a `notify` command during a run. | +| Control | Notify | `control_notify` | When a Guardrails control invokes a `notify` command during a run. | +| Control | Updated | `control_updated` | When a Guardrails control is updated. Notifications will be sent if and only if a control changes state, i.e. `ok` -> `alarm`, `invalid` -> `ok`, etc. If the control updates but the state does NOT change, no notification will be generated. | +| Favorite | Created | `favorite_created` | When a favorite is created for a resource. | +| Favorite | Deleted | `favorite_deleted` | When a favorite is deleted for a resource. | +| Grant Activation | Created | `active_grants_created` | When a Guardrails grant is activated. | +| Grant Activation | Deleted | `active_grants_deleted` | When a Guardrails grant is deleted. | +| Grant | Created | `grant_created` | When a Guardrails grant is created. By default in the UI "Activate for immediate use" is checked. In that case, a `grant_created` notification is generated followed by `active_grants_created`. | +| Grant | Deleted | `grant_deleted` | When a Guardrails grant is deleted. | +| Policy Setting | Created | `policy_setting_created` | When a new Guardrails policy setting is created. | +| Policy Setting | Deleted | `policy_setting_deleted` | When an existing Guardrails policy setting is deleted. | +| Policy Setting | Updated | `policy_setting_updated` | When an existing Guardrails policy setting is updated. | +| Policy Value | Updated | `policy_value_updated` | When a Guardrails policy value is updated. | +| Resource | Created | `resource_created` | When a new resource is created in Guardrails. | +| Resource | Deleted | `resource_deleted` | When a resource in Guardrails is deleted. | +| Resource | Updated | `resource_updated` | When a resource in Guardrails is updated. | diff --git a/docs/concepts/controls/control_types_categories-ex.png 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Depending on what control objective is being monitored and/or enforced, controls can rely on either one or multiple policies to evaluate cloud resources for compliance. + +Controls are where the magic happens with Guardrails. These "control" all policy enforcements, either generating alarms for administrative review or taking action against out of compliance cloud resources. Controls also monitor Guardrails to ensure that resources such as [Mods](mods) are installed correctly. + +Controls rely on resource state and policy settings to operate. Essentially: + +``` +Resource State + Policy Setting = Control State +``` + +As a concrete example: A cloud storage resource does not have encryption at rest configured. In Guardrails, the encryption at rest policy asserts that storage should be encrypted at rest. The encryption at rest control evaluates resource state against the policy then acts. In this case, the control will go into an `alarm` state. If the policy is set to check mode then the control will only go into `alarm`. If in enforce mode, the control will go into `alarm` and Guardrails will act to remediate the resource. When the remediation is successful, the control will rerun then go into `ok`. + +## Control Types + +A **Control Type** is a definition for a particular control. Each different control type is a blueprint that can be configured for resources, such the **Approved** control type for AWS S3 buckets. In this case, the control `AWS > S3 > Bucket > Approved` evaluates policy settings to determine what it means for an S3 bucket to be "Approved," and will take the action defined in the associated, identically named policy (`AWS > S3 > Bucket > Approved`). + +Control types are useful for filtering control objectives. Using the above example, users can drill into the `AWS`, `S3`, `Bucket`, and then `Approved` to see all Approved controls for every bucket managed by Guardrails. This process can be repeated for any control or resource. + +## Control Categories + +Guardrails control types exist for different resources and cloud providers. **Control Categories** provide an alternative to control types, allowing a vendor agnostic categorization of control types. + +For example, the control category `Resource > Encryption at Rest` includes many controls, such as `AWS > S3 > Bucket > Encryption at Rest`, `GCP > Compute > Disk > Encryption at Rest`, and `Azure > Storage > Storage Account > Encryption at Rest`. + +Control categories are typically used for reporting as well as useful aggregation and filtering of data. + +## Control Types and Categories - Visualized + +![control_types_categories](/images/docs/guardrails/control_types_categories-ex.png) + +## Control State + +Controls are responsible for enforcing policy values. This introduces the concept of a **Control State**. After a control has completed running, it is assigned a state, which can depend on a variety of factors, such as the IAM permissions (i.e. can Guardrails describe the resource?), pending work (i.e. is a policy waiting to be calculated?), or simply that the evaluated policy tells the control to not do anything. + +Controls have six different possible states: + +1. **OK** - Generally, this is the desired state of any control in the environment. It implies that Guardrails and cloud resources are working and within the guidelines set by the organization via a policy set. An OK state is denoted by a green checkmark while on the controls tab. +2. **Alarm** - Controls in the alarm state are either waiting to be modified by Guardrails for compliance (this generally clears within a few seconds), or have a policy/ collection of policies configured such that Guardrails is only monitoring cloud resources rather than remediating. Controls in alarm should be investigated by administrators, as enforcement requires review. +3. **Error** - The error state signifies that the control cannot enforce the configured policy values on a specific resource, or that a specific resource is misconfigured. This can be for a variety of reasons, such as the Guardrails role in the target account does not have sufficient permissions to describe or modify a resource. Each error will need to be evaluated by an administrator. Often, the control itself will specify what issue occurred, be it a policy misconfiguration or permissions. If there are any questions or concerns regarding controls in error, contact [Guardrails Support](mailto:help@turbot.com). +4. **Invalid** - This control state means that Guardrails cannot configure, or possibly describe, a particular resource due to policy misconfigurations. For example, if an administrator has the policy `AWS > EC2 > Key Pair` set to `Check: Active`, but all dependent policies such as `AWS > EC2 > Key Pair > Active > Age` are set to skip, Guardrails does not have the required policy settings to accurately evaluate what `Active` means. In this case, the control `AWS > EC2 > Key Pair > Active` is invalid. +5. **Skipped** - A skipped state means that the resource in question is not evaluated by policies by choice. This can range from not enforcing or checking tags on resources to allowing users to build any security group in one or many cloud accounts. +6. **To Be Determined (TBD)** - Controls waiting on policies to be calculated will be in the TBD state. When troubleshooting controls in a TBD state, check the policies tab to ensure that no policies are also in the TBD state. This can be accomplished by navigating to the **Policies** tab, then clicking on **Values**, then setting the **State** dropdown menu on the right side to **TBD**. + +## Control Detail Page + +The **Control Detail Page** contains information that is used to diagnose alarms and errors. Each control type will have different criteria for the final control state. + +For example, the control `AWS > Events > Target > Approved` depends on multiple policies for the eventual control state evaluation. The control detail page makes that explicit. + +Guardrails provides a snapshot view of what the Approved control checks. In this case the control checks the following policies: + +- `AWS > Events > Target > Approved` +- `AWS > Events > Target > Approved > Usage` +- `AWS > Events > Target > Approved > Regions` + +Each one of these policies can be seen on the right hand side of the control detail page, including the state of the policy (very similar to the state of the control, but policy states are a result of the policy value calculation, not policy application) and the value of the policy. + +On this screen, you will find these criteria will be evaluated and presented in a simple manner. The policy evaluations can either be `Approved` or `Not approved`. If troubleshooting unexpected alarms, errors, or resources changes, the control detail window can help diagnose any policy misconfigurations. diff --git a/docs/concepts/guardrails/access-logging.md b/docs/concepts/guardrails/access-logging.md new file mode 100644 index 00000000..6949e80e --- /dev/null +++ b/docs/concepts/guardrails/access-logging.md @@ -0,0 +1,137 @@ +--- +title: Access Logging Guardrails +sidebar_label: Access Logging +--- + +# Access Logging Guardrails + +## Overview + +Access logging guardrails allow administrators to enable and store access +logging information for cloud resources. Access logs are great to help +understand the nature of requests to a particular resource, though it must be +noted that they are +[often not guaranteed delivery](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ServerLogs.html). +From a best practices security standpoint, it is almost always recommended to +have access logging configured if there is an option to do so. + +Guardrails Access Logging policies can be found directly under the service in the +hierarchy: + +- `{Provider} > {service} > {resource} > Access Logging` + +

    +
      +
    • AWS > S3 > Bucket > Access Logging
      • +
    • AWS > EC2 > Application Load Balancer > Access Logging
      • +
    • AWS > EC2 > Classic Load Balancer > Access Logging
      • +
    • AWS > EC2 > Network Load Balancer > Access Logging
      • +
    +
    + +Below is the list of allowed values for a generic Access Logging policy. This is +not comprehensive as different resource types might have slightly different +verbage: + +``` + Skip + Check: Disabled + Check: Enabled + Check: Enabled to Access Logging > Bucket + Enforce: Disabled + Enforce: Enabled to Access Logging > Bucket +``` + +The Access Logging guardrail has a number of policy sub-settings to determine +what Guardrails is checking for. The format of these policy types is +`{Provider} > {service} > {resource} > Access Logging > {Items}`. For example: + +``` + {Provider} > {service} > {resource} > Access Logging > Bucket + {Provider} > {service} > {resource} > Access Logging > Key Prefix +``` + +### Policy Types Description + +| Policy | Description | +| ------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- | +| `{Provider} > {service} > {resource} > Audit Logging` | Allows you to check or enforce access logging requirement for the resource. | +| `{Provider} > {service} > {resource} > Audit Logging > Bucket` | The name of a S3 bucket to which the resource access logs is stored. | +| `{Provider} > {service} > {resource} > Audit Logging > Key Prefix` | Define a folder (optional) inside S3 bucket to which the resource access logs is stored. | + +**Notes**: + +- The `AWS > S3 > Bucket > Access Logging` control will skip any buckets that + are created as part of the `AWS > Turbot > Logging > Bucket` stack. +- For S3 access logs, the target bucket must be in the same region as the source + bucket. +- Server access logs are delivered to the target bucket by a delivery account + called the + [Log Delivery group](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ServerLogs.html). + The S3 log delivery group must have access to `write objects` and + `read bucket ACL`. +- Similarly for EC2 load balancers, the bucket must have proper access granted. + AWS provides documentation for + [Application Load Balancers (ALB)](https://docs.aws.amazon.com/elasticloadbalancing/latest/application/load-balancer-access-logs.html), + [Network Load Balancers (NLB)](https://docs.aws.amazon.com/elasticloadbalancing/latest/network/load-balancer-access-logs.html), + and + [Classic Load Balancers](https://docs.aws.amazon.com/elasticloadbalancing/latest/classic/access-log-collection.html) + for prerequisite steps prior to enabling Access Logging. +- For more details refer + [Enabling Amazon S3 server access logging](https://docs.aws.amazon.com/AmazonS3/latest/userguide/enable-server-access-logging.html). +- [Access log requests are delivered on a best-effort basis](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ServerLogs.html). + AWS recommends that you use access logs to understand the nature of the + requests, not as a complete accounting of all requests. It is good to keep + this in mind when dealing with access logging in other cloud providers, too. + +## Access Logging for Guardrails Managed Buckets + +Guardrails provides policies to allow the automatic creation of logging buckets for +use in services that require them. Guardrails logging bucket creation is managed by +a stack, `AWS > Turbot > Logging > Bucket`, and is targeted at AWS regions. For +more information, refer +[Stacks and Configured guardrail](concepts/guardrails/configured). + +The Guardrails Access Logging guardrail has a number of policy sub-settings to +determine the attributes of the access logging check. The format of these policy +types is `{Provider} > Turbot > Logging > Bucket > Access Logging > {Items}`: + +``` + {Provider} > Turbot > Logging > Bucket > Access Logging + {Provider} > Turbot > Logging > Bucket > Access Logging > Bucket + {Provider} > Turbot > Logging > Bucket > Access Logging > Key Prefix +``` + +Example family of policies: + +
    +
      +
    • AWS > Turbot > Logging > Bucket > Access Logging
      • +
    • AWS > Turbot > Logging > Bucket > Access Logging > Bucket
      • +
    • AWS > Turbot > Logging > Bucket > Access Logging > Key Prefix
      • +
    +
    + +Example policy values: + +
    +
    +    # AWS > Turbot > Logging > Bucket > Access Logging
+      - Disabled
+      - Enabled
+
    +
    + +| Policy | Description | +| ---------------------------------------------------------------------- | --------------------------------------------------------------------------------------- | +| `{Provider} > Turbot > Logging > Bucket > Access Logging` | Allows you to enable or disable access logging requirement for the services. | +| `{Provider} > Turbot > Logging > Bucket > Access Logging > Bucket` | The name of a S3 bucket to which the services access logs is stored. | +| `{Provider} > Turbot > Logging > Bucket > Access Logging > Key Prefix` | Define a folder(Optional) inside S3 bucket to which the services access logs is stored. | + +**Note**: + +- Server access logs are delivered to the target bucket by a delivery account + called the + [Log Delivery group](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ServerLogs.html). + The S3 log delivery group must have access to `write objects` and + `read bucket ACL`. diff --git a/docs/concepts/guardrails/active.md b/docs/concepts/guardrails/active.md new file mode 100644 index 00000000..df1c1138 --- /dev/null +++ b/docs/concepts/guardrails/active.md @@ -0,0 +1,169 @@ +--- +title: Active Guardrails +sidebar_label: Active +--- + +# Active Guardrails + +## Overview + +The Active guardrail flags whether the resource is in active use, and if not, +has the ability to delete/cleanup the resource. When running an automated +compliance environment, it's common to end up with a wide range of alarms that +are difficult and time consuming to clear. The Active guardrail brings +automated, well-defined control to this process. + +The Active guardrail is completely independent of the Approved guardrail. For +example, an Approved resource may actually be Inactive - e.g. an S3 bucket +created 2 years ago with no items and no usage. Similarly, an Unapproved +resource may be Active - e.g. an S3 bucket in an unapproved region that is still +receiving active traffic. + +In general, Approved is considered more at the point of resource creation while +Active is considered more as the resource reaches the end of it's useful life. + +The Active guardrail checks the status of the defined Active policies for the +resource, raises an alarm, and takes the defined enforcement action. Each Active +sub-policy can calculate a status of active, inactive or skipped. Generally, if +the resource appears to be Active for any reason it will be considered Active. +Note the contrast with Approved, where if the resource appears to be Unapproved +for any reason it will be considered Unapproved. + +The core Active policy has a consistent form: `{service} > {resource} > Active` + +
    +
      +
    • AWS > S3 > Bucket > Active
      • +
    • AWS > SNS > Topic > Active
      • +
    • AWS > EC2 > Instance > Active
      • +
    +
    + +The values for this policy reflect how it should be checked and the action to +take if the resource is not active. The basic form is: + +``` + Skip + Check: Active + Enforce: {action} inactive with {period} warning +``` + +
    +
    {`    # AWS > S3 > Bucket Active
+    - Skip
+    - Check: Active
+    - Enforce: Delete with 1 day warning
+    - Enforce: Delete with 3 days warning
+    - Enforce: Delete with 7 days warning
+    - Enforce: Delete with 14 days warning
+    - Enforce: Delete with 30 days warning
+    - Enforce: Delete with 60 days warning
+    - Enforce: Delete with 90 days warning
+    - Enforce: Delete with 180 days warning
+    - Enforce: Delete with 365 days warning`}
    +
    + +The alarm lifecycle is as follows: + +- If Active, the status is OK. +- If Inactive, the status is ALARM and the warning period starts. +- If Inactive and the warning period has expired, the enforcement action is + taken. +- The enforcement action is typically a delete, which will then automatically + cleanup the alarm. If it fails, the alarm will remain in ALARM or ERROR state. + +The Active guardrail and policy have a number of sub-settings to determine the +attributes of the Active check. The format of these policy types is +`{service} > {resource} > Active > {Items}`: + +``` + {service} > {resource} > Active > Status + {service} > {resource} > Active > Last Modified + {service} > {resource} > Active > Recently Used + {service} > {resource} > Active > Age +``` + +Each of these policies defines rules or settings to determine if that specific +area or attribute of the resource is Active. Per above, if **any** Active +sub-check returns active then the overall resource is active. + +
    +
      +
    • AWS > IAM > Access Key > Active > Age
      • +
    • AWS > IAM > Access Key > Active > Status
      • +
    • AWS > IAM > Access Key > Active > Last Modified
      • +
    • AWS > IAM > Access Key > Active > Recently Used
      • +
    +
    + +## Guardrails Resource Active Evaluation + +For an Active control, the status is based on the evaluation of the child policy +conditions. This happens in the following order: + +1. If any of the **Active > \*** policies evaluate to `Force Active`, the + resource is `Active`. +2. If any of the **Active > \*** policies evaluate to `Force Inactive`, the + resource is `Inactive`. +3. If any of the **Active > \*** policies evaluate to `Active`, the resource is + `Active`. +4. If any of the **Active > \*** policies evaluate to `Inactive`, the resource + is `Inactive`. +5. If all **Active > \*** policies evaluates to `Skip`, the control will be in + `Skipped`. + +For example, if one policy evaluates to `Inactive`, but another evaluates to +`Force Active`, the resulting control will deem the resource `Active`. + +Active controls are designed to be slow to decide, but forceful in action. This +is in contrast to the `Approved` family of policies, guardrails, and controls, +which are designed to be fast to decide, but weak in action. + +### Example: AWS > EC2 > Instance > Active + +First, assume that the instance is 60 days old, but it was last modified only 15 +days ago (i.e. tags on the instance were changed). The following policies have +been configured in Guardrails: + +- **AWS > EC2 > Instance > Active > Age** is set to + `Force inactive if age > 60 days`. +- **AWS > EC2 > Instance > Active > Last Modified** is set to + `Active if last modified <= 30 days`. +- **AWS > EC2 > Instance > Active > Budget** is set to + `Force inactive if Budget > State is Over or higher`. +- **AWS > Account > Budget > State** is set to `Under`. +- **AWS > EC2 > Instance > Active** is set to `Check: Active`. + +In order, these policies will evaluate to `Active` (age is equal to 60 days), +`Active` (modified within the last 30 days) and `Active` (As Account spending is +below the budget and the current state is under). Using the rules above, the +final result is that the instance is `Active`. The last policy in the list tells +the `AWS > EC2 > Instance > Active` control how to evaluate the result. In this +case, the control is simply checking the instance for being active or not. The +policy evaluation of `Active` results in the control being in the **OK** state. + +### Example: AWS > EC2 > Volume > Active + +First, assume that the volume is 170 days old, but it was last modified 58 days +ago (i.e. tags on the volume were changed). The volume is available and not +attached to any instance. The following policies have been configured in Guardrails: + +- **AWS > EC2 > Volume > Active > Age** is set to + `Force inactive if age > 180 days`. +- **AWS > EC2 > Volume > Active > Last Modified** is set to + `Active if last modified <= 60 days`. +- **AWS > EC2 > Volume > Active > Attached** is set to + `Force inactive if unattached`. +- **AWS > EC2 > Volume > Active > Budget** is set to `Skip`. +- **AWS > EC2 > Volume > Active** is set to + `Enforce: Detach, snapshot and delete inactive with 7 days warning`. + +In order, these policies will evaluate to `Active` (age is less than 180 days) , +`Active` (modified within the last 60 days) and `Force inactive` as the volume +is not attached. Using the rules above, the final result is that the volume is +`Force inactive`. The last policy in the list tells the +`AWS > EC2 > Volume > Active` control how to evaluate the result. The policy +evaluation of `Force inactive` results in the control being in the **ALARM** +state. In this case, the control is going to take action and will schedule +volume deletion in 7 days from the date of alarm. A snapshot will get created +prior to deleting the volume. diff --git a/docs/concepts/guardrails/approved.md b/docs/concepts/guardrails/approved.md new file mode 100644 index 00000000..95a1a6b4 --- /dev/null +++ b/docs/concepts/guardrails/approved.md @@ -0,0 +1,224 @@ +--- +title: Approved Guardrails +sidebar_label: Approved +--- + +# Approved Guardrails + +## Overview + +The Approved guardrail is used to verify whether a particular resource is +allowed to exist, and to take an appropriate action if required (shutdown, +delete, etc). + +The Approved guardrail is completely independent of the Active guardrail. For +example, an Approved resource may actually be Inactive - e.g. an S3 bucket +created 2 years ago with no items and no usage. Similarly, an Unapproved +resource may be Active - e.g. an S3 bucket in an unapproved region that is still +receiving active traffic. + +In general, Approved is considered more at the point of resource creation, while +Active is considered more as the resource reaches the end of its useful life. + +The Approved guardrail checks the status of the defined Approved sub-policies +for the resource. If the resource is not approved according to _any_ of these +policies, this control raises an alarm and takes the defined enforcement action. + +For any enforcement actions that specify `if new`, e.g., +`Enforce: Delete unapproved if new`, this control will only run the enforcement +actions for resources created within the last 60 minutes. + +The core Approved policy has a consistent form: +`{service} > {resource} > Approved` + +
    +
      +
    • AWS > S3 > Bucket > Approved
      • +
    • AWS > SNS > Topic > Approved
      • +
    • AWS > EC2 > Instance > Approved
      • +
    +
    + +The Approved guardrail and policy have a number of sub-settings to determine the +attributes of the Approved check. The format of these policy types is +`{service} > {resource} > Approved > {Items}`: + +``` + {service} > {resource} > Approved > Regions + {service} > {resource} > Approved > Usage + +``` + +Each of these policies defines rules or settings to determine if that specific +area or attribute of the resource is Approved. Per above, **all** approval tests +must pass - if any Approved sub-check returns `unapproved` then the overall +resource is unapproved. + +### Example Guardrail: AWS > EC2 > Instance > Approved + +The `AWS > EC2 > Instance > Approved` policy determine the action to take if an +instance is not approved. You can set the policy to skip (don't run at all), to +check whether unapproved instances exist and raise an alarm, or to enforce that +unapproved instances are stopped and/or terminated. + +The Approved sub-policies allow you to set the rules for which instance types, +regions, encryption settings, AMI IDs, Publishers of AMIs etc are approved: + +
    +
      +
    • AWS > EC2 > Instance > Approved > Instance Types
      • +
    • AWS > EC2 > Instance > Approved > Public IP
      • +
    • AWS > EC2 > Instance > Approved > Regions
      • +
    • AWS > EC2 > Instance > Approved > Usage
      • +
    • AWS > EC2 > Instance > Approved > Image > AMI IDs
      • +
    • AWS > EC2 > Instance > Approved > Image > Publishers
      • +
    +
    + +### Example Guardrail: AWS > VPC > Security Group > Egress Rules > Approved + +Organizations need to keep a close eye on egress security group rules, but at +scale it can become difficult to track, check, and remediate security groups. +Using Guardrails' egress approved policies, we can define allowed ports, CIDR +blocks, minimum bitmask, and more. Guardrails will check or remediate when +violations are detected. + +
    +
      +
    • AWS > VPC > Security Group > Egress Rules > Approved
      • +
    • AWS > VPC > Security Group > Egress Rules > Approved > Rules
      • +
    • AWS > VPC > Security Group > Egress Rules > Approved > Minimum Bitmask
      • +
    • AWS > VPC > Security Group > Egress Rules > Approved > Prohibited Ports
      • +
    • AWS > VPC > Security Group > Egress Rules > Approved > CIDR Ranges
      • +
    • AWS > VPC > Security Group > Egress Rules > Approved > Maximum Port Range
      • +
    • AWS > VPC > Security Group > Egress Rules > Approved > Compiled Rules
      • +
    +
    + +The base policy, `AWS > VPC > Security Group > Egress Rules > Approved`, is +usually the last one to be set, but is also the most important. This tells +Turbot Guardrails HOW to act - the rest of the policies tell Turbot Guardrails what is valid and what +is not within security group egress rules. + +Let's assume that we want to reject any egress rule pointing to 0.0.0.0/0 and +approve anything else. Additionally, we want to set a minimum bitmask of 4 and +maximum port range as 10. + +First, set the approved sub policies. Doing this allows us to enable all of the +sub policies at once. If we had enabled the approved policy first, each +subsequent setting triggers control runs. This can get noisy, messy, and could +generate false positives (or negatives). + +- `AWS > VPC > Security Group > Egress Rules > Approved > Minimum Bitmask` set + to `4`. +- `AWS > VPC > Security Group > Egress Rules > Approved > Maximum Port Range` + set to `10`. + +For the `AWS > VPC > Security Group > Egress Rules > Approved > Rules` policy, +we will define the following block: + +```ocl +# Reject any rule from 0.0.0.0/0 +REJECT $.turbot.cidr:0.0.0.0/0 + +# Approve everything else. +APPROVE * +``` + +Once these are created, we are ready to enable Guardrails' auto remediation of +security group egress rules! Simply set the policy +`AWS > VPC > Security Group > Egress Rules > Approved` to +`Enforce: Delete unapproved`. + +Immediately following the creation of the `Approved` policy, Guardrails will begin +running controls against all security groups that have the setting applied! +Guardrails will continue to monitor new and existing security groups and take +remediation action if necessary! + +### Custom Checks + +You can create your own custom checks against resource attributes in the +Approved control using the `Approved > Custom` policy. These custom checks would +be a part of the evaluation of the Approved control. Custom messages can also be +added which are then displayed in the control details table. + +For instance, let's assume we want to have the `AWS > KMS > Key > Approved` +control to alarm if automatic key rotation is not enabled for the key by +checking the `KeyRotationStatus` attribute. + +Using the calculated policy builder, set the +`AWS > KMS > Key > Approved > Custom` policy to: + +Input query: + +```graphql +{ + resource { + KeyRotationStatus: get(path: "KeyRotationStatus") + } +} +``` + +Template: + +```nunjucks +{% if $.resource.KeyRotationStatus %} + "Approved" +{% else %} + "Not approved" +{% endif %} +``` + +To add a custom key and message, both of which will then show up in the details +table, update the template to: + +```nunjucks +{% if $.resource.KeyRotationStatus %} + result: Approved + message: Key rotation is enabled + title: Key Rotation Status +{% else %} + result: Not approved + message: Key rotation is disabled + title: Key Rotation Status +{% endif %} +``` + +The Custom policy can be used to check multiple attributes as well by setting +the policy value to a list of objects. For instance, to check if the key is +enabled and automatic key rotation is enabled, use the following input query and +template: + +Input query: + +```graphql +{ + resource { + KeyRotationStatus: get(path: "KeyRotationStatus") + KeyState: get(path: "KeyState") + } +} +``` + +Template: + +```nunjucks +{% if $.resource.KeyRotationStatus %} + - result: Approved + message: Key rotation is enabled + title: Key Rotation Status +{% else %} + - result: Not approved + message: Key rotation is disabled + title: Key Rotation Status +{% endif %} +{% if $.resource.KeyState === "Enabled" %} + - result: Approved + message: Key is enabled + title: Key State +{% else %} + - result: Not approved + message: Key is disabled + title: Key State +{% endif %} +``` diff --git a/docs/concepts/guardrails/audit-logging.md b/docs/concepts/guardrails/audit-logging.md new file mode 100644 index 00000000..fda5738a --- /dev/null +++ b/docs/concepts/guardrails/audit-logging.md @@ -0,0 +1,103 @@ +--- +title: Audit Logging Guardrails +sidebar_label: Audit Logging +--- + +# Audit Logging Guardrails + +## Overview + +Audit Logging guardrails allow administrators to enable logging on the cluster +and databases. With Turbot Guardrails Audit Logging policies, administrators can define +where to store the logs depending on the resource. The Audit Logging control can +audit or enforce those policies, giving centralized control over data that is +stored, such as data subject to compliance or regulatory requirements. + +The core Audit Logging policy has a consistent form: +`{Provider} > {service} > {resource} > Audit Logging` + +
    +
      +
    • AWS > Redshift > Cluster > Audit Logging
      • +
    • Azure > PostgreSQL > Server > Audit Logging
      • +
    +
    + +Below are the list of allowed values for the Audit Logging policy. Depending on +the resource type it can be different. The basic form is: + +``` + Skip + Check: Disabled + Check: Enabled + Check: Enabled to Audit Logging > Bucket + Enforce: Disabled + Enforce: Enabled to Audit Logging > Bucket + Check: Audit Logging > * + Enforce: Audit Logging > * +``` + +
    +
    +    # AWS > Redshift > Cluster > Audit Logging
+    - Skip
+    - Check: Disabled
+    - Check: Enabled
+    - Check: Enabled to Audit Logging > Bucket
+    - Enforce: Disabled
+    - Enforce: Enabled to Audit Logging > Bucket
+
    +
    +    # Azure > PostgreSQL > Server > Audit Logging
+    - Skip
+    - Check: Audit Logging > *
+    - Enforce: Audit Logging > *
+
    +
    + +The Audit Logging guardrail for AWS resources has a number of policy +sub-settings to determine the attributes of the audit logging check. The format +of these policy types is +`{Provider} > {service} > {resource} > Audit Logging > {Items}`: + +``` + {Provider} > {service} > {resource} > Audit Logging > User Activity Logging + {Provider} > {service} > {resource} > Audit Logging > Bucket + {Provider} > {service} > {resource} > Audit Logging > Key Prefix +``` + +The Audit Logging guardrail for Azure resources have a number of policy +sub-settings to determine the attributes of the audit logging check. The format +of these policy types is +`{Provider} > {service} > {resource} > Audit Logging > {Items}`: + +``` + {Provider} > {service} > {resource} > Audit Logging > Log Checkpoints + {Provider} > {service} > {resource} > Audit Logging > Log Retention Days + {Provider} > {service} > {resource} > Audit Logging > Log Duration + {Provider} > {service} > {resource} > Audit Logging > Log Connections + {Provider} > {service} > {resource} > Audit Logging > Log Disconnections +``` + +### Policy Types Description + +| Policy | Description | +| ----------------------------------------------------------------------------- | -------------------------------------------------------------------------------------- | +| `{Provider} > {service} > {resource} > Audit Logging` | Allows you to check or enforce audit logging requirement for the resource. | +| `{Provider} > {service} > {resource} > Audit Logging > User Activity Logging` | Define the user activity audit logging settings required for the resource. | +| `{Provider} > {service} > {resource} > Audit Logging > Bucket` | The name of a S3 bucket to which the resource audit logs is stored. | +| `{Provider} > {service} > {resource} > Audit Logging > Key Prefix` | Define a folder(Optional) inside S3 bucket to which the resource audit logs is stored. | +| `{Provider} > {service} > {resource} > Audit Logging > Log Checkpoints` | Sets desired value for each checkpoint. | +| `{Provider} > {service} > {resource} > Audit Logging > Log Retention Days` | Sets the number of days a log file is saved for. | +| `{Provider} > {service} > {resource} > Audit Logging > Log Duration` | Sets the desired value to log the duration of each completed SQL statement. | +| `{Provider} > {service} > {resource} > Audit Logging > Log Connections` | Sets the desired value to log each successful connection. | +| `{Provider} > {service} > {resource} > Audit Logging > Log Disconnections` | Sets the desired value to log end of a session, including duration. | + +**Note**: + +- The `Audit Logging` control evaluates and take actions if and only if the + parameter group of the cluster is not the default and is not shared with any + other cluster. If these conditions are not met, the control is set in the + `invalid` state. +- The S3 bucket configured to inject the logs must exist in the same region as + the cluster and the Redshift service must be allowed write access. diff --git a/docs/concepts/guardrails/budget.md b/docs/concepts/guardrails/budget.md new file mode 100644 index 00000000..15ce12e1 --- /dev/null +++ b/docs/concepts/guardrails/budget.md @@ -0,0 +1,164 @@ +--- +title: Budget Guardrails +sidebar_label: Budget +--- + +# Budget Guardrails + +## Overview + +Budget guardrails provide a mechanism for tracking current spend against +a planned target, and taking appropriate actions to help control cost. + +Current and forecast spend APIs are used to get information on the budget. This +is currently available for AWS only. + +## Policy Types + +Budget policies can be broadly classified into two categories: + +- Account-level settings for the target and the current spend etc, as well as + permission settings in lockdown policies to restrict access. +- Service/ Resource-level settings for taking action based on the budget state. + These are defined in specific services and leverage existing controls such as + `Active` and `Approved + +### Policy Types Description + +| Policy | Description | +| ------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `AWS > Account > Budget > Enabled` | Determine whether budget reporting is enabled for the account or not. | +| `AWS > Account > Budget > Target` | The budget target for the AWS Account in US Dollars. | +| `AWS > Account > Budget > State` | Calculates the current status of the set budget. The default policy setting is generally sufficient. | +| `AWS > Account > Permissions > Lockdown > Budget` | Configure lockdown policies to restrict APIs based on the budget state (when the current spend exceeds a defined threshold). | +| `AWS > Account > Permissions > Lockdown > Budget > Restricted APIs` | A list of APIs that is restricted when the budget reaches the defined state. | +| `{provider} > {service} > {resource type} > Active > Budget` | The policy allows you to force {resource type} to the inactive status based on the current budget state, as defined in `AWS > Account > Budget > State`. | +| `{provider} > {service} > {resource type} > Approved > Budget` | The policy allows you to set {resource type} to Not approved based on the current budget state, as defined in `AWS > Account > Budget > State`. | + +### Policy Types Definition + +#### Account Level Policies + +- Account-level policies appear under `AWS > Account > Budget` in the type + hierarchies, and are used to set and/ or view settings, values, and + definitions that are shared by all services. +- The state of the budget is determined by the interaction of several account + level policies: + - The `Budget > Enabled` policy allows you to enable or disable budget + checking. If set to `Skip` (the default), The budget control should not look + up the budget data in the account. +- The `Budget > State` policy a calculated value by default. It reflects the + current state of the actual and forecast spend, as compared to the budget + target set. The resource-level budget policies will use this policy to + determine the actions to minimize cost. +- The `Budget > Target` policy allows you to set the budget (allowed spend) for + the account. The `Budget > State` will be set in relation to this amount. + +#### Budget States + +- Guardrails defines named budget states. The enforcement policies and controls will + refer to these states and will use the current state to determine when to take + action. +- The states are as follows: + +| State | Description | +| ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `Shutdown` | Budget is completely spent, or trending significantly over. No more money is available. All spending must cease, even if it results in degraded service. | +| `Critical` | Budget is completely spent, or trending significantly over. Urgent action is needed to reduce spend. | +| `Over` | Current or forecast spend exceeds the budget target. | +| `On target` | Current and forecast spend are in line with the budget target. No action is required. | +| `Under` | Current and forecast spend are lower than projected. | +| `Unused` | Current and forecast spend is so low that it appears that the account may not be in-use. | +| `Unknown` | Current and forecast spend is unknown for the account. | + +**Note**: + +- The default value for `AWS > Account > Budget > Target` is -1. If the policy + value for the `AWS > Account > Budget > Enabled` policy is not Skip, and the + `AWS > Account > Budget > Target` is < 0, the control should move to an + `invalid` state, and informing the user to set the + `AWS > Account > Budget > Target` policy to a positive integer value. + +#### Account Level Preventive - Permissions + +- Account level preventive policies can be set to enforce preventative controls + via AWS lockdown policies. +- You can enable lockdowns via the + `AWS > Account > Permissions > Lockdown > Budget` policy. +- You can specify which api actions will be locked via the + `AWS > Account > Permissions > Lockdown > Budget > Restricted APIs` policy, + which allows you to set a list of IAM actions that are prevented for each + state. For example: + +```yaml +critical: + - ec2:RunInstance + - ec2:StartInstance + - rds:StartDB* + - redshift:createcluster +``` + +#### Resource Level Policies + +- The budget policies defined as part of the `Active` control is used to + determine whether the resource is `active` or `inactive` based on the current + budget state of the account. +- The budget policies defined as part of the `Approved` control is used to + determine whether the resource is `approved` or `unapproved` based on the + current budget state of the account. + +The **Active > Budget** policy has a consistent form: {Provider} > {service} > +{resource} > Active > Budget + +
    +
      +
    • AWS > EC2 > Instance > Active > Budget
      • +
    • AWS > RDS > DB Cluster > Active > Budget
      • +
    • AWS > Redshift > Cluster > Active > Budget
      • +
    +
    + +The values for this policy reflect when it should be `inactive`. The basic form +is: + +``` + Skip + Force inactive if Budget > State is Over or higher + Force inactive if Budget > State is Critical or higher + Force inactive if Budget > State is Shutdown +``` + +The **Approved > Budget** policy has a consistent form: {Provider} > {service} > +{resource} > Approved > Budget + +
    +
      +
    • AWS > EC2 > Instance > Approved > Budget
      • +
    • AWS > RDS > DB Cluster > Approved > Budget
      • +
    • AWS > Redshift > Cluster > Approved > Budget
      • +
    +
    + +The values for this policy reflect when it should be `unapproved`. The basic +form is: + +``` + Skip + Unapproved if Budget > State is Over or higher + Unapproved if Budget > State is Critical or higher + Unapproved if Budget > State is Shutdown +``` + +### Example: AWS > Account > Budget > Enabled + +First, assume that the monthly actual spent becomes $ 1001. The following +policies have been configured in Guardrails: + +- **AWS > Account > Budget > Enabled** is set to + `Check: Budget > State is on Target or below`. +- **AWS > Account > Budget > Targe** is set to `1000`. +- **AWS > Account > Budget > State** is calculated to `Over`. + +In order, these policies will evaluate account spending is over the budget and +has entered the `Over` state. The policy evaluation of `Budget > Enabled` +results the control being in **ALARM** state. diff --git a/docs/concepts/guardrails/cmdb.md b/docs/concepts/guardrails/cmdb.md new file mode 100644 index 00000000..d885bb1f --- /dev/null +++ b/docs/concepts/guardrails/cmdb.md @@ -0,0 +1,32 @@ +--- +title: CMDB Guardrails +sidebar_label: CMDB +--- + +# CMDB Guardrails + +## Overview + +The CMDB control is responsible for populating and updating all the attributes +for that resource type in the Guardrails CMDB. + +
    The Resource Type AWS > SQS > Queue defines a +Control AWS > SQS > Queue > CMDB with a target Resource Type of AWS > SQS > Queue. +
    + +### Policies to control CMDB + +CMDB controls have an associated policy that allows them to be enforced or +skipped. Note, however, that if CMDB is set to `Skip` for a resource, then it +will not exist in the CMDB, and _no controls that target it will run_. + +
    The AWS > S3 > Bucket > CMDB policy may be set to `Skip` or `Enforce: Enabled` +
    + +CMDB controls also use the `Region` policy associated with the resource. If +region is not in `Regions` policy, the CMDB control should delete the resource +from the CMDB (since we don’t want to capture any resources in that region, we +should also cleanup). + +
    The AWS > S3 > Bucket > CMDB will add/modify a resource in the CMDB if the resource is in region specified in AWS > S3 > Bucket > Regions, and delete it from the CMDB if it is not. +
    diff --git a/docs/concepts/guardrails/configured.md b/docs/concepts/guardrails/configured.md new file mode 100644 index 00000000..241dcbcc --- /dev/null +++ b/docs/concepts/guardrails/configured.md @@ -0,0 +1,506 @@ +--- +title: Stacks and Configured Guardrails +sidebar_label: Stack/Configured +--- + +# Stacks and the Configured Guardrails + +## Overview + +Guardrails provides a mechanism for managing resource configuration using Terraform. +Guardrails **Stack** and **Configured** controls allow you to define the +configuration for a resource or set of resources using standard Terraform HCL. +Guardrails can apply your configuration whenever resources change, enforcing your +standards and preventing configuration drift. + +- A **Stack** is a set of resources configured via a terraform source from + Guardrails. +- A resource can configure itself using terraform via its **Configured** + control. + +
    +A resource does not need to be configured by a Guardrails stack or configured policy to be managed by other guardrails. +
    + +### Stacks + +A Guardrails **Stack** is a set of resources managed by Turbot Guardrails using Terraform. +Guardrails uses stacks to deploy, configure, and manage sets of related resources. + +Each stack has a single `Source` policy that specifies the Terraform +configuration source code. When the stack control runs, resources will be +created, modified or deleted per the `Source`. + +Stacks are responsible for the creation and deletion of multiple resources. Once +created, the resources are responsible for updating themselves via the +[Configured control](#configured-control). Changes to the underlying resources +will trigger the resource's Configured control to run. The Configured control +will use the `Source` from the parent stack to re-apply its configuration, +keeping it configured per the policy. + +
    +After being created by the AWS > Turbot > Event Handlers stack, the configuration of a the turbot_aws_api_handler SNS Topic is managed by its AWS > SNS > Topic > Configured control. If the topic is modified, the AWS > SNS > Topic > Configured control will re-apply its configuration using the terfafrom source defined in the AWS > Turbot > Event Handlers > Source policy +
    + +#### Stack Terraform Version + +Guardrails Stacks supports up to the most recent +[Terraform 0.15 version](https://github.com/hashicorp/terraform/blob/v0.15/CHANGELOG.md), +which is 0.15.5. Using the policy family `* > * > Terraform Version`, users can +define which version of Terraform to use. The policy +`Turbot > Stack Terraform Version [Default]` can be used to define the Terraform +version across all stack policies. + +**Notes**: + +- While the policy allows administrators to specify any version of Terraform, + only the "oldest" minor version for each patch is valid. I.e. `0.11.*` and + `0.11.12` are valid values, but `0.11.10` is not. In general, it is + recommended to use `*` in conjunction with the patch version. +- Guardrails supports the different syntax of each version, but does NOT support the + use of new features or modules. + +Supported values for the policy `* > * > Terraform Version`: + +- `0.11.*` or `0.11.14` +- `0.12.*` or `0.12.28` +- `0.13.*` or `0.13.0-beta3` +- `0.14.*` or `0.14.11` +- `0.15.*` or `0.15.5` +- `*` This value will use the latest version of Terraform. + +#### Guardrails-Defined Stacks + +Guardrails provides pre-defined stacks to assist with common setup and configuration +tasks. Guardrails-defined stacks manage common resources required to operate Guardrails, +as well as resources used as containers or defaults for other controls. + +Guardrails-defined stacks typically appear under `{provider} > Turbot` in the policy +type hierarchy. + +
    +Guardrails-defined stacks include: +
      +
    • GCP > Turbot > Event Handlers
      • +
    • Azure > Turbot > Event Handlers
      • +
    • AWS > Turbot > Event Handlers
      • +
    • AWS > Turbot > Audit Trail
      • +
    • AWS > Turbot > Logging
      • +
    • AWS > Turbot > OS Management
      • +
    • AWS > Turbot > Service Roles
      • +
    +
    + +The `Source` policy is read-only for Guardrails-defined stacks, and is generated by +Guardrails. Sub-policies of the stack allow you to change common parameters, +providing a simple interface for customizing resources created by the stack. +Modifying a stack policy will result in changes in the stack source policy, +which in turn will run the stack to apply the changes. + +
    +The AWS > Turbot > Logging > Bucket stack creates and manages S3 buckets used by multiple AWS services for logging. This stack is configured per the AWS > Turbot > Logging > Bucket > Source> policy, which is generated using policies that allow you to set options to customime the bucket name, tags, and other properties: + +
      +
    • AWS > Turbot > Logging > Bucket > Default Encryption
      • +
    • AWS > Turbot > Logging > Bucket > Name
      • +
    • AWS > Turbot > Logging > Bucket > Name > Prefix
      • +
    • AWS > Turbot > Logging > Bucket > Regions
      • +
    • AWS > Turbot > Logging > Bucket > Tags
      • +
    • AWS > Turbot > Logging > Bucket > Versioning
      • +
    +
    + +### User-Defined Stacks + +User-defined stacks are custom Guardrails stacks built entirely from user-defined +Terraform source. With user-defined stacks, you can describe your configuration +using standard Terraform syntax, and let Guardrails manage applying the +configuration, re-applying the configuration in response to changes on the +resources or policies, and automatically configuring new resources as they are +added. + +#### Stack Polices + +Stack behavior is controlled by the `Stack` policy and sub-policies. + +| Policy | Description | +| ---------------------------- | ----------------------------------------------------------------------- | +| **Stack** | Determine whether to run the stack in check mode, enforce mode, or skip | +| **Stack > Source** | The Terraform configuration source code that should be applied | +| **Stack > Variables** | `.tfvar`-style variable overrides | +| **Stack > Secret Variables** | `.tfvar`-style variable overrides for sensitive variables | + +The `Stack` policy determines what action the control will take: + +| Value | Description | +| ----------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- | +| **Skip** | The control will not run | +| **Check: Configured** | A Terraform plan will be generated. If the planned configuration does not match the current configuration, the control will alarm. | +| **Enforce: Configured** | A Terraform plan will be generated. If the planned configuration does not match the current configuration, the control will apply the configuration. | + +The `Stack > Source` policy contains the Terraform configuration code that +should be applied. + +Note that the stack expects to continue to manage any resources that were +created in the stack - if you delete a resource from the Terraform configuration +in the `Source` policy, the stack control will destroy the resource. For +example, if you wish to destroy all the objects created by the stack, set the +`Source` policy to `{}`, and leave the `Stack` policy set to +`Enforce: Configured`. + +The `Stack > Variables` policy can contain variable definitions in Terraform +HCL, in the same way that they would use a +[.tfvars file](https://www.terraform.io/docs/configuration/variables.html#variable-definitions-tfvars-files). + +Like `Stack > Variables`, the `Stack > Secret Variables` policy can contain +variable definitions. This policy will be marked `secret` in Guardrails, and is +meant for parameters that are sensitive or confidential. + +The `Variables` and `Secret Variables` policies are merged into a single set of +variables that are passed as a `tfvars` file to Terraform by the stack control. + +The `Variables` and `Secret Variables` are not required, however separating the +variables from the configuration will simplify using stacks in Guardrails: + +- As a best practice, you should only enter an immediate value in the + `Stack > Source`. If calculated policies are required to get input data for + the stack, the `Stack > Variables` should use a calculated policies to get the + data and pass it in as Terraform variables. + + - This makes the source easily testable outside of Guardrails, as it is not a + calculated policy + - Rendering the input variables in nunjucks is much simpler than rendering the + whole Terraform source + +- Using map or object variables allows you to create a map policy in the + `Variables` with configuration information that can be used in all child + resource stacks. If a new item is added, the variables can be updated without + updating the terraform configuration. + + + +### User-Defined Stack Controls + +Guardrails typically provides custom stack policies at the +account/project/subscription for managing global resources: + +- `AWS > Account > Stack` +- `GCP > Project > Stack` +- `Azure > Subscription > Stack` + +Stacks also target a Region or Resources Group, allowing you to manage locally +scoped resources as well: + +- `AWS > Region > Stack` +- `GCP > Region > Stack` +- `Azure > Resource Group > Stack` + +Guardrails also provides service-level stacks for some services. This allows you to +organize and separate your stack configurations by the types of resources that +they manage. The services stacks target the region or resource group for +regional services, and the "global" region for global services (Route53, IAM, +etc). + +- `AWS > VPC > Stack` +- `AWS > SSM > Stack` + +#### Example - standard IAM service roles and users + +Many organizations rely on 3rd party software or SaaS products that requires IAM +users or roles to access their accounts. Performance monitoring tools are an +example -- typically, an IAM cross-account role has to be created in all AWS +accounts in the enterprise to allow the tool access. + +You can use Guardrails Stacks to simplify the creation and management of these +roles across all of your AWS Accounts. Using a Stack targeting AWS accounts, +simply define the configuration for the IAM role using Terraform. Guardrails will +create it in all your AWS accounts. If the vendor adds new features that require +additional access for the role, you can simply modify the `Stack > Source` +policy, and Guardrails will deploy the changes. If you add new AWS Accounts, Guardrails +automatically runs your stack, making it consistent and compliant with your +standards. + +1. Enter the Terraform configuration in the `AWS > Account > Stack > Source` + policy. For example: + +```hcl +resource "aws_iam_role" "monitoring_role" { + name = "my_monitoring_role" + + assume_role_policy = < Account > Stack` policy to `Enforce: Configured` + +Guardrails will apply the Terraform source, creating the custom role and policy, and +then assigning the policy to the role. + +### Configured Control + +Every resource in Guardrails can manage its own configuration in its own +**Configured** control. For resources that are configured by a stack, it is the +Configured control that keeps the resource configured per the stack source. +Resources that are not managed by a stack can define their own configuration in +their own `Configuration > Source`. + +
    +Every resource in Guardrails can manage its own configuration in its own Configured policy: +
      +
    • AWS > EC2 > Instance > Configured
      • +
    • AWS > VPC > Security Group > Configured
      • +
    • AWS > DynamoDB > Table > Configured
      • +
    +
    + +Resources that are not part of a stack can define their own Terraform +configuration using the standard `Configured` policies: + +| Policy | Description | +| ---------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **{resource} > Configured** | Determine how to configure this resource. Note that If the resource is managed by another stack, then the Skip/Check/Enforce values here are ignored and inherit from the stack that owns it | +| **{resource} > Configured > Source** | The Terraform source used to configure this resource | +| **{resource} > Configured > Precedence** | An ordered list of who is allowed to claim this resource. A stack cannot claim this resource if it is already claimed by another stack at a higher level of precedence. | + +The `Configured` policy determines the overall behavior of the control. Note +that resources that are part of a stack are controled by the corresponding +`Stack` policy, and the `Configured` policy setting will have no effect. + +| Value | Description | +| ---------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------- | +| **Skip (unless claimed by a stack)** | Do not manage this resource via the configured control (unless it is managed by another stack) | +| **Check: Per Configured > Source (unless claimed by a stack)** | Check the resource configuration against the `Source` policy, and alarm if it is not configured correctly (unless it is managed by another stack) | +| **Enforce: Per Configured > Source (unless claimed by a stack)** | Apply the configuration in the`Source` policy (unless it is managed by another stack) | + +The `Configured > Source` policy should specify the Terraform source used to +configure this resource. + +The `Configured > Precedence` policy allows you to define what stack may own +this resource. A resource can only be configured by a single stack (at a time), +and the [claim precedence](#resource-claiming) defines the rules for determining +who can configure the resource. + +### Resource Claiming + +Guardrails determines the Terraform resource state dynamically. This allows Guardrails +to manage existing resources via Terraform, even if they were not created by +Guardrails! While this is an extremely powerful capability, this may not always be +the desired behavior - sometimes you may NOT want to Guardrails to manage a resource +in a Terraform stack if it already exists. **Claim Precedence** allows you to +define whether a resource can be claimed by a stack, and the order of priority +for ownership. + +The `Precedence` policy defines an ordered list of who is allowed to claim a +resource. The list is ordered by precedence from highest to lowest. - A stack +cannot claim a resource if it is already claimed by another stack at a higher +level of precedence. If this occurs the stack that tries to claim it should +become invalid - The stack will not be able to create or delete resources - +Although the stack is invalid, the individual resources will be able to continue +to manage themselves using the stack source. + +- If the stack that attempts to claim the resource does not match any item in + the list, it cannot claim it. Note that this implies that an empty list means + the resource cannot be claimed by any stack. If this occurs the stack that + tries to claim it should become invalid. + +- The list is comprised of Guardrails control type references, as well as special + constants. + - The following constants are available: + - **current** - The current stack (usually the one that created it) + - **source** - The **Configured > Source** sub-policy + - The references will allow wildcards following standard bash globbing. + - Note that '\*' matches any character except '/'; you should use '\*\*' to + match recursively: + ``` + @turbot/turbot-iam#/control/types/** + @turbot/aws-vpc** + @turbot/** + ``` + - Using glob wildcards, it is possible that the current (owning) stack, and + the new stack attempting to claim the resource BOTH match the same rule. + When this occurs, the new stack will **_not_** be able to claim the resource + - Using this pessimistic claim model prevents fighting - If the new stack + was allowed to claim the resource, the next time the old stack ran, it + would **_also_** be able to claim it, and the two stacks would fight + infinitely. + - This means that `**` by itself is the same as `current` when a resource + has already been claimed -- `["**"]` is identical to `["current","**"]` + - The stack attempting to claim the resource will become invalid at this + point, providing a notification to the user of the conflict + - Example: Consider a precedence list as follows: + ``` + @turbot/** + @myCompany/** + current + source + ``` + - my resource is currently configured by: + `@turbot/aws-vpc#/control/types/my-stack` + - another stack, `@turbot/aws-ec2#/control/types/my-other-stack`, attempts + to claim this resource + - In this case, both items are matched by the first entry: `turbot/**`. + The current stack wins - `@turbot/aws-ec2#/control/types/my-other-stack` + **_cannot_** claim the resource + +#### Claim Precedence Examples + +- No one can claim me: + + ```yaml + [] #empty list + ``` + +- Anyone can claim me if I have never been claimed: + ```yaml + - ** + ``` +- I can be configured via Source, but not claimed via a stack + + ```yaml + - source + ``` + +- Guardrails wins, but custom stacks are allowed: + + ```yaml + - @turbot/** + - current + - source + - ** + ``` + +- Guardrails wins, but only if not already claimed: + + ```yaml + - current + - @turbot/** + - source + - ** + ``` + +- Can only be configured by Guardrails, or as a custom (non-configured resource): + + ```yaml + - @turbot/** + ``` + +- Internal controls > Guardrails > Custom: + ```yaml + - @mycompany/** + - @turbot/** + - current + - source + - ** + ``` diff --git a/docs/concepts/guardrails/data-protection.md.not-yet-implemented b/docs/concepts/guardrails/data-protection.md.not-yet-implemented new file mode 100644 index 00000000..6670964e --- /dev/null +++ b/docs/concepts/guardrails/data-protection.md.not-yet-implemented @@ -0,0 +1,127 @@ +--- +title: Data Protection Guardrails +sidebar_label: Data Protection +--- + +## Overview + +The aim of Data Protection is to mitigate or eliminate risk of data loss due to user error, corruption (both accidental and intentional) and system/media failure. + +The cloud enables us to store and process massive data sets with a plethora of tools and technologies. These capabilities have rendered traditional backup and recovery tools ineffective. As the size of data has increased, techniques such as snapshots become necessary to meet backup and (perhaps more importantly) restore SLAs. These data protection mechanisms are often cloud and service specific, making it a challenge for organizations to audit and enforce standards, best practices, and regulatory compliance. + +Guardrails helps organizations address data protection challenges with policies that can: +* Check & Enforce service-specific snapshot and backup settings, such as retention periods and backup windows +* Automate the process of scheduling backups and snapshots +* Provide a consistent, easy to use set of backup schedules and retentions, with built-in backoff rotations (daily/weekly/monthly/yearly etd) +* Provide default policies to assist teams in setting appropriate schedules and retentions +* Enforce **mandatory minimum** retention policies, while allowing teams to exceed those retentions. +* Automate offsite backup copies with technologies like cross-region snapshots +* Assist in meeting regulatory and compliance requirements + + +## General Guidelines + +Policies related to snapshots, backups, snapshot replication, etc will appear as **Data Protection** under the resource to which the policies apply + +Data Protection policies use names consistent with those of the underlying service . For example: +* DynamoDB uses the term "Backup", thus the policies should be: `AWS > DynamoDB > Table > Data Protection > Managed Backups` +* Redshift uses the term "Snapshot", thus the policies should be: `AWS > Redshift > Cluster > Data Protection > Manage Snapshots` +* RDS Uses multiple terms: +* RDS uses "Backup" to refer to the daily automated snapshots that can be used for point-in-time restore. Such policies would reside under: `AWS > RDS > DB Instance > Data Protection > Backup` +* RDS uses "Snapshot" to refer to manual snapshots. Policies where Guardrails would manage these should reside under: `AWS > RDS > DB Instance > Data Protection > Managed Snapshots` + + +## Guardrails Managed Backups/Snapshots +Guardrails has many policies to assist in the configuration of backups, snapshots, and other options that are built in to cloud services. Many times, however, these options are insufficient to meet an organizations data protection requirements. Guardrails has its own capability to automate scheduling and retention of backups/snapshots for many cloud resources. We typically use the term **Managed** to refer to these entities. + +
    +
      +
    • AWS > DynamoDB > Table > Data Protection > Managed Backups
      • +
    • GCP > Compute > Disk > Data Protection > Managed Snapshots
      • +
    +
    + +Backup schedules and retentions for Guardrails-managed backups/snapshots are combined in a single policy called **Schedule**. These schedules will include implicit backoffs (Grandfather/father/son models). + +In addition to the configurable backup schedule, there is a separately configurable schedule to set a **minimum** backup and retention level. This policy will be called **Minimum Schedule**, and will have similar values to the **Schedule** policy. This allows an organization to set a minimum level of data protection, while giving the individual teams the ability to exceed these minimum to meet their needs. + +The effective schedule will be the merger of the **Schedule** and **Minimum Schedule** policies. This effective schedule will + * Use the more frequent schedule from the two policies. If one is hourly, and the other is daily, the hourly schedule should be used. + * Use the longer retention value at each level. If one policy specifies 4 weekly and the other 8, use 8. + +
    +
      +
    • AWS > EBS > Disk > Data Protection > Managed Snapshots
      • +
    • AWS > EBS > Disk > Data Protection > Managed Snapshots > Schedule
      • +
    • AWS > EBS > Disk > Data Protection > Managed Snapshots > Minimum Schedule
      • +
    +
    + +In addition, Guardrails provides default schedules to allow an organization to set schedules and minimum schedules across multiple services. These policies are: +- `{provider} > Data Protection > Default Schedule` +- `{provider} > Data Protection > Default Minimum Schedule` + + + +## Schedules and Retention +Many Data Protection policies specify a backup and retention schedule. To simplify configuration, Guardrails provides a consistent list of possible schedules: + +| Name | Hours | Hours12 | Days | Weeks | Months | Quarters | Years | +|------| ------|------|------|------|------|------|------| +| Daily for 3 days | - | - | 3 | - | - | - | - | +| Daily for 7 days | - | - | 7 | - | - | - | - | +| Daily for 14 days | - | - | 14 | - | - | - | - | +| Daily for 30 days | - | - | 30 | - | - | - | - | +| Daily for 90 days | - | - | 90 | - | - | - | - | +| Daily for 365 days | - | - | 365 | - | - | - | - | +| Daily with backoff to 3 months | - | - | 14 | 8 | 3 | - | - | +| Daily with backoff to 1 year | - | - | 30 | 12 | 12 | - | 1 | +| Daily with backoff to 3 years | - | - | 30 | 12 | 12 | 8 | 3 | +| Daily with backoff | - | - | 30 | 12 | 12 | 8 | 999| +| Hourly with backoff to 7 days | 24 | 6 | 7 | - | - | - | - | +| Hourly with backoff to 14 days | 72 | 14 | 14 | - | - | - | - | +| Hourly with backoff to 1 month | 72 | 14 | 14 | 4 | 1 | - | - | +| Hourly with backoff to 3 months | 72 | 14 | 14 | 4 | 3 | - | - | +| Hourly with backoff to 1 year | 72 | 14 | 30 | 12 | 12 | - | 1 | +| Hourly with backoff to 3 years | 72 | 14 | 30 | 12 | 12 | 8 | 3 | +| Hourly with backoff | 72 | 14 | 30 | 12 | 12 | 8 | 999| + +### Assumptions +* The scheduler uses the timezone of the region in which the resource resides. +* Hourlies are taken anywhere in the hour +* The "Hour12" is the last hourly before noon, and the last hourly of the day +* The "Daily" is the last one of the day +* The "Monthly" is the Daily on the last day of the month +* The "Quarter" is the Daily on the last day of the quarter +* The "Yearly" is the Daily on the last day of the year + + +## Guardrails Managed Remote Copies + +For some resources, Guardrails also has capabilities to automate copying snapshots to another region and/or account, and to manage the scheduling and retention of these backups/snapshots for cloud resources. We use the term **Copies** to refer to these entities. + + **Copies** will exist as sub-policies under the snapshot types to which they apply. + +
    +
      +
    • AWS > RDS > DB Instance > Data Protection > Managed Snapshots > Copies
      • +
    • AWS > RDS > DB Instance > Data Protection > Backup > Copies
      • +
    +
    + +Snapshots will be copied after they are created in the primary region. +Snapshots will have their own retention policies, separate from those if the originating snapshot. These policies will use the same **Schedule** and **Minimum Schedule** format as the **Managed Snapshots**. + +Remote snapshot copies require a region be specified. This should be included in a sub-policy called **Region**. + +Most remote snapshot copies require a KMS key be specified it copying an encrypted snapshot. This should be included in a sub-policy called **Encryption Key**. An empty string will mean no encryption. + + +
    +
      +
    • AWS > RDS > DB Instance > Data Protection > Managed Snapshots > Copies > Schedule
      • +
    • AWS > RDS > DB Instance > Data Protection > Managed Snapshots > Copies > Minimum Schedule
      • +
    • AWS > RDS > DB Instance > Data Protection > Managed Snapshots > Copies > Region
      • +
    • AWS > RDS > DB Instance > Data Protection > Managed Snapshots > Copies > Encryption Key
      • +
    +
    diff --git a/docs/concepts/guardrails/discovery.md b/docs/concepts/guardrails/discovery.md new file mode 100644 index 00000000..0176e7ea --- /dev/null +++ b/docs/concepts/guardrails/discovery.md @@ -0,0 +1,39 @@ +--- +title: Discovery Guardrails +sidebar_label: Discovery +--- + +# Discovery Guardrails + +## Overview + +The `Discovery` control is tasked with identifying instances for a particular +resource. If there are any resources that are not captured in the CMDB as part +of the events that AWS triggers, Guardrails will capture them through the Discovery +controls. + +A Discovery control is run on the parent resource (e.g. an AWS Region) to +periodically search for new target resources (e.g. S3 Buckets) and save them to +the Guardrails CMDB. + +Once discovered, the resource is then responsible for tracking changes to itself +through the CMDB control. + +
    The Resource Type AWS > SQS > Queue defines a +Control AWS > SQS > Queue > Discovery with a target Resource Type of AWS > Region. +
    + +### Policies to control Discovery + +Discovery controls are enforced or skipped based on the associated CMDB policy. + +
    The AWS > S3 > Bucket > Discovery control relies on the value of the AWS > S3 > Bucket > CMDB policy for its configuration. AWS > S3 > Bucket > CMDB may be set to `Skip` or `Enforce: Enabled` +
    + +Discovery controls also use the `Region` policy associated with the resource. If +region is not in `Regions` policy, the CMDB control should delete the resource +from the CMDB (since we don’t want to capture any resources in that region, we +should also cleanup). + +
    The AWS > S3 > Bucket > Discovery control will search for S3 buckets in a the regions specified in AWS > S3 > Bucket > Regions, and will add any buckets it finds to the CMDB as AWS > S3 > Bucket resources. +
    diff --git a/docs/concepts/guardrails/encryption-at-rest.md b/docs/concepts/guardrails/encryption-at-rest.md new file mode 100644 index 00000000..3c939194 --- /dev/null +++ b/docs/concepts/guardrails/encryption-at-rest.md @@ -0,0 +1,131 @@ +--- +title: Encryption at Rest Guardrails +sidebar_label: Encryption at Rest +--- + + +# Encryption at Rest Guardrails + +## Overview + +Most corporations already have standards around data encryption. These vary from +detailed rules that classify data by sensitivity and provide encryption +requirements for each, to more general guidelines like "encrypt everything!". +Guardrails provides a simple yet flexible platform for the implementation and +auditing of these standards, whatever they may be. + +**Encryption at Rest** refers specifically to the encryption of data when +written to an underlying storage system. All the major cloud vendors provide +options for encryption of the data that they store on your behalf. Often, the +details vary by service; within a given cloud provider, the encryption options +may be different for their object storage, relational databases, no-sql +databases, file servers, etc. While the details may differ, the type of options +are generally the same: + +- Encryption Level: is it enabled? Is it the correct algorithm/type? +- Key Management: what key should be used? + +Guardrails generally solves these with 2 policies: + +- `Encryption at Rest`: This policy allows you check or enforce the minimum or + actual level of encryption required for the service. The option values are + ordered from least secure to most secure. Note that in these policies, Guardrails + considers a customer managed key more secure than a default key managed by the + vendor. +- `Encryption At Rest > Customer Managed Key`: This allows you to specify the + key to be used for encryption (assuming you have set the "Encryption at Rest") + policy to use a customer managed key. + +For services that support changing the encryption level and/or key, Guardrails can +enforce your standard and change the encryption on the fly. These policies can +be found directly under the service in the hierarchy: + +- `{Provider} > {Service} > {Resource} > Encryption at Rest` +- `{Provider} > {Service} > {Resource} > Encryption at Rest > Customer Managed Key` + +
    +
      +
    • AWS > S3 > Bucket > Encryption at Rest
      • +
    • AWS > S3 > Bucket > Encryption at Rest > Customer Managed Key
      • +
    • GCP > Storage > Bucket > Encryption at Rest
      • +
    • GCP > Storage > Bucket > Encryption at Rest > Customer Managed Key
      • +
    +
    + +Some services only allow you to set the encryption options when the resource is +created. While you may not be able to change the encryption level on the fly in +this case, you may want to take some other action such as stopping, detaching, +or deleting the resource. Guardrails provides these capabilities in the "Approved" +policies: + +- `{Provider} > {Service} > {Resource} > Approved > Encryption at Rest` +- `{Provider} > {Service} > {Resource} > Approved > Encryption at Rest > Customer Managed Key` + +
    +
      +
    • AWS > EC2 > Volume > Approved > Encryption at Rest
      • +
    • AWS > EC2 > Volume > Approved > Encryption at Rest > Customer Managed Key
      • +
    • GCP > BigQuery > Table > Approved > Encryption at Rest
      • +
    • GCP > BigQuery > Table > Approved > Encryption at Rest > Customer Managed Key
      • +
    +
    + +## General Guidelines + +Most Encryption At Rest policies have options for using a custom key. This will +be defined in a sub policy `Encryption At Rest > Customer Managed Key` + +### Values + +Encryption at Rest value names are consistent where possible, though all of the +implementations support different values: + +- The term `{provider) Managed Key` refers to encryption using default keys + (Microsoft managed keys, AWS managed keys) +- The term `Customer Managed Key` refers to non-default keys (customer keys in + KMS or KeyVault) +- When using an policy specifies “or higher”, the values list will appear in + order from least secure to most secure + +Note that policies may not contain all of these possible values depending on the +implementation, and there may be other values specific to a service/resource . +Most `Check` policies have a matching `Enforce` policy. A notable exception is +that we don't use `Enforce: None or higher` as it would never take an action. + +| Value | Description | +| ---------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `Skip` | Skip | +| `Check: None` | Check that encryption is NOT enabled | +| `Check: None or higher` | will always pass, but notes that we have explicitly checked it, not just skipped | +| `Check: {Provider} managed key` | Check that encryption is enabled and set to use the providers default key (Microsoft key, aws/ebs service key, etc) | +| `Check: {Provider} managed key or higher` | Check that encryption is enabled with either a default key or a custom key (which Guardrails considers more secure) | +| `Check: Customer managed key` | Check that encryption is enabled using **any** customer managed key (A custom KMS/KeyVault key, not a Microsoft/AWS/google default key) | +| `Check: Encryption at Rest > Customer Managed Key` | Check that encryption is enabled using the customer managed key that is defined in the sub-policy for this resource | +| `Enforce: None` | Disable encryption at rest | +| `Enforce: {Provider} managed key` | **Always** set the the encryption to the provider managed key. | +| `Enforce: {Provider} managed key or higher` | Set the the encryption to the provider managed key unless it is already set using a customer managed key, which Guardrails considers a higher encryption level | +| `Enforce: Customer managed key` | Check that encryption is enabled using **ANY** customer managed key. If not, then set it using the key defined in the sub-policy for this resource. | +| `Enforce: Encryption at Rest > Customer Managed Key` | Set the encryption to use the key defined in the sub-policy for this resource, regardless of the current setting. | + +
    + 
    +    # AWS > S3 > Bucket > Encryption at Rest
+    - Skip
+    - "Check: None"
+    - "Check: None or higher"
+    - "Check: AWS SSE"
+    - "Check: AWS SSE or higher"
+    - "Check: AWS managed key"
+    - "Check: AWS managed key or higher"
+    - "Check: Customer managed key"
+    - "Check: Encryption at Rest > Customer Managed Key"
+    - "Enforce: None"
+    - "Enforce: None or higher"
+    - "Enforce: AWS SSE"
+    - "Enforce: AWS SSE or higher"
+    - "Enforce: AWS managed key"
+    - "Enforce: AWS managed key or higher"
+    - "Enforce: Customer managed key"
+    - "Enforce: Encryption at Rest > Customer Managed Key"
+
    +
    diff --git a/docs/concepts/guardrails/encryption-in-transit.md b/docs/concepts/guardrails/encryption-in-transit.md new file mode 100644 index 00000000..5731e538 --- /dev/null +++ b/docs/concepts/guardrails/encryption-in-transit.md @@ -0,0 +1,77 @@ +--- +title: Encryption in Transit Guardrails +sidebar_label: Encryption in Transit +--- + +# Encryption in Transit Guardrails + +## Overview + +Most corporations already have standards around data encryption. These vary from +detailed rules that classify data by sensitivity and provide encryption +requirements for each, to more general guidelines like "encrypt everything!". +Guardrails provides a simple yet flexible platform for the implementation and +auditing of these standards, whatever they may be. + +**Encryption in Transit** refers specifically to the encryption of data while +data moves between your site and the cloud provider or between two services. +This protection is achieved by encrypting the data before transmission; +authenticating the endpoints; and decrypting and verifying the data on arrival. +All the major cloud vendors provide options for encryption of the data that they +transfer on your behalf. + +Guardrails generally solves these with below policy: + +- `Encryption in Transit`: This policy allows you check or enforce the minimum + or actual level of encryption required for the resource. + +For service resources that support the encryption, Guardrails can enforce your +organization standard and change the encryption on the fly. These policies can +be found directly under the service in the hierarchy: + +- `{Provider} > {Service} > {Resource} > Encryption in Transit` + +
    +
      +
    • AWS > S3 > Bucket > Encryption in Transit
      • +
    • AWS > Redshift > Cluster > Encryption in Transit
      • +
    • Azure > Storage > Storage Account > Encryption in Transit
      • +
    • Azure > PostgreSQL > Server > Encryption in Transit
      • +
    +
    + +The values for this policy are consistent across all resource types. The basic +form is: + +``` + Skip + Check: Disabled + Check: Enabled + Enforce: Disabled + Enforce: Enabled +``` + +### Policy Values + +Note that policies may not contain all of these possible values depending on the +implementation, and there may be other values specific to a service/resource. +Most `Check` policies have a matching `Enforce` policy. + +| Value | Description | +| ------------------- | --------------------------------------------------------------------------------------- | +| `Skip` | Skip | +| `Check: Disabled` | Check that encryption is NOT enabled | +| `Check: Enabled` | Check that encryption is enabled | +| `Enforce: Disabled` | Check that encryption is disabled. If not, then set it using the right parameter/policy | +| `Enforce: Enabled` | Check that encryption is enabled. If not, then set it using the right parameter/policy | + +
    + 
    +    # AWS > S3 > Bucket > Encryption in Transit
+    - Skip
+    - Check: Disabled
+    - Check: Enabled
+    - Enforce: Disabled
+    - Enforce: Enabled
+
    +
    diff --git a/docs/concepts/guardrails/index.md b/docs/concepts/guardrails/index.md new file mode 100644 index 00000000..d9254258 --- /dev/null +++ b/docs/concepts/guardrails/index.md @@ -0,0 +1,31 @@ +--- +title: Guardrails +sidebar_label: Guardrails +--- + +# Guardrails + +Turbot Guardrails [Policies](concepts/policies) and [Controls](concepts/controls) provide a +flexible framework for auditing and enforcing configuration across hundreds of +cloud services, networking, OS, and DB tiers. While this model is extensible, +there are many guardrails that are common and consistent across resources. + +| Guardrail | Description | +| ------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| [Access Logging](concepts/guardrails/access-logging) | Monitor and enable access logging on various cloud resources. | +| [Active](concepts/guardrails/active) | Use a variety of criteria to determine if a cloud resource is Active, i.e. number of days the resource has existed, and take action (shutdown, delete, alarm, etc). | +| [Approved](concepts/guardrails/approved) | Verify whether a particular resource is allowed to exist and take an appropriate action if not (shutdown, delete, alarm, etc). | +| [Audit Logging](concepts/guardrails/audit-logging) | Audit Logging configuration tools for cloud resources. | +| [Budget](concepts/guardrails/budget) | A mechanism for tracking current spend against a planned target and taking appropriate action to control cost. | +| [CMDB](concepts/guardrails/cmdb) | Responsible for populating and updating all the attributes for that resource type in the Guardrails CMDB. | +| [Discovery](concepts/guardrails/discovery) | Mechanism by which Guardrails initially adds a resource to the CMDB. | +| [Encryption at Rest](concepts/guardrails/encryption-at-rest) | A mechanism to manage data encryption at rest (i.e. AWS S3 Buckets). | +| [Encryption in Transit](concepts/guardrails/encryption-in-transit) | A mechanism to manage data encryption in transit (i.e. AWS S3 Buckets). | +| [Public Access](concepts/guardrails/public-access) | Configure public access settings on cloud resources. | +| [Scheduling](concepts/guardrails/scheduling) | Define schedules to control cloud resource usage. | +| [Stacks/ Configured](concepts/guardrails/configured) | Manage resource configuration using Terraform. | +| [Tagging](concepts/guardrails/tagging) | Tagging of both Guardrails resources, such as a folder, and Cloud Provider resources, such as an Azure Subscription or AWS EC2 instance. | +| [Trusted Access](concepts/guardrails/trusted-access) | Trusted Access allow you to define whom and what you trust and enforce those limitations on your cloud resources. | +| [Usage](concepts/guardrails/usage) | Generate alarms if the number of resources in a specific service exceeds a set amount. | + +![Standard Controls](/images/docs/guardrails/standard_controls.png) diff --git a/docs/concepts/guardrails/public-access.md b/docs/concepts/guardrails/public-access.md new file mode 100644 index 00000000..c019ccc5 --- /dev/null +++ b/docs/concepts/guardrails/public-access.md @@ -0,0 +1,103 @@ +--- +title: Public Access Guardrails +sidebar_label: Public Access +--- + +# Public Access Guardrails + +## Overview + +As the number of cloud resources in environments expands, it becomes +increasingly difficult to ensure a tight network perimeter. Public +Access Guardrails monitor cloud resources for possible misconfigurations, such +as exposed RDS instances or S3 buckets. Not only can the guardrail generate an +alarm for immediate action, it can _take_ the action itself (in the RDS example, +sets the attribute `PubliclyAccessible` on an RDS instance to `False`.) + +To Guardrails, a resource is public if it shared in such a way that anyone can +access it - it is not restricted to a discrete list of entities, or from a +limited network boundary. Additionally, many cloud resources, such as the RDS +instance, have an attribute that can be toggled to allow or block public access. + +The core Public Access policy has a consistent form: +`{Provider} > {service} > {resource} > Publicly Accessible` + +
    +
      +
    • AWS > Redshift > Cluster > Publicly Accessible
      • +
    • AWS > RDS > DB Instance > Publicly Accessible
      • +
    +
    + +The basic form of the above policies is as follows: + +``` +Skip +Check: {resource} is not publicly accessible +Enforce: {resource} is not publicly accessible +``` + +
    +
    +    # AWS > Redshift > Cluster > Cluster Publicly Accessible
+    - Skip
+    - Check: Cluster is not publicly accessible
+    - Enforce: Cluster is not publicly accessible
+
    +
    + +### Example: Enforce all RDS instances to be not publicly accessible + +RDS instances have a option Publicly Accessible attribute that can be set to +`Publicly Accessible` at any time. In this example, we want to ensure that no +RDS instance is set to `Publicly Accessible`, and if it is, change the value +from `Publicly Accessible` to `Not Publicly Accessible`. + +Set the following policy at a level where RDS instances have the setting, either +at a high level so that instances inherit the policy definition or at the RDS +instance level itself: + +- **AWS > RDS > DB Instance > Publicly Accessible** set to + `Enforce: DB Instance is not publicly accessible`. + +When Guardrails discovers a RDS instance, the `PubliclyAccessible` will be checked. +If that attribute is set to `True`, Guardrails will modify the value to `False` with +no human action required! + +### S3 Public Access Block + +S3 accounts and buckets have +[`Public Access Block` settings](https://docs.aws.amazon.com/AmazonS3/latest/userguide/access-control-block-public-access.html) +that Guardrails can check for misconfigurations. Administrators can choose to change +the configurations to that which is approved, or simply alarm. In this example, +all public access settings are configured to true. + +#### Account Settings + +Set the policy `AWS > S3 > Account > Public Access Block` to +`Check: Per 'Public Access Block > Settings'` + +Set the policy `AWS > S3 > Account > Public Access Block > Settings` to the +following: + +```yaml +- "Block Public ACLs" +- "Block Public Bucket Policies" +- "Ignore Public ACLs" +- "Restrict Public Bucket Policies" +``` + +#### Bucket Settings + +Set the policy `AWS > S3 > Bucket > Public Access Block` to +`Check: Per 'Public Access Block > Settings'` + +Set the policy `AWS > S3 > Bucket > Public Access Block > Settings` to the +following: + +```yaml +- "Block Public ACLs" +- "Block Public Bucket Policies" +- "Ignore Public ACLs" +- "Restrict Public Bucket Policies" +``` diff --git a/docs/concepts/guardrails/scheduling.md b/docs/concepts/guardrails/scheduling.md new file mode 100644 index 00000000..12246ed6 --- /dev/null +++ b/docs/concepts/guardrails/scheduling.md @@ -0,0 +1,208 @@ +--- +title: Scheduling in Guardrails +sidebar_label: Schedule +--- + +# Scheduling in Guardrails + +**Scheduling** allow Organizations to control costs. Guardrails provides a simple +and flexible mechanism for starting and stopping cloud resources on a +pre-defined schedule. Using Guardrails `Schedule` and `Schedule Tag` policies, users +and administrators can define schedules to control cloud resource usage. + +## Setting a Schedule + +Guardrails generally solves these with 2 policies: + +- `Schedule`: This policy allows to select a start/stop schedule from a + pre-defined list of schedules. +- `Schedule Tag`: This allows to specify a custom schedule using the + `turbot_custom_schedule` tag on the resource. + +Both policies are set to `Skip` by default. When both the policies are set to +`Enforce`: + +- The policy specified in the `Schedule tag` will be in effect if the + `turbot_custom_schedule` tag exists. +- The policy specified in the `Schedule` will be in effect if the resource does + not have a `turbot_custom_schedule` tag. + +These policies can be found directly under the supported services in the +hierarchy: + +- `{Provider} > {Service} > {Resource} > Schedule` +- `{Provider} > {Service} > {Resource} > Schedule Tag` + +
    +
      +
    • AWS > EC2 > Instance > Schedule
      • +
    • AWS > EC2 > Instance > Schedule Tag
      • +
    +
    + +The values available for `Schedule` policy provides a simple mechanism that +meets most common cases. + +
    +
    +    # AWS > EC2 > Instance > Schedule
+    - Skip
+    - Enforce: Enforce: Business hours (8:00am - 6:00pm on weekdays)
+    - Enforce: Extended business hours (7:00am - 11:00pm on weekdays)
+    - Enforce: Stop for night (stop at 10:00pm every day)
+    - Enforce: Stop for weekend (stop at 10:00pm on Friday)
+
    +
    + +### Schedules Description: + +| Name | Value | Description | +| --------------------- | ----------------------------------------------------------------- | -------------------------------------------------------------------------------------------- | +| skip | `Skip` | No scheduling enforced. | +| businessHours | `Enforce: Business hours (8:00am - 6:00pm on weekdays)` | Guardrails will start instances at 8:00 AM and stop them at 6:00 PM from Mon-Fri. | +| extendedBusinessHours | `Enforce: Extended business hours (7:00am - 11:00pm on weekdays)` | Guardrails will start instances at 7:00 AM and stop them at 11:00 PM from Mon-Fri. | +| stopForNight | `Enforce: Stop for night (stop at 10:00pm every day)` | Guardrails will stop instances every night at 10:00 PM and will not power on them back. | +| stopForWeekend | `Enforce: Stop for weekend (stop at 10:00pm on Friday)` | Guardrails will stop instances at 10:00 PM on Friday night, and will not power on them back. | + +## Time Zones + +Guardrails will use the resource region to determine the time to start or stop as +per the schedule. + +Consider if the schedule for all EC2 instances in an account is set from 8:00 AM +to 6:00 PM and there are instances in `us-east-1` and `us-west-1`, the instances +will not be started together at 8:00 AM ET. The instances in `us-east-1` will be +started at 8:00 AM ET but the instances in `us-west-1` will start at 8:00 AM PT. + +## Starting and Stopping the Instance + +Guardrails will automatically start and stop instances according to the schedule +set. + +Consider if the instance is scheduled to run from 8:00 AM to 6:00 PM, and the +user manually stops the instance at 4:00 PM, Guardrails will not start the instance +again. This allows users to easily manage the starting and stopping of instances +outside the schedule. + +If the start and stop expression is invalid, Guardrails will not take any actions +against the instance. + +## Scheduling with a Tag + +The tagging mechanism is native to the cloud provider to specify a custom +schedule. When the `Schedule Tag` policy is set to +`Enforce: Schedule per turbot_custom_schedule tag`, Guardrails will attempt to use +the tag's value for setting the schedule. A tag with the exact key name as +`turbot_custom_schedule` and value with correct expression should be set for the +instance. + +The `turbot_custom_schedule` tag may contain: + +- `Skip` to exempt the resource from the schedule. +- A named Schedule (i.e. `businessHours` or `business_hours`) +- A custom Schedule expression ( AWS and Azure only ) + +A blank tag value is considered as `invalid`. The control moves to `invalid` +state and no action is taken. + +## Custom Schedule Expressions + +A custom schedule expression is to start and/or stop expression included in one +line of YAML. Neither the start nor stop expressions are required - You can +schedule stopping but not starting or vice-versa. + +For each expression, either a +[5 Item CRON Expression](https://en.wikipedia.org/wiki/Cron#CRON_expression) or +[Later.js Text Expression](https://bunkat.github.io/later/parsers.html#text) can +be used. + +```yaml +# Start at 8:00 AM and stop at 4:00 PM on weekdays +CRON exp: {"start": "* 8 * * MON-FRI", "stop": "* 16 * * MON-FRI"} +Text exp: {"start": "at 8:00am every weekday", "stop": "at 4:00pm every weekday"} +# Start at 8:00 AM on weekdays +CRON exp: {"start": "* 8 * * MON-FRI"} +Text exp: {"start": "at 8:00am every weekday"} +# Stop at 5:00 P.M. on Monday, Wednesday, and Friday +CRON exp: {"stop": "* 17 * * MON,WED,FRI"} or +Text exp: {"stop": "at 5:00pm on Mon,Wed and Fri"} +``` + +CRON and Text expressions can be used together in the same tag: + +```yaml +# Start at 8:00 AM and stop at 4:00 PM on weekdays +{ "start": "at 8:00am every weekday", "stop": "* 16 * * MON-FRI" } +``` + +**Note**: + +- Custom schedule expressions via tagging is not supported in GCP due to limited + list of allowed characters (GCP only allows alphanumeric characters, hyphens, + and underscores). +- As a fail-safe in case of temporary Guardrails outage or queueing, the control + checks the current time against the start or stop time before it starts or + stops the instance. When the current time is more than 1 hour after the start + or stop time: + - The control will not take any action - it will not start or stop the + instance. + - The control will go to error state. +- Named schedule supports Guardrails defined standard lower camel case as well as + snake case required to support GCP tagging (labels do not support uppercase + characters) such as: + - `business_hours` or `businessHours` + - `extended_business_hours` or `extendedBusinessHours` + - `stop_for_night` or `stopForNight` + - `stop_for_weekend` or `stopForWeekend` + +### Example 1: AWS > EC2 > Instance > Schedule + +Assume that user has multiple EC2 instances in each region of an account. The +user needs to start all the instances at 8:00 AM and stop them at 6:00 PM on +weekdays. The following policies have been configured in Guardrails at the account +level: + +- **AWS > EC2 > Instance > Schedule** is set to + `Enforce: Business hours (8:00am - 6:00pm on weekdays)`. +- **AWS > EC2 > Instance > Schedule Tag** is set to `Skip`. + +Setting the above policies will ensure that all EC2 instances are started at +8:00 AM and stopped at 6:00 PM, (local time in each region) Monday through +Friday. + +### Example 2: AWS > EC2 > Instance > Schedule + +Assume that the user has an EC2 instance which needs to run 24\*7 and other +instances should start at 7:00 AM and stop at 11:00 PM on weekdays. The +following policies have been configured in Guardrails at the account level: + +- **AWS > EC2 > Instance > Schedule** is set to + `Enforce: Extended business hours (7:00am - 11:00pm on weekdays)`. +- **AWS > EC2 > Instance > Schedule Tag** is set to `Skip`. + +The following policy (exception) has been configured in Guardrails at the instance +level which needs to run 24\*7: + +- **AWS > EC2 > Instance > Schedule Tag** is set to + `Enforce: Schedule per turbot_custom_schedule tag`. + +The instance has a tag with the key as `turbot_custom_schedule` and a value as +`skip`. + +The above policy settings will ensure that the instance requiring 24\*7 uptime +remains up, while the other instances are running between 7:00 AM and 11:00 PM +(local time based on region) and stopped outside of that time window. + +### Example 3: GCP > Compute Engine > Instance > Schedule + +Assume that the user has multiple VM instances in each region of a project. All +the instances must be stopped at at 10:00 PM every day. To do this, the +following policies have been configured in Guardrails at the project level: + +- **GCP > Compute Engine > Instance > Schedule** is set to `Skip`. +- **GCP > Compute Engine > Instance > Schedule Tag** is set to +`Enforce: Schedule per turbot_custom_schedule tag`. + + +The following label is then applied to the instances that must be stopped: +`turbot_custom_schedule`: `stop_for_night` diff --git a/docs/concepts/guardrails/standard_controls.png b/docs/concepts/guardrails/standard_controls.png new file mode 100644 index 0000000000000000000000000000000000000000..ae77b08d77b8b5ecc161e05a5da488b0f516539a GIT binary patch literal 97390 zcmeGEWmuJ8^9BsVrb{}NMnJl|QyM|KMM)`X*lbcd1xYCpkOt{SQaTj`q`Nye?C08g z_kI7qyvKVyU!MOr4!B}nGqYySIp9x}vZD$M1SBkG3U%j!l)KZi|KoE+F(J`@kq(dap>}pNV zFrxjM@2%TsNu0+xiMo8bHBJ7%ehD}xD+$cfZN0oW7)k9P5#nvW%hizA1at3X5OufL z2hcE|S7cR~k9}<>BikhqUjFQ!)NEIZYf#q3iv?$x@YxeW|ulww>dId^i 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zz~EcLx1`mv+|?I3L+2KJZQ5>jZU4PB^?xJR&joH{JXE;L9* zE-(Ehze=a5T#9*f*;VadQ&w2L*)oMGz*(bf-Gx7|+(Kvnei|E^nZ9vS;X+M4QIFVf z-@93_J?`VS-+SZS6<`>pSKXSoc^A(d@X{lR-2w9t-z&2P_ps*lverU|8~;x|io-Ja;FBpyfx)eAVa}w$&2EjBD`G?bp7W`e%1M{Bb^H-;dvA+zbsX zwS_Z}wV%8GdjH-1_wsnp?AgBV&;9GSz&*PE->=lmf7^TYh4>k%{WjZz-_N_X+B^K; z)o;KMSNOd0xYI3b?^S;2H5#jKUf0bJzgiQ-z_q@(=zzr+&( Uy_{PCDj+|3y85}Sb4q9e00miBZU6uP literal 0 HcmV?d00001 diff --git a/docs/concepts/guardrails/tagging/dynamic-tags.md b/docs/concepts/guardrails/tagging/dynamic-tags.md new file mode 100644 index 00000000..188224f6 --- /dev/null +++ b/docs/concepts/guardrails/tagging/dynamic-tags.md @@ -0,0 +1,359 @@ +--- +title: Dynamic Tags +sidebar_label: Dynamic Tags +--- + +# Tag Resources with Dynamic Metadata + +Org control objectives often include the need to tag resources with metadata of +the resource or dynamic metadata from other sources, such as a +[Guardrails File](guides/files). This guide will go over three different scenarios: + +- Tag an S3 bucket with an attribute in the bucket metadata. +- Tag an S3 bucket with attributes stored in a Guardrails File. +- Tag an S3 bucket with attributes from a + [Guardrails Folder](concepts/resources/hierarchy#folders) + + + +## Initial Configuration + +For our initial configuration, let us assume we have an AWS S3 bucket called +`turbot-test-bucket`. + +Assume that we have also set the policy +[AWS > S3 > Bucket > Tags](/guardrails/docs/mods/aws/aws-s3/policy#aws--s3--bucket--tags) +to `Check: Tags are correct`. This means that Guardrails will only alarm and not +change any tags on the resource itself. + +Each example will be defining a calculated policy using +[AWS > S3 > Bucket > Tags > Template](tmod:@turbot/aws-s3#/policy/types/bucketTagsTemplate). + +## Tagging Resources with CMDB Metadata + +This example will use the following S3 bucket metadata: + +
    + S3 bucket metadata + +```yaml +AccelerateConfiguration: +Status: Suspended +Acl: +Grants: + - Grantee: + ID: 6eb349968d9164c06c9c28123456sdfoadjf09a9ee8f79cb36157431f5e9713f + Type: CanonicalUser + Permission: FULL_CONTROL +Owner: + ID: 6eb349968d9164c06c9c28123456sdfoadjf09a9ee8f79cb36157431f5e9713f +Cors: {} +CreationDate: '2020-07-20T17:07:32.000Z' +Encryption: +ServerSideEncryptionConfiguration: + Rules: + - ApplyServerSideEncryptionByDefault: + KMSMasterKeyID: alias/turbot/default + SSEAlgorithm: 'aws:kms' + BucketKeyEnabled: false +Lifecycle: +- Filter: + And: + Prefix: test + Tags: + - Key: test + Value: value + ID: new-rule + NoncurrentVersionTransitions: [] + Status: Enabled + Transitions: + - Days: 9999 + StorageClass: STANDARD_IA +LocationConstraint: us-east-2 +Logging: {} +Name: turbot-test-bucket +NotificationConfiguration: {} +Payer: BucketOwner +Policy: +Statement: + - Action: 's3:GetBucketAcl' + Effect: Allow + Principal: + Service: cloudtrail.amazonaws.com + Resource: 'arn:aws:s3:::turbot-test-bucket' + Sid: AWSCloudTrailAclCheck20150319 + - Action: 's3:PutObject' + Condition: + StringEquals: + 's3:x-amz-acl': bucket-owner-full-control + Effect: Allow + Principal: + Service: cloudtrail.amazonaws.com + Resource: 'arn:aws:s3:::turbot-test-bucket/AWSLogs/12345678012/*' + Sid: AWSCloudTrailWrite20150319 + - Action: 's3:*' + Effect: Allow + Principal: + Service: config.amazonaws.com + Resource: + - 'arn:aws:s3:::turbot-test-bucket' + - 'arn:aws:s3:::turbot-test-bucket/*' + Sid: ConfigRule + - Action: 's3:*' + Condition: + Bool: + 'aws:SecureTransport': 'false' + Effect: Deny + Principal: '*' + Resource: + - 'arn:aws:s3:::turbot-test-bucket' + - 'arn:aws:s3:::turbot-test-bucket/*' + Sid: MustBeEncryptedInTransit +Version: '2012-10-17' +PolicyStatus: +IsPublic: false +PublicAccessBlock: +BlockPublicAcls: false +BlockPublicPolicy: false +IgnorePublicAcls: false +RestrictPublicBuckets: false +Replication: {} +Tags: +- Key: Owners + Value: john Doe +- Key: Test + Value: '' +- Key: environment + Value: DEV +Versioning: +MFADelete: Disabled +Status: Suspended +Website: {} +``` + +
    + + + +In this example, we want to ensure that the payer is a tag on the bucket, i.e. +the key:value pair `payer`:`BucketOwner`. Let's start with the GraphQL query: + +```graphql +{ + resource { + payer: get(path: "Payer") + turbot { + tags + } + } +} +``` + +This gives us the following output: + +```json +{ + "resource": { + "region": "us-east-2", + "turbot": { + "tags": { + "Test": "", + "Owners": "john Doe", + "environment": "DEV" + } + } + } +} +``` + +Note that we can use this `get: path()` function to call a specific attribute. +This example uses `Payer` and we call the attribute `payer`. + +Finally, to implement the logic, we use this nunjucks template: + +```nunjucks +{%- if $.resource.turbot.tags['payer'] == $.resource.payer -%} +[] +{%- else -%} +- payer: '{{ $.resource.payer }}' +{%- endif -%} +``` + +The `AWS > S3 > Bucket > Tags` control will go into alarm if there does not +exist a tag `payer` with the value defined on the bucket metadata, and will +state that their should be that tag on the bucket. + +### Tagging Resources with Guardrails File Data + +A Guardrails File is simply a json data structure that can be referenced in +calculated policies. Let's assume the file has the following data: + +```json +{ + "dev": "john doe", + "prod": "greg duke", + "qa": "gen gomes" +} +``` + +The aka of this file is `owner_env`. It is also possible to use the Guardrails ID, +which is of the format `220880720738517`. + +We will be using the same calculated policy +([AWS > S3 > Bucket > Tags > Template](tmod:@turbot/aws-s3#/policy/types/bucketTagsTemplate)) +as in the first example. In the query we need to not only call the resource tags +but also the Guardrails file. + +```graphql +{ + resource { + turbot { + tags + } + } + tag_file: resource(id: "owner_env") { + data + } +} +``` + +In this scenario, tag the resource with the name of the owner of the particular +environment (each environment owner is defined in the File). As an +administrator, assume we know that there can only be three values for the key +`environment`: `qa`, `prod`, and `dev`. + +```nunjucks +{%- for key, value in $.resource.turbot.tags -%} + + +{%- if not $.resource.turbot.tags.environment -%} +- environment: "missing" +{%- elif $.resource.turbot.tags.environment == 'dev' -%} +- owner: {{ $.tag_file.data.dev }} +{%- elif $.resource.turbot.tags.environment == 'qa' -%} +- owner: {{ $.tag_file.data.qa }} +{%- elif $.resource.turbot.tags.environment == 'prod' -%} +- owner: {{ $.tag_file.data.prod }} +{%- else -%} +- environment: "invalid_value" +{%- endif -%} +``` + +As always, first check for the existence of the key. If the key does exist, +check it's value to see if it matches with any of the key terms, and if it does, +create the necessary new tag. Lastly, if the environment key does exist but it +is not qa, prod, or dev, output that the environment key has an invalid value. + +### Tagging Resources with Guardrails Folder Metadata + +This example will detail how to pull tagging information about a Guardrails folder +and apply that tag to all resources within it. The query response will include +the folder that is "closest to the resource" in the Guardrails hierarchy. For +example, if there existed folder A and folder B, with B inside of folder A, and +a resource was inside folder B, the hierarchy would show **A > B > Resource**, +and folder B is considered "closest." + +```graphql +{ + resource { + turbot { + tags + } + } + folder { + turbot { + tags + } + } +} +``` + +Assume the tag `environment`:`qa` exists on the folder and this must be applied +to all resources within it. This one is easy - we can just echo the folder tag +value to set it. + +```nunjucks +{%- if $.folder.turbot.tags.environment -%} +- environment: {{ $.folder.turbot.tags.environment }} +{%- else -%} +- environment: "folder missing tag" +{%- endif -%} +``` + +If the environment tag does not exist on the folder, simply output a static +value stating there is no tag. + +### Tagging Resources with User who Created Resource (and Creation Time) + +Guardrails can automate the tagging of resources with the user who created it and +the time at which it was created. Like these other examples, this will be a +calculated policy, but this time our query will be a bit different! + +Query: + +```graphql +{ + resource { + creator: notifications(filter: "sort: version_id limit:1") { + items { + actor { + identity { + turbot { + title + } + } + } + turbot { + createTimestamp + } + } + } + } +} +``` + +An example response might look as follows: + +```json +{ + "resource": { + "creator": { + "items": [ + { + "actor": { + "identity": { + "turbot": { + "title": "John Doe" + } + } + }, + "turbot": { + "createTimestamp": "2020-09-28T18:42:20.990Z" + } + } + ] + } + } +} +``` + +In the template, we simply reference the two objects then use the nunjucks +template to force everything lower case, as well as replacing unapproved +characters. + +Template: + +```nunjucks +{%- set owner = $.resource.creator.items[0].actor.identity.turbot.title -%} +created_by: "{{ owner | lower | replace(" ", "_") }}" + +{%- set create_time = $.resource.creator.items[0].turbot.createTimestamp %} +created_time: "{{ create_time | lower | replace(".", "_") | replace(":", "-") }}" +``` + +This policy can be applied to any resource. Be sure to test the GraphQL query to +ensure that it is responding with the correct info! Also notice that in the +second `set` variable line, we remove the trailing `-` to ensure that the +`created_time` key is a new line and parsable by the policy. diff --git a/docs/concepts/guardrails/tagging/index.md b/docs/concepts/guardrails/tagging/index.md new file mode 100644 index 00000000..c545661c --- /dev/null +++ b/docs/concepts/guardrails/tagging/index.md @@ -0,0 +1,197 @@ +--- +title: Tags in Guardrails +sidebar_label: Tags +--- + +# Tags in Guardrails + +Tags are a fundamental concept for many organizations. Identification of cloud +resources across many accounts is trivial, but only if tagging processes are in +place and understood by users. With Guardrails, we can enforce tags on various +resource types. This includes, but is not limited to, checking for the following +scenarios: + +- Ensuring all resources have at least one tag. +- Ensuring all tags are lower (or upper) case to allow for automation. +- Specific keys must exist. +- Specific keys AND values must exist. + +Guardrails can both check and remediate resources that do not have compliant tags. +Metadata about the resource stored in CMDB or information from a +[Guardrails File](guides/files) can be referenced when checking and applying tags. + +If you are not familiar with Calculated Policies, check out the +[Calculated Policies FAQ](concepts/policies/calculated-faq) as well as our +[7 minute lab](7-minute-labs/calc-policy). + +## Tagging Cloud Resources + +For any cloud resource that can be tagged, an associated policy in Guardrails exists +(note that tags are called "Labels" in Google Cloud): + +- `AWS > Service > Resource > Tags` +- `Azure > Service > Resource > Tags` +- `GCP > Service > Resource > Labels` + +For example, if an administrator wanted to enforce tags on an AWS EC2 instance, +the policy would become `AWS > EC2 > Instance > Tags`. This set of policies is +the driving mechanism to determine if tags should be checked for violations by +Guardrails, and if action should be taken when a resource is found to not have the +correct set of tags. + +## Tag Value Reserved Strings + +Guardrails uses tag values of `null` and `undefined` as indicators that a tag key +should be removed. If a user sets these reserved keywords as tag values, in some +cases this can result in unintentional tag key removal. For this to happen, the +following conditions must be met: + +- Tags policy is set to `Enforce`. +- The tag key most be specified in the Tags Template policy. +- The tag value set by the user is `null` or `undefined`. If the tag keys aren't + specified in the template, then Guardrails will ignore them. + +## Tagging Templates + +Tagging templates allow flexibility in assigning tags for various resources +across a wide number of accounts. A policy will check all resources within the +scope for the correct tags. If a tag exists but should not, it is removed. Tags +that do not exist but should will be added by Guardrails. + +A basic tagging template is a YAML list with static values. Consider the policy +`AWS > EC2 > Instance > Tags > Template`. In this example, instances are +required to have a `Cost Center`, `Environment`, and `Account Owner` tags. These +tags do not change throughout the account, and thus the policy can be set at the +folder level of which the AWS account is a child of (recommended) or on the AWS +account within Guardrails. + +```yaml +- Cost Center: "Security" +- Environment: "Dev" +- Account Owner: "John Doe" +``` + +If the policy `AWS > EC2 > Instance > Tags` is set to `Enforce: Set tags`, +Guardrails will take action on any EC2 instance without the required set of tags. + +## Add, Update or Remove Tags using Tagging Templates + +Adding, updating or removing tags can be done in a straightforward way. The tags +template asserts which tags that should or should not be set on the resource. +NOTE: If a resource has tags that are not described in the Tags Template, then +Guardrails will ignore those tags. Only tags defined in the template are processed. + +### Add + +To add a new tag, specify it in the template. If the tag already exists on the +resource, then Guardrails will update that tag to the specified value. + +```yaml +- SomeTag: ReallyImportantTagValueV1 +``` + +### Remove Tag + +To remove a tag, set the value to `null`. + +```yaml +- SomeTag: null +``` + +### Update Tag Value + +Updating a tag value on a resource is done by updating the tag value in the tags +template. The approach is the same as adding a new tag. + +```yaml +- SomeTag: ReallyImportantTagValueV2 +``` + +### Update Tag Key + +To change a tag key, one must destroy the old tag then create a new one. Use the +approach described in "Remove Tag" to proceed. + +```yaml +- SomeTag: null +- SomeNewTag: NewReallyImportantTagValue +``` + +## Dynamic Tagging + +Using the tagging template example above, it becomes trivial to enforce a set of +tags on a variety of resources. However, many organizations have more complex +tagging requirements, such as not only ensuring that AWS IAM users have an email +tag, but also validating that the tag is in fact an email. + +Continuing to use the above example, the +`AWS > EC2 > Instance > Tags > Template` in the new policy view has the option +to `Switch to calculated mode`. The policy window then changes to allow users to +write custom [Calculated Policies](guides/managing-policies). + +### Examples + +For all the examples, use the following query in the calculated policy, using +`AWS > EC2 > Instance > Tags > Template`: + +```grapqhql +{ + resource { + turbot { + tags + } + } +} +``` + +### Alarm if key does not exist + +If the key `cost_center` does not exist, output `cost_center`:`missing_tag`. +Else, simply output a blank array. Guardrails will alarm if the tag is not correct. + +Template: + +```nunjucks +{%- if 'cost_center' not in $.resource.turbot.tags -%} {# Check for the key cost_center #} +- cost_center: 'missing_tags' +{%- else -%} +[] +{%- endif -%} +``` + +### Alarm if key:value pair does not exist + +If the key:value pair `cost_center`:`Security` does not exist, output +`cost_center`:`Security`. Else, simply output a blank array. Guardrails will alarm +if the tag is not correct. + +Template: + +```nunjucks +{%- if 'costcenter' not in $.resource.turbot.tags-%} {# Check for the key cost_center #} +- cost_center: 'Security' +{%- elif 'Security' != $.resource.turbot.tags.costcenter -%} {# Check for the value of key cost_center #} +- cost_center: 'Security' +{%- else -%} +[] +{%- endif -%} +``` + +### Alarm if a Resource has no Tags + +A simple use case for Guardrails tagging controls is to check resources for the +existence of tags. + +Template: + +```nunjucks +{# Checks if there are any tags #} +{% if $.resource.turbot.tags | length == 0 -%} +"tag_compliance": "untagged_resource" {# temp placeholder to mark it untagged #} +{% else -%} +[] {# if there are tags, do nothing #} +{%- endif %} +``` + +If there are tags, the template policy returns a blank array (`[]`). If there +are no tags, the tagging control will alarm saying that a new tag must be added. diff --git a/docs/concepts/guardrails/tagging/require-keys.md b/docs/concepts/guardrails/tagging/require-keys.md new file mode 100644 index 00000000..a385dc1d --- /dev/null +++ b/docs/concepts/guardrails/tagging/require-keys.md @@ -0,0 +1,173 @@ +--- +title: Require Keys +sidebar_label: Require Keys +--- + +# Requiring Tag Keys with Guardrails Tagging Guardrails + +Requiring specific tags on cloud resources is a fundamental control objective +for many organizations. This guide will overview some basics when it comes to +verifying specific keys exist. The first scenario is requiring a key with any +value except `null`, and the second is requiring specific keys with specific +values. + +
    + This example, along with many others, can be found in the Guardrails Samples Repo +
    + +## Initial Configuration + +For our initial configuration, let us assume we have an AWS S3 bucket called +`turbot-test-bucket` with the following tags: + +| Key | Value | +| ----------- | -------- | +| Test | `null` | +| environment | DEV | +| owner | john Doe | + +Assume that we have also set the policy +[AWS > S3 > Bucket > Tags](/guardrails/docs/mods/aws/aws-s3/policy#aws--s3--bucket--tags) +to `Check: Tags are correct`. This means that Guardrails will only alarm and not +change any tags on the resource itself. + +## Tagging with Guardrails + +For both scenarios, we will be setting a calculated policy using +[AWS > S3 > Bucket > Tags > Template](/guardrails/docs/mods/aws/aws-s3/policy#aws--s3--bucket--tags--template). + +We will also use the same GraphQL query for both calculated policies: + +```graphql +{ + resource { + turbot { + tags + } + } +} +``` + +### Require Specific Keys with Any Value Except `null` + +This is a simple test as an empty string is functionally equivalent to `null`, +so we only need to test for the existence of a value. This can be accomplished +via the following Nunjucks template: + +```nunjucks +{%- if $.resource.turbot.tags['Test'] -%} +[] +{%- else -%} +- Test: not approved +{%- endif -%} +``` + +Note that this test is case sensitive! We can, however, reference our +[guide that ignores casing on tags](concepts/guardrails/tagging/tag-casing) and +adjust our template: + +```nunjucks +{%- set approved = 'no' -%} + +{%- for key,value in $.resource.turbot.tags -%} + {%- if r/test/.test(key | lower) -%} + {%- if $.resource.turbot.tags[key] %} + {%- set approved = 'yes' -%} + {%- endif %} + {%- endif -%} +{%- endfor -%} + +{%- if approved == 'no' -%} +- Test: not approved +{%- else -%} +[] +{%- endif -%} +``` + +Applying these template policies will check the S3 bucket for the tag `Test`, +with the bottom template ignoring casing, and the control will alarm if the tag +`Test` has a `null` value or the key `Test` does not exist. + +### Require Specific Keys with Specific Values + +This is very similar to the above example, and in fact we can reuse the +templates with a very slight modification. Let's assume we want to check for the +key: value pair `Test`:`example`. + +For the case sensitive scenario: + +```nunjucks +{%- if $.resource.turbot.tags['Test'] == 'example' -%} +[] +{%- else -%} +- Test: not approved +{%- endif -%} +``` + +To ignore casing in the key: + +```nunjucks +{%- set approved = 'no' -%} + +{%- for key,value in $.resource.turbot.tags -%} + {%- if r/test/.test(key | lower) -%} + {%- if $.resource.turbot.tags[key] == 'example' %} + {%- set approved = 'yes' -%} + {%- endif %} + {%- endif -%} +{%- endfor -%} + +{%- if approved == 'no' -%} +- Test: not approved +{%- else -%} +[] +{%- endif -%} +``` + +Further, we can ignore casing in the key _and_ value: + +```nunjucks +{%- set approved = 'no' -%} + +{%- for key,value in $.resource.turbot.tags -%} + {%- if r/test/.test(key | lower) -%} + {%- if r/example/.test(value | lower) %} + {%- set approved = 'yes' -%} + {%- endif %} + {%- endif -%} +{%- endfor -%} + +{%- if approved == 'no' -%} +- Test: not approved +{%- else -%} +[] +{%- endif -%} +``` + +### Require a Specific Selection of Values + +This example will allow an array of values that a key can be, and if the key +either does not exist or the value is not in the list, we will set the value to +be `Non-Compliant Tag`. This example is very similar to our +[Calculated Policy 7 minute lab](7-minute-labs/calc-policy). + +Our query will remain the same as in the other examples: + +```graphql +{ + resource { + turbot { + tags + } + } +} +``` + +For the sake of this example, we simply want to have the key `Environment` set +to `QA`, `Prod`, `Dev`, or `Temp`. If the existing value is none of those, set +the tag value to `Non-Compliant Tag`. Note how we can use logical expressions +within the quotes. This can be expanded upon to as many tags as required. + +```nunjucks +Environment: "{% if $.bucket.turbot.tags['Environment'] in ['Dev', 'QA', 'Prod', 'Temp'] %}{{ $.bucket.turbot.tags['Environment'] }}{% else %}Non-Compliant Tag{% endif %}" +``` diff --git a/docs/concepts/guardrails/tagging/tag-casing.md b/docs/concepts/guardrails/tagging/tag-casing.md new file mode 100644 index 00000000..cc52cf5c --- /dev/null +++ b/docs/concepts/guardrails/tagging/tag-casing.md @@ -0,0 +1,156 @@ +--- +title: Tag Casing +sidebar_label: Tag Casing +--- + +# Resource Tagging and Handling Key:Value Casing + +Upper and lower case characters can lead to false positives. With Guardrails, we can +use calculated policies to check for tags regardless of casing, reducing false +positives and allowing users and administrators to focus on real business +improvements. Additionally, a calculated policy can be written to automatically +fix values that should be either all lower or all upper case. Note that existing +keys CANNOT be changed (this is done to protect any existing tag). + +
    + This example, along with many others, can be found in the Guardrails Samples Repo +
    + +## Initial Configuration + +For our initial configuration, let us assume we have an AWS S3 bucket called +`turbot-test-bucket` with the following tags: + +| Key | Value | +| ----------- | -------- | +| Test | Tag | +| environment | DEV | +| owner | john Doe | + +Assume that we have also set the policy +[AWS > S3 > Bucket > Tags](/guardrails/docs/mods/aws/aws-s3/policy#aws--s3--bucket--tags) +to `Check: Tags are correct`. This means that Guardrails will only alarm and not +change any tags on the resource itself. + +## Tagging with Guardrails + +### Check Tags, Ignoring Casing + +Using Guardrails, we can define a policy +[AWS > S3 > Bucket > Tags > Template](/guardrails/docs/mods/aws/aws-s3/policy#aws--s3--bucket--tags--template) +with logic that is case agnostic. + +First, let's start with the GraphQL query. We want to just pull in the resource +tags: + +```graphql +{ + resource { + turbot { + tags + } + } +} +``` + +If our template looked like the following: + +```nunjucks +{%- if $.resource.turbot.tags['owner'] == 'john doe' -%} +[] +{%- else -%} +- 'owner': 'invalid_tag' +{%- endif -%} +``` + +Guardrails would evaluate the control `AWS > S3 > Bucket > Tags` to `Alarm` due to +the casing on the tag value `john Doe`. To get around this, we use +[RegEx](guides/nunjucks#regex) to evaluate the string. If we are confident in +the casing of the key, it is possible to do something simple like so: + +```nunjucks +{%- if r/john doe/.test($.resource.turbot.tags['owner'] | lower) -%} +[] +{%- else -%} +- 'owner': 'invalid_tag' +{%- endif -%} +``` + +However, real applications are usually not so trivial. To account for the casing +differences with the key AND value, we need to add some additional lines of +code: + +![](/images/docs/guardrails/calc-policy.png) + +```nunjucks +{%- set approved = 'no' -%} + +{%- for key,value in $.resource.turbot.tags -%} + {%- if r/owners/.test(key | lower) -%} + {%- if r/john doe/.test(value | lower) %} + {%- set approved = 'yes' -%} + {%- endif %} + {%- endif -%} +{%- endfor -%} + +{%- if approved == 'no' -%} +- owner: 'Missing_tag' +{%- else -%} +[] +{%- endif -%} +``` + +First, set a variable that is used to denote if the key: value pair exists. +Then, parse out the key and value pairs using a for loop, check for the key +first, and if the key exists, check for the value. If both the key and value if +statement evaluate to true, we set the dummy variable to `yes` and in the final +if statement, simply pass an empty array denoting the tags are approved. Because +our bucket has the key:value pair `Owners`:`john Doe`, it passes with flying +colors! + +### Check Tags, Change Casing + +Using Guardrails, we can define a policy +[AWS > S3 > Bucket > Tags > Template](/guardrails/docs/mods/aws/aws-s3/policy#aws--s3--bucket--tags--template) +with logic that is case agnostic. + +As above, let's start with the GraphQL query. We want to just pull in the +resource tags: + +```graphql +{ + resource { + turbot { + tags + } + } +} +``` + +We want to check to make sure the key `owner` exists, then change the value to +be all lower case. + +```nunjucks +{%- set regExp = r/owners/ -%} +{%- set set_key = 0 -%} + +{%- for key, value in $.resource.turbot.tags -%} +{%- set lower_value = (value | lower) -%} +{%- if regExp.test(key | lower) and lower_value != value -%} + - {{ key }}: {{ lower_value }} + {%- set set_key = 1 -%} +{%- endif -%} +{%- endfor -%} + +{%- if set_key == 0 -%} +[] +{%- endif -%} +``` + +In this template, set a variable that can be used as a boolean that changes +value only if the lower case tag change is necessary. If there is no change, we +want to be sure to output a blank array. We can utilize Regex to test the key to +ensure we are looking at the right one, then test the existing value with +another string that has had the `lower` function applied. If those strings don't +match, the result of the template is to change the current value with the lower +case value. diff --git a/docs/concepts/guardrails/tagging/tagging-helpers.md b/docs/concepts/guardrails/tagging/tagging-helpers.md new file mode 100644 index 00000000..1f2566f7 --- /dev/null +++ b/docs/concepts/guardrails/tagging/tagging-helpers.md @@ -0,0 +1,469 @@ +--- +title: Tagging Helpers +sidebar_label: Tagging Helpers +--- + +# Tagging Helpers + +To help with complex tagging use cases, Guardrails offers additional functionality to assist in writing calculated policies for tagging. Collectively, these improvements are known as "Tagging Helpers". + +## createdBy and createTimestamp + +A common tagging requirement is to tag a resource with the identity of the creator and the time it was created. Here is an example graphql query for the resource metadata (which includes the creation information). +```graphql +{ + resource { + metadata + } +} +``` +Query results: +```yaml +metadata: + aws: + accountId: 012345678912 + partition: aws + region: us-east-1 + createTimestamp: 2023-01-28T05:31:46.000Z + createdBy: "arn:aws:sts::013122550996:user/dwight" +``` + +### createdBy data source + +Guardrails populates the createdBy attribute based on the identity found in the creation event. For resources that exist prior to Guardrails discovering them, createdBy will be set to null. The format for the createdBy value varies by cloud provider: + +**AWS** +- userIdentity.arn: The full ARN of the identity that created the resource. + +**Azure** +- initiatedBy.userPrincipalName (Active Directory resources) +- caller (Azure resources) + +**GCP** +- authenticationInfo.principalEmail + +### Example of how to use createdBy and createTimestamp + +This example shows a generic `template_input` and `template` that will work for any AWS, Azure or GCP resource type. + +template_input: +```graphql +{ + resource { + metadata + turbot{ tags } + } +} +``` + +```nunjucks +{# As createdBy and createTimestamp can be null, it's important to test that they are available. -#} +{% if $.resource.metadata.createdBy %} +- "creator": "{{ $.resource.metadata.createdBy }}" +{% endif %} +{% if $.resource.metadata.createTimestamp %} +- "createTimestamp": "{{ $.resource.metadata.createTimestamp }}" +{% endif %} +``` + +## Tag Maps with setAttribute + +In more complex tagging scenarios, accumulating tag key:value pairs into a map can assist in writing clean readable code. Nunjucks does not natively supply a way to create mutable dictionaries. To overcome this limitation, the `setAttribute()` function can help. The function accepts a dictionary object and two string parameters. + +**Template** +```nunjucks +{% set currentTags = {"Key1":"Value1"} -%} +{% set currentTags = setAttribute(currentTags, "Key2", "ValueTwo") %} +{% set currentTags = setAttribute(currentTags, "Key1", "ValueOne") %} +{% for key,value in currentTags -%} +- "{{key}}": "{{value}}" +{% endfor -%} +``` + +**Output** +With output of: +```yaml +- "Key1": "ValueOne" +- "Key2": "ValueTwo" +``` + +Note: Appending to arrays is not supported by this function but can be accomplished in other ways. + +## Rectify and cleanup bad keys and values + +Fixing incorrect keys and values is the most common tagging use case. The `transformMap` function can be used in calculated policies to easily process rules across all tags on any given resource. + +### transformMap(tags_map, rules) -> transformed_map + +Transforms `tags_map` based on `rules` and returns `transformed_map`; the `tags_map` paramater and the `transformed_map` return value are simple arrays of `key:value` pairs e.g.: + +```json +{ + "foo": "bar", + "fizz": "buzz", + "crop": "beets" +} +``` +or +```yaml +- foo: bar, +- fizz: buzz, +- crop: beets +``` + +The `rules` object must conform to a specific schema which will be outlined in a series of examples. All examples will use the following starting `tags_map` (the current tags on the resource): + +```yaml +- Env: prd, +- CostCenter: scranton-1138, +- owner: dwight +``` + +### Example: Create remediated tags while preserving existing tags + +**Rules** +```yaml +environment: + incorrectKeys: + - Env +``` + +**Transformed Tags** +```yaml +- "CostCenter": "scranton-1138" +- "Env": "prd" +- "environment": "prd" +- "owner": "dwight" +``` + +### Example: Replace an incorrect tag key. + +**Rules** +```yaml +environment: + incorrectKeys: + - Env + replacementValue: undefined +cost_center: + incorrectKeys: + - CostCenter + replacementValue: undefined +``` + +_Reminder: "undefined" is a reserved value in Guardrails to indicate a tag that should be removed!_ + +**Transformed Tags** +```yaml +- "cost_center": "scranton-1138" +- "environment": "prd" +- "owner": "dwight" +``` + +### Example: Replace an incorrect tag value. + +**Rules** +```yaml +owner: + values: + dwight.schrute@dmi.com: + incorrectValues: + - dwight + - dks + - dwight.schrute + pam.beasly@dmi.com: + incorrectValues: + - Beasly + - pam +``` + +**Transformed Tags** +```yaml +- "CostCenter": "scranton-1138" +- "Env": "prd" +- "owner": "dwight.schrute@dmi.com" +``` + +### Example: Combine value and key replacement. + +**Rules** +```yaml +environment: + incorrectKeys: + - Env + replacementValue: undefined + values: + production: + incorrectValues: + - prod + - prd + - PROD + development: + incorrectValues: + - dev + - DEV +cost_center: + incorrectKeys: + - CostCenter + replacementValue: undefined + values: + SCR1138: + incorrectValues: + - scranton-1138 + NSH1234: + incorrectValues: + - nashua-1234 +owner: + values: + dwight.schrute@dmi.com: + incorrectValues: + - dwight + - dks + - dwight.schrute + pam.beasly@dmi.com: + incorrectValues: + - Beasly + - pam +``` + +**Transformed Tags** +```yaml +- "cost_center": "SCR1138" +- "environment": "production" +- "owner": "dwight.schrute@dmi.com" +``` + +### Example: Using regex matches + +Regular expressions can be used in `incorrectValues` and `incorrectKeys` are identified by this regex: +``` +^/((?:\\/|[^/])*)/([dgimsuy]*)$ +``` +Malformed regexes are treated as string literals. + +**Rules** +```yaml +environment: + incorrectKeys: + - /env.*/gi + replacementValue: undefined + values: + production: + incorrectValues: + - /pr.*/gi + development: + incorrectValues: + - /dev.*/gi +cost_center: + incorrectKeys: + - /cost.*cent.*/gi + replacementValue: undefined + values: + SCR1138: + incorrectValues: + - /.*1138.*/ + NSH1234: + incorrectValues: + - /.*1234.*/ +``` + +**Transformed Tags** +```yaml +- "cost_center": "SCR1138" +- "environment": "production" +- "owner": "dwight" +``` + +### Edge Cases +- If there are multiple matches for an incorrect value then the first alphabetical match for the correct key will be used. +- Malformed regexes are treated as string literals. +- If there is no match for the incorrectKeys or in incorrectValues, the output map will match the input. +- Multiple matches for an incorrect value will result in the the first alphabetical match being used. + +## Rules Schema + +### Structure of the Rules YAML + +The transformMap function expects a JSON object with the following structure: + +```json +{ + "key1": { + "incorrectKeys": [ + "badkey1a", + "badkey1b" + ], + "replacementValue": "newKey1", + "values": { + "value1": { + "incorrectValues": [ + "badValue1a", + "badValue1b" + ] + } + } + }, + "key2": { + "incorrectKeys": [ + "badkey2a", + "badkey2b" + ], + "replacementValue": "newKey2", + "values": { + "value2": { + "incorrectValues": [ + "badValue2a", + "badValue2b" + ] + } + } + } +} +``` + +The rules object can be stored in Guardrails using the policy `Turbot > Tags > Transform Rules`. When setting this policy via the Guardrails console yaml format can be used in addition to json: + +```yaml +key1: + incorrectKeys: + - badkey1a + - badkey1b + replacementValue: newKey1 + values: + value1: + incorrectValues: + - badValue1a + - badValue1b +key2: + incorrectKeys: + - badkey2a + - badkey2b + replacementValue: newKey2 + values: + value2: + incorrectValues: + - badValue2a + - badValue2b +``` + +## Storing rules in a Guardrails File + +The recommended way of managing transform rules as code, is to store them in a `Guardrails File`. Here is an example terraform template for creating a Guardrails file. + +```hcl +resource "turbot_file" "tag_rules" { + parent = "tmod:@turbot/turbot#/" + title = "Tag Transform Rules" + akas = ["tag_rules"] + content = <<-EOT + { + "key1": { + "incorrectKeys": [ + "badkey1a", + "badkey1b" + ], + "replacementValue": "newKey1", + "values": { + "value1": { + "incorrectValues": [ + "badValue1a", + "badValue1b" + ] + } + } + }, + "key2": { + "incorrectKeys": [ + "badkey2a", + "badkey2b" + ], + "replacementValue": "newKey2", + "values": { + "value2": { + "incorrectValues": [ + "badValue2a", + "badValue2b" + ] + } + } + } + } + EOT +} +``` + +Guardrails Files only accept JSON, but YAML can still be used for the rules here by using the built-in YAML and JSON encode and decode functions in Terraform: + +```hcl +locals { + yaml_string = <<-EOT + key1: + incorrectKeys: + - badkey1a + - badkey1b + replacementValue: newKey1 + values: + value1: + incorrectValues: + - badValue1a + - badValue1b + key2: + incorrectKeys: + - badkey2a + - badkey2b + replacementValue: newKey2 + values: + value2: + incorrectValues: + - badValue2a + - badValue2b + EOT +} + +resource "turbot_file" "tag_rules" { + parent = "tmod:@turbot/turbot#/" + title = "Tag Transform Rules" + akas = ["tag_rules"] + content = jsonencode(yamldecode(local.yaml_string)) +} +``` + +## Example Calculated Policy + +The example creates a Smart Folder, sets the `AWS > S3 > Bucket > Tags` guardrail to `Enforce: Set tags`, and creates our calculated policy that reads the rules from the Guardrails File specified in the previous section. + +```hcl +resource "turbot_smart_folder" "tag_transform_example" { + parent = "tmod:@turbot/turbot#/" + title = "Tagging Transformation Example" +} + +resource "turbot_policy_setting" "aws_s3_bucket_tags" { + resource = turbot_smart_folder.tag_transform_example.id + type = "tmod:@turbot/aws-s3#/policy/types/bucketTags" + value = "Enforce: Set tags" +} + +resource "turbot_policy_setting" "aws_s3_bucket_tags_template" { + resource = turbot_smart_folder.tag_transform_example.id + type = "tmod:@turbot/aws-s3#/policy/types/bucketTagsTemplate" + template_input = <<-EOT + { + rules: resource(id:"tag_rules") { + data + } + resource { + turbot { + tags + } + } + } + EOT + template = <<-EOT + {%- set tags_map = $.resource.turbot.tags -%} + {%- set rules = $.rules.data -%} + {% for key,value in transformMap(tags_map, rules) -%} + - "{{key}}": "{{value}}" + {% endfor -%} + EOT +} +``` diff --git a/docs/concepts/guardrails/trusted-access.md b/docs/concepts/guardrails/trusted-access.md new file mode 100644 index 00000000..fe58b271 --- /dev/null +++ b/docs/concepts/guardrails/trusted-access.md @@ -0,0 +1,248 @@ +--- +title: Trusted Access Guardrails +sidebar_label: Trusted Access +--- + +# Trusted Access Guardrails + +## Overview + +Trusted Access guardrails allow you to define whom and what you trust and +enforce those limitations on your cloud resources. With Guardrails Trusted Access +policies, you can define which accounts, services, and organizations are allowed +to be granted access your resources. The Trusted Access control can audit or +enforce those policies, giving centralized control over trusted boundaries. + +Many examples here will list AWS, but these policies also are available for +Azure and GCP resources. + +## Policies and Controls + +Trusted Access controls are generally divided into two patterns: + +- [Simple List Pattern](#simple-list-pattern) + +- [IAM Resource Policy Pattern](#iam-resource-policy-pattern) + +## Default Policies + +Default policies at the account level allow administrators to define trusted +boundaries centrally for all services. However, these can be overrode by either +defining resource type specific Trusted Access policies, or by setting an +exception for the default policy. + +### Account-level Defaults + +The value for all of the account-level default policies is to allow everything: +`*` + +| Policy | Description | +| ------------------------------------------------------ | ------------------------------ | +| `AWS > Account > Trusted Accounts [Default]` | A list of AWS account IDs | +| `AWS > Account > Trusted Organizations [Default]` | A list of AWS organization IDs | +| `AWS > Account > Trusted Identity Providers [Default]` | A list of Identity providers | +| `AWS > Account > Trusted Service [Default]` | A list of AWS services | + +### Service-level Defaults + +The value for all of the service-level default policies is to allow everything: +`*` + +| Policy | Description | +| -------------------------------------------------------- | ------------------------------ | +| `AWS > {Service} > Trusted Accounts [Default]` | A list of AWS account IDs | +| `AWS > {Service} > Trusted Organizations [Default]` | A list of AWS organization IDs | +| `AWS > {Service} > Trusted Identity Providers [Default]` | A list of Identity providers | +| `AWS > {Service} > Trusted Service [Default]` | A list of AWS services | + +### Simple List Pattern + +Some resource types allow you to grant access to other accounts. + +Guardrails solves this with two policies: + +- `Trusted Access`: Allows you check or enforce whether the sharing is allowed + or not, and to which accounts. Allows administrators to configure if Guardrails + will check or enforce Trusted Access. +- `Trusted Access > Accounts`: Allows you to specify the list of AWS account IDs + that are trusted. + +For resources that support cross account access, Guardrails can check or enforce to +the list of AWS accounts. These policies can be found directly under the service +in the hierarchy: + +- `{Provider} > {Service} > {Resource} > Trusted Access` +- `{Provider} > {Service} > {Resource} > Trusted Access > Accounts` + +
    +Example: Trusted Access policies for EC2 Snapshots: +
      +
    • AWS > EC2 > Snapshot > Trusted Account
      • +
    • AWS > EC2 > Snapshot > Trusted Account > Accounts
      • +
    +
    + +Acceptable Trusted Access policy values are consistent across resource types: + +| Value | Description | +| ------------------------------------ | ---------------------------------------------------------- | +| `Skip` | Skip - no action taken | +| `Check: Trusted Access > Accounts` | To check access is granted to the list of trusted accounts | +| `Enforce: Trusted Access > Accounts` | To enforce, access to non-trusted accounts are removed | + +### IAM Resource Policy Pattern + +Many resources allow users to grant access directly on the resource itself via a +resource policy. The Trusted Access control will evaluate and modify access +granted in said resource policy. + +Guardrails allows Trusted Access configurations via this list of policies. Note that +while they all exist, is not necessary to configure all of them in order to +enforce or check resources for unauthorized access: + +- `Trusted Access`: Allows administrators to check or enforce whether the + sharing is allowed or not and to which accounts, services, and federated + users. +- `Trusted Access > Accounts`: Allows administrators to specify the list of AWS + account IDs that are trusted to access the resource. +- `Trusted Access > Organization Restrictions`: Allows administrators to specify + the list of AWS organization IDs that are trusted to access the resource. +- `Trusted Access > Identity Providers`: Allows administrators to specify the + list of Identity Providers that are trusted to access the resource. +- `Trusted Access > CloudFront Origin Access Identities`: Allows administrators + to specify the list of CloudFront Origin Access Identities (OAIs) that are + trusted to access the resource. +- `Trusted Access > Services`: Allows administrators to specify the list of AWS + Services that are trusted to access the resource. + +These policies can be found under the service in the hierarchy: + +- `{Provider} > {Service} > {Resource} > Policy > Trusted Access` +- `{Provider} > {Service} > {Resource} > Policy > Trusted Access > Accounts` +- `{Provider} > {Service} > {Resource} > Policy > Trusted Access > Organization Restriction` +- `{Provider} > {Service} > {Resource} > Policy > Trusted Access > Identity Providers` +- `{Provider} > {Service} > {Resource} > Policy > Trusted Access > CloudFront Origin Access Identities` +- `{Provider} > {Service} > {Resource} > Policy > Trusted Access > Services` + +
    +Example: S3 Trusted Access policy family: +
      +
    • AWS > S3 > Bucket > Policy > Trusted Access
      • +
    • AWS > S3 > Bucket > Policy > Trusted Access > Accounts
      • +
    • AWS > S3 > Bucket > Policy > Trusted Access > Organization Restriction
      • +
    • AWS > S3 > Bucket > Policy > Trusted Access > Identity Providers
      • +
    • AWS > S3 > Bucket > Policy > Trusted Access > CloudFront Origin Access Identities
      • +
    • AWS > S3 > Bucket > Policy > Trusted Access > Services
      • +
    +
    + +Again, acceptable Trusted Access policy values are consistent across resource +types: + +| Value | Description | +| ---------------------------------- | ------------------------------------------------------------------------------------------------------------------------------- | +| `Skip` | Skip - no action taken | +| `Check: Trusted Access` | To check access is granted to the list of AWS accounts, Organizations, Services, Identity Providers, and OAIs set on the policy | +| `Enforce: Revoke untrusted access` | To enforce, access to non-trusted members are removed | + +**Note**: + +- The `Trusted Access` control only evaluates access granted to **external + entities** for the resource in the resource policy. +- All the `Trusted Access` sub-policies might not be applicable for all resource + types. +- The `Trusted Access` control only applies to policy statements that allow + access (where effect is allow). Deny statements are ignored by the control. +- Both `Trusted Access > Accounts` and + `Trusted Access > Organization Restrictions` apply to AWS principals, and are + evaluated independently. To have access, a principal must be allowed in + `Trusted Access > Accounts` AND be a member of an Organization that is allowed + in `Trusted Access > Organization Restrictions` +- A Service Principal that is allowed per `Trusted Access > Services` may also + restrict the source resource to accounts per + `Trusted Access > Services > Source Account Restrictions` via a condition. + - When the service supports `aws:Source*` conditions, Guardrails will evaluate the + `aws:Source*` conditions on that statement and amend (or add the + `aws:SourceAccount` condition) to remediate. S3 Bucket notifications to SNS + are an example of such a situation. + - When the service (such as CloudTrail) does not support `aws:Source*` + conditions, Guardrails will not enforce this restriction on that statement. + +### Example: AWS > S3 > Bucket > Policy > Trusted Access + +First, assume that the bucket policy is trusting the account `123456789210` that +is under the organization `o-c6v5d4wd43`. The identity provider granted access +in the bucket policy is `www.facebook.com`. The service granted access to the +bucket via existing bucket policies is `ec2.amazonaws.com`, and the CloudFront +Origin Access Identity with access is defined as `E1QK6X5E0FOET6`. The following +policies have been configured in Guardrails: + +- **AWS > S3 > Bucket > Policy > Trusted Access** is set to + `Check: Trusted Access`. +- **AWS > S3 > Bucket > Policy > Trusted Access > Accounts** is set to + `- 123456789210`. +- **AWS > S3 > Bucket > Policy > Trusted Access > Organization Restriction** is + set to `- o-c6v5d4wd43`. +- **AWS > S3 > Bucket > Policy > Trusted Access > Identity Providers** is set to + `- www.google.com`. +- **AWS > S3 > Bucket > Policy > Trusted Access > Services** is set to + `- sns.amazonaws.com`. +- **AWS > S3 > Bucket > Policy > Trusted Access > CloudFront Origin Access + Identities** is set to `E1QK6X5E0FOET6`. + +In order, these policies will evaluate `Accounts`, `Organization Restriction`, +and `CloudFront Origin Access Identities` as trusted, but `Identity Providers` +and `Services` as untrusted. The policy evaluation will result the control being +in the **ALARM** state. + +**Sample S3 bucket policy for the above example**: + +```json +{ + "Version": "2012-10-17", + "Id": "2012-10-17", + "Statement": [ + { + "Sid": "ReadAccess", + "Effect": "Allow", + "Principal": { + "Federated": "www.facebook.com" + }, + "Action": "s3:ListBucket", + "Resource": "arn:aws:s3:::bucketexample01" + }, + { + "Sid": "WriteAccess", + "Effect": "Allow", + "Principal": { + "AWS": "arn:aws:iam::cloudfront:user/CloudFront Origin Access Identity E1QK6X5E0FOET6" + }, + "Action": "s3:PutBucket", + "Resource": "arn:aws:s3:::bucketexample01" + }, + { + "Sid": "ReadAccess1", + "Effect": "Allow", + "Principal": { + "Service": "ec2.amazonaws.com" + }, + "Action": "s3:ListBucket", + "Resource": "arn:aws:s3:::bucketexample01" + }, + { + "Sid": "WriteAccess1", + "Effect": "Allow", + "Principal": { + "AWS": "arn:aws:iam::123456789210:root" + }, + "Action": "s3:PutBucket", + "Resource": "arn:aws:s3:::bucketexample01", + "Condition": { + "StringEquals": { + "aws:PrincipalOrgID": "o-c6v5d4wd43" + } + } + } + ] +} +``` diff --git a/docs/concepts/guardrails/usage.md b/docs/concepts/guardrails/usage.md new file mode 100644 index 00000000..9146c12b --- /dev/null +++ b/docs/concepts/guardrails/usage.md @@ -0,0 +1,81 @@ +--- +title: Usage Guardrails +sidebar_label: Usage +--- + +# Usage Guardrails + +**Usage** guardrails give administrators the ability to generate alarms +if the number of resources in a specific service exceeds a set amount. These +guardrails exist for a wide number of resources across many services in AWS and +GCP. + +Note that the Usage guardrails are not related to the Approved > Usage policy in +the [Approved guardrails](guardrails/approved) family. + +Usage guardrails have a consistent form: + +- `{provider} > {service} > {resource} > Usage` + +
    +
      +
    • AWS > EC2 > Instance > Usage
      • +
    • GCP > Network > Firewall > Usage
      • +
    +
    + +These policies also have consistent options that can be configured: + +- `Skip` +- `Check: Usage <= 85% of Limit` +- `Check: Usage <= 100% of Limit` + +Note that Guardrails will never destroy resources even if the limit is exceeded, and +will not prevent users from creating resources once the Usage control moves into +the alarm state. + +The above policies have a sub setting to determine said limit, again with a +consistent form: + +- `{provider} > {service} > {resource} > Usage` + +
    +
      +
    • AWS > EC2 > Instance > Usage > Limit
      • +
    • GCP > Network > Firewall > Usage > Limit
      • +
    +
    + +The limit policy checks the total number of resource types within a given +account. This value can either be set statically by an administrator or a +[calculated policy](faq/calculated-policies) can be written to set the value +dynamically. + +### Example Guardrail: AWS > EC2 > Instance > Usage + +The `AWS > EC2 > Instance > Usage` policy queries an AWS account for the amount +of EC2 instance that exist. The policy `AWS > EC2 > Instance > Usage > Limit` +determines the amount of resources that can exist before the Usage guardrail +triggers an alarm. + +Suppose two organizations have a limit of 50 EC2 instance that can be active at +any one time. The first organization has a soft limit, and the second +organization has a hard limit. + +
    + Assume the organization wants to be notified at 50 instances, but this is a soft limit. The following policies could be set: +
      +
    • AWS > EC2 > Instance > Usage > Limit set to 50.
      • +
    • AWS > EC2 > Instance > Usage set to Check: Usage <= 100% of limit
      • +
    + When the number of EC2 instances within said account reaches 50, the Usage control will generate an alert. +
    + +
    + Assume the organization wants to be notified at 50 instances, and accounts must not have more than this limit at any one time (aka hard limit). The following policies could be set: +
      +
    • AWS > EC2 > Instance > Usage > Limit set to 50.
      • +
    • AWS > EC2 > Instance > Usage set to Check: Usage<= 85% of limit
      • +
    + When the number of EC2 instances within said account reaches 43, the Usage control will generate an alert. This allows administrators to monitor the account prior to reaching the organizational restriction of 50 instances per account. +
    diff --git a/docs/concepts/iam/authentication/index.md b/docs/concepts/iam/authentication/index.md new file mode 100644 index 00000000..6472fd20 --- /dev/null +++ b/docs/concepts/iam/authentication/index.md @@ -0,0 +1,87 @@ +--- +title: Authentication +sidebar_label: Authentication +--- + +# Authentication + +Guardrails supports multiple methods of authentication, including LDAP and +local username/passwords. + +### Directories + +A directory is a mechanism that allows users and groups to access Guardrails. In the +simplest use case, a directory will allow a user to log into the Guardrails +application, where they can then perform actions entitled to them via the +permissions model. + +Guardrails currently allows user/group access from 3 different sources: + +| Source | Description | +| -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| Guardrails Local Directory | Guardrails provides support for basic user and group management in an internal directory. Guardrails local directories are typically used for bootstrapping and break-glass access. An installation of Guardrails will contain an initial internal directory, with a break-glass/admin user. This user can then be used to create further break-glass users, or add and manage additional directories. | +| Turbot.com Directory | While named similarly, the Turbot.com directory is the connection of the user profile that exists on turbot.com and workspaces. A Turbot.com directory can be created in a workspace, and when attempting to log in via this directory, the user will get redirected to guardrails.turbot.com and back to the workspace! A profile is created upon the first login and administrators can assign permissions once the user has done so. | +| Google | Guardrails integrates with Google domains via a client ID/secret pair, allowing users within that domain to log into Guardrails. Group management can be done from within the Google Admin console. | +| SAML | We have integrations with Identity Providers (IDPs) such as Okta, Ping, ADFS and in-house SAML solutions.

    SAML is a popular choice, particularly with customers wishing to access Cloud Providers such as AWS, but without needing to provide direct access back to their on-site directory (e.g. Active Directory).

    Guardrails also supports the sourcing of user groups in the SAML assertion | +| LDAP/ LDAPS | Guardrails can use a LDAP/ LDAPS directory to sync groups and users and map them to existing profiles. | + +To setup a new directory or if there are questions regarding LDAP group sync, +head on over to our [Directories guide](guides/directories). + +To get right in and assign grants to user profiles on existing directories, +check out our +[Assigning Permissions in Guardrails](guides/iam/permission-assignment) +documentation. + +### Profiles + +A profile is simply the Guardrails representation of a user from one or more +directories. Every user that logs into Guardrails via a directory will be +represented as a profile. All subsequent permissions, actions etc will be +attributed to that profile. + +By creating an abstraction of a directory user as a profile in Guardrails, this +allows advanced techniques such as multiple directories mapping a user to a +single profile in Guardrails. For example, you can configure a SAML directory used +for user authentication, whilst adding an additional LDAP directory used to +perform searches and other controls against the same user in your corporate +directory. + +#### Login names + +While a user in a directory can only be represented by a single profile in +Guardrails, that same user may require a different identity in all of the providers +that Guardrails will interact with ( AWS, Azure, GCP, etc.). These mappings can be +controlled using policies that target the profile. + +
    Login name mappings for the Guardrails Profile + Turbot > Google @ acme.com > John Doe to login to AWS, Azure, and GCP + are set via the policies Azure > IAM > Login Names, + GCP > IAM > Login Names, and AWS > IAM > Login User Names +
    + +Typically, these use calculated policies to map users with a standard template. + +##### Example: `Azure > IAM > Login Names` + +For Acme corp, the `Azure > IAM > Login Names` is set using a calculated policy: + +**Input Query** + +```graphql +{ + profile { + email + } +} +``` + +**Input Template** + +``` +{% if $.profile.email %} +- {{$.profile.email.split("@")[0]}}@acme.onmicrosoft.com +{% endif %} +``` + +This results in user names such as "wiley@acme.onmicrosoft.com" diff --git a/docs/concepts/iam/identity/index.md b/docs/concepts/iam/identity/index.md new file mode 100644 index 00000000..7ae39143 --- /dev/null +++ b/docs/concepts/iam/identity/index.md @@ -0,0 +1,115 @@ +--- +title: Identity +sidebar_label: Identity +--- + +# Identity in Guardrails + +Guardrails attempts to map event to specific entities to facilitate analysis and correlation of notifications and events. Every Guardrails event contains an Actor object with this identifying information. + +An Identity represents an actor known to Guardrails. An Identity can be: + + - A Guardrails Profile - A user that can log in to Guardrails. + - A cloud resource like an AWS Account (for Root activities) or EC2 Instance. + - Turbot - A special Guardrails Identity represents Turbot. + - If Guardrails cannot map the request to a known resource, it is Unidentified. + +A **Persona** is a physical representation of an identity id in a given scope. A single identity may have multiple personas. For example. John (Identity) has an user accounts (personas) in AWS, Azure and Google. Examples of personas include: + + - AWS User Account + - AWS Role + - GCP User + +Guardrails attempts to map both Identities and Personas to resources in the CMDB, however not all security principles may be present in the Guardrails CMDB. Guardrails uses the **Alternate Persona** as a way to help provide context for such instances. The **alternate persona** for an event is NOT mapped to a Guardrails entity, but is a string representation to identify the actor in the native format provided in the event. + +**Note**: +Guardrails maps the actor information at the time that it receives the event. If we cannot map the identity and persona at the time the event is received, they will be unidentified in the event. The events are never updated with actor information. Note that something is always written to the alternate persona, so some minimal set of identifying information is always contained in the event. For example: + + - Guardrails receives a Bucket created event for bucket1, and the user was `john@mycompany.com` + - Assume that there is no profile for `john@mycompany.com`, so the identity is Unidentified, and the alternate persona is set to `john@mycompany.com` + - An admin creates a Guardrails profile for `john@mycompany.com` + - Any new events from `john@mycompany.com` will map his profile as the identity, however the bucket created event for bucket1 will NOT be updated with his identity. + +Guardrails identity mapping is a powerful mechanism for providing user context and correlating user activity throughout the infrastructure stack. In order to simplify the setup and operation, Guardrails must make certain (usually safe) assumptions about the identifying information in the provider's events. While Guardrails provides enhanced visibility into user activity, your cloud provider's audit trail should be considered the data of record. + +## AWS Identities +AWS identities are determined from the `userIdentity` element in CloudTrail. + +### userIdentity Schema + - `userIdentity` schemas varies by type + - `IAMUser` and `AssumedRole` are the most common types + +### Types + + +| Type | Description +|-|- +| **Root** | The request is made with your AWS account credentials. If the `userIdentity` type is Root and you set an `alias` for your account, the *userName* field contains your account alias. +| **IAMUser** | The request is made with the credentials of an IAM user. +| **AssumedRole**| The request is made with security credentials that were obtained with a role via a call to the AWS Security Token Service (AWS STS) AssumeRole API. +| **FederatedUser**| The request is made with security credentials that were obtained via a call to the AWS STS GetFederationToken API. The `sessionIssuer` element indicates if the API was called with root or IAM user credentials. +| **AWSAccount** | The request is made by another AWS account. (Another AWS account switches to that role to assume the role for your account). +| **AWSService** | The request is made by an AWS account that belongs to an AWS service. (An AWS account owned by an AWS service assumes a role in your account. For example, AWS Elastic Beanstalk assumes an IAM role in your account to call other AWS services on your behalf). + +*AWSAccount* and *AWSService* appear for type in your logs when there is cross-account access using an IAM role that you own. The AssumeRole call is of *AWSAccount* or *AWSService* type, but subsequent calls from that role seem to be AssumeRole type. + +## Examples userIdentity schemas + +### userIdentity with IAM user credentials (User) + +```json +"userIdentity": { + "type": "IAMUser", + "principalId": "AIDAJ45Q7YFFAREXAMPLE", + "arn": "arn:aws:iam::123456789012:user/Alice", + "accountId": "123456789012", + "accessKeyId": "AKIAIOSFODNN7EXAMPLE", + "userName": "Alice" +} +``` +### userIdentity with temporary security credentials (assume role) + +```json +"userIdentity": { + "type": "AssumedRole", + "principalId": "AROAIDPPEZS35WEXAMPLE:AssumedRoleSessionName", + "arn": "arn:aws:sts::123456789012:assumed-role/RoleToBeAssumed/MySessionName", + "accountId": "123456789012", + "accessKeyId": "AKIAIOSFODNN7EXAMPLE", + "sessionContext": { + "attributes": { + "mfaAuthenticated": "false", + "creationDate": "20131102T010628Z" + }, + "sessionIssuer": { + "type": "Role", + "principalId": "AROAIDPPEZS35WEXAMPLE", + "arn": "arn:aws:iam::123456789012:role/RoleToBeAssumed", + "accountId": "123456789012", + "userName": "RoleToBeAssumed" + } + } +} +``` +## Mapping AWS Identities in Guardrails + + +| Type | Identity | Persona | AltPersona +|-|-|-|- +| **Root**| An AWS Account resource via `arn` | undefined | `arn` +| **FederatedUser** | reverse lookup of `sessionContext.sessionIssuer.userName` in Login user names policy | Resources with aka `sessionContext.sessionIssuer.arn` | `sessionContext.sessionIssuer.userName` +| **AWSAccount** | An AWS Account resource via `accountId` | Any resource with aka `roleArn` | `recipientAccountId` +| **AWSService**| none | none | `invokedBy` +| **IAMUser**| reverse lookup of `userName` in login user names policy to a Guardrails Profile | (AWS User) resource via resource with aka matching `arn` | `userName` +| **AssumedRole**| Set to Turbot if `sessionIssuer.arn` is the Guardrails service role. If it has a token in the arn, get the identity (Guardrails Profile) from it. Else it is `unidentified` | any resource with aka matching `arn` | first 2 fields after the first slash in the `arn` + +**Note**: + - IAM Users are mapped via a reverse lookup of the username to the `AWS > IAM > Login User Names` policy to find a matching profile. + - Guardrails roles (AWS/Superuser, AWS/Admin, AWS/S3/Operator, etc) contain an encoded token in the session name that contains the id of the Guardrails Profile that is logged in. + - These tokens are encrypted with a secret + - The tokens are valid for 1 hour + + - Non-Guardrails roles are mapped via a reverse lookup of the role session id to the `AWS > IAM > Login User Names` policy to find a matching profile, similar to user names + - This is not completely secure because we don't know for sure who assumed the role - anyone that can assume the role can set the role session name. + + diff --git a/docs/concepts/iam/index.md b/docs/concepts/iam/index.md new file mode 100644 index 00000000..1b5705da --- /dev/null +++ b/docs/concepts/iam/index.md @@ -0,0 +1,39 @@ +--- +title: IAM +sidebar_label: IAM +--- + +# Identity and Access Management (IAM) + +Identity and Access Management (IAM) is a core concept of Guardrails and is +responsible for key features such as: + +- Management of user/group directory sources for Guardrails +- Attributing actions to a directory user/group +- Management of permissions in Guardrails +- Management of permissions in Cloud Providers + +The [Authentication](concepts/iam/authentication) concepts page details +different ways to grant users access to the Guardrails console - Turbot directory +(local or via an organization directory), SAML (Azure AD, Okta, Ping, etc), and +Google. Guardrails does support +[LDAP/LDAPS directories](guides/directories/ldap-ldaps). These directories can +be created to sync active directory groups with Guardrails profiles. + +[Identities](concepts/iam/identity) is the mapping of events in the cloud to +Guardrails entities. Every Guardrails event contains an Actor object with this +identifying information. + +Finally, [Permissions](concepts/iam/permissions) tie together authentication to +resource access. Using Guardrails' robust permission structure, administrators can +grant users access to a broad and/or specific set of resources. + +## Guides + +| | | +| --------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| [Setting up a directory](guides/directories) | This page includes instructions on creating a Local directory (both a local and organizational directory), Google, Okta, Azure AD, as well as configuring LDAP/LDAPS to sync groups. | +| [Best practice for Guardrails provisioned admin](guides/iam/administrators) | Upon workspace creation, a local administrator is provisioned in the local directory. This guide details the steps to take after initial login. | +| [Adding users to a local Turbot directory](guides/iam/user-mgt) | SAML and Google directories in Guardrails automatically provision profiles when users login, but administrators must create profiles for a local Turbot directory. | +| [API Access keys](guides/iam/access-keys) | Create API access keys in Guardrails. | +| [Assigning permissions](guides/iam/permission-assignment) | Assigning permissions in Guardrails. | diff --git a/docs/concepts/iam/permissions/index.md b/docs/concepts/iam/permissions/index.md new file mode 100644 index 00000000..b4876a84 --- /dev/null +++ b/docs/concepts/iam/permissions/index.md @@ -0,0 +1,176 @@ +--- +title: Permissions +sidebar_label: Permissions +--- + +# Permissions + +Guardrails provides a rich set of capabilities for managing authentication of users, +as well as authorization to cloud based services and resources. + +Guardrails integrates with the native Identity and Access Management solutions for +the cloud provider but takes a loosely prescriptive approach to managing access +-- we attempt to provide a well-defined framework that allows flexibility in +implementation while greatly simplifying the management of permissions and +policies. + +![](/images/docs/guardrails/turbot-iam.png) + +
    Alice is granted Turbot/Owner at the Guardrails (Workspace) level. She can set permissions, install and uninstall mods, create sub-folders, and import cloud accounts. She can perform any Turbot/Owner operation anywhere through the hierarchy. +
    + +
    Bob is granted AWS/Metadata in Folder A. He can read metadata for any resources anywhere in FolderA (Account A1 and all its descendants, Account A2 and all its descendants). He has no access to anything in Folder B +
    + +
    Carol is granted AWS/S3/ReadOnly in Account A2. She can perform any S3 ReadOnly operation (e.g. ReadOnly, Metadata, Access) in Account A2, but has no access to other services in Account A2 (EC2, etc), and no access to any other AWS accounts +
    + +## Permission Categories, Hierarchy & Inheritance + +After a user has been authenticated and granted access, Guardrails Permission Levels +determine what access they should be granted to which Accounts and Resources. + +Permissions in Guardrails are designed to be consistent, convenient, secure and +flexible. + +  + +### Permission Levels + +Each area of Guardrails (e.g. Folder, AWS, S3) defines a (sub)set of **Permission +Levels** that are consistently defined into specific categories. + +The set of possible levels is consistent across services (though not all +services have all levels). Permissions levels are cumulative, where each level +includes all the permissions of the level(s) before it. + +Permissions Levels, from lowest to highest are as follows: + +- **User**: Can log in, but no rights +- **Metadata**: Read metadata +- **ReadOnly**: Read metadata and data +- **Operator**: Read metadata and data, make low-med risk changes +- **Admin**: Read metadata and data, make high risk changes +- **Owner**: Read metadata and data, make high risk changes, manage access, + modify IAM resources + +At the provider level, there is a special **SuperUser** level. Users assigned +SuperUser permissions have unlimited access. + +- SuperUser has full access to all services, even those that Guardrails doesn't + define permissions for. +- Lockdown policies do not apply to SuperUser. +- There are are no SuperUser levels for individual services, only the AWS + Account or Google project. + +  + +#### Guardrails Permissions + +Guardrails permissions control what users are able to do through the Guardrails Console +and API: + +| Level | Description | +|---------------------|-------------------------------------------------------------------------------------------------------------------------------------------| +| **Turbot/Owner** | Manage permissions (including directories), manage mods AND | +| **Turbot/Admin** | Manage Guardrails resources and policies, including managing Guardrails folders, AWS Accounts, GCP Projects, Azure Subscriptions, etc AND | +| **Turbot/Operator** | Run policy values & controls AND | +| **Turbot/ReadOnly** | View resource data in the CMDB\*\*\* AND | +| **Turbot/Metadata** | View resource data in the CMDB\*\*\* AND | +| **Turbot/User** | Log into the console | + +\*\*\* At present, all the resource data stored in the Guardrails CMDB is considered +to be metadata, thus **Turbot/ReadOnly** and **Turbot/Metadata** are currently +the same. + +  + +#### Cloud Provider Example - AWS Permissions + +AWS permissions are specific to the service they are granting permissions for +while following the general guidelines listed above. For instance, AWS/EC2/Admin +allows users to launch and terminate instances (high risk changes) while +AWS/EC2/Operator allows users to stop and start instances (medium risk changes): + +The Guardrails-standard roles described below automatically accounts for any `AWS > {Service} > Enabled` policy +settings. By default, access is denied to all AWS services. + +| Level | Description | +|-------------------|--------------------------------------------------------------------------------------------------------------------| +| **AWS/SuperUser** | Allows full access permissions to the service with no preventative controls. | +| **AWS/Owner** | Manage permissions in AWS, e.g., management of AWS IAM users, groups, roles, and policies AND | +| **AWS/Admin** | Perform high to medium risk changes, e.g., creating and deleting resources, policy management AND | +| **AWS/Operator** | Perform medium to low risk changes, e.g., stopping and starting resources, tag management, snapshot management AND | +| **AWS/ReadOnly** | Read data, e.g., S3 key contents AND | +| **AWS/Metadata** | Read configuration data and metadata, e.g., describe instance configurations, list buckets. | + +Guardrails also supports permission assignments to Custom Roles and to Custom Groups. + +| Level | Description | +|---------------------------|--------------------------------------------------------------| +| **AWS/Role/{RoleName}** | Grants access to a custom IAM role | +| **AWS/Group/{GroupName}** | Attaches a custom IAM group to a Guardrails-provisioned user | + +  + +### Permission Types + +The permissions levels are applied to **permission types**, which define the +types of resources or services to which they will apply. For example, **AWS** +permissions types apply to all the resources within an AWS account, whereas +**AWS/S3** permissions apply only resource in the S3 service. + +### Permissions & Grants + +A **permission** is the combination of a permission type and level, for example: +`AWS/Admin`, `AWS/S3/ReadOnly`, `AWS/EC2/Operator`. + +A **grant** is the assignment of a permission to a Guardrails user or group on a +resource or resource group. For instance: + +- Nathan is granted `AWS/Admin` on folder `Operations` +- The Ops group is granted `AWS/EC2/Operator` on AWS account `aab` + +Note that a **grant** does not have to be an **active grant**: a grant can be +explicitly activated or deactivated. A grant activation can be set to expire at +a specific time, allowing for time-bound temporary privilege escalation. + +--- + +## Note to Mod Authors + +While Guardrails provides a centralized mechanism for granting permissions, as well +as a framework for defining permissions, it is up to the mod author to determine +how to apply the Guardrails permission levels to their resources and APIs. To +maintain consistency with other Guardrails mods, you should follow the same +guidelines for defining which level to assign a given action: + +- Does the action read, list or describe only metadata properties? If so, this + is likely a **Metadata** permission. Examples include: + - Listing the buckets in an account or project + - Viewing information about whether a virtual machine is running +- Does the action read (but not write) data within a resource? If so, this is + likely a **ReadOnly** permission. Examples include: + - Getting or listing the objects inside a bucket + - Reading log file entries + - Querying a database +- Can the operation be considered low-medium risk? Does it change the state of + resources in ways that are reversible, have no impact on how the resource + operates, and don't permanently destroy primary data? If so, this is likely an + **Operator** permission. Examples include: + - Powering up/down VM instances + - Managing tags + - Managing snapshots / backups +- Can the operation be considered med-high risk, potentially permanently + changing or deleting resources or data? If so, this is likely an + **Administrator** permission. Examples include: + - Creating or deleting VM instances, databases or other cloud resources + - Modifying network routing or gateways + - Managing policies +- Does the operation manage permissions? If so, this is likely an **Owner** + permission. Examples include: + - Managing Users, Roles and Policies + - Managing directories and authentication +- Does the technology have a mode that is completely unrestricted? If so, this + should be reserved for the **SuperUser** level. Examples include: + - Root Login / sudo to root diff --git a/docs/concepts/iam/permissions/turbot-iam.png b/docs/concepts/iam/permissions/turbot-iam.png new file mode 100644 index 0000000000000000000000000000000000000000..165c31a4029c46a30d15428a643f142f1407e5c5 GIT binary patch literal 43235 zcmeFZ^LJ$37A_oijE<9vZFX$iw%M_bj%{_+9ox3mv2C+sC%5{%{hsmt1K%(Ao*KJq z@0w%ng}LUQYd&*5RpAP9;s~%fupl5H2$B*aN+2L$Qy?Iq$1Vo?P_5mBmK ze+krNy@IAGK~DrS4UR$7ALxd#6(C2 z6hhFy$FL+=3MW-&t)xGM#6O1skw9?ZBq&TA$bSxj7}OuV@w;J~|CNBCBl3Zh3V{7{ zaLW0^ipP+cLH<{w!tn_I_ht~7Jq}Q6T+Wy@^#4i}wzpXRy_qy_7oymHkHbjqzmh+V z|I;$?^M8&1|EBhGr}j^ID)v*ol=I)^3g{AZZU;0NO#xA=FNyD`aHhtq^~HCp0~~+M zgb@L(-ac)RqZae;9LJTxC~ObU_w^0N|1(womdHPP4RLmd_5QV*N^*f<5_KdbfcRfK zDHQA$$r6(_wqJrn8HR&+Z~g6~XHh7)y418lVdZ1iOHt*fY2$Z+%h2F);*^XDuEKG> zQ(QAn8rKH>NI@{Fi@c2L- zrwXRR;b^j#kRYNWQ@XdeM`4IvKt8g%#1Zh?9CyF{D~Mi9&rJ`$2|KJ%J;Q0=uIav82zqP zt?7$d`2^%(sul&L8tc#{522(Zk~Muy$ks5!I%Sr_cfa>Xbro-AOQ)KRTnqUC4_!UJ 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Amazon Web Services, Microsoft Azure, and Google Cloud. + +Balancing agility with controls requires a clear and simple set of beliefs guiding our designs and trade-off decisions. This section outlines how Guardrails thinks about enterprise controls for infrastructure governance and outlines the beliefs, models and assumptions Turbot Guardrails has defined to create those guardrails - providing organizations with a working balance between agility and compliance. + +| | +| ---------------------------------------------------- | ------------------------------------------------------------------------------| +| [Controls](concepts/controls) | Controls enforce policies | +| [Guardrails](concepts/guardrails) | Standard guardrails provide a consistent set of controls and policies | +| [Identity and Access Management (IAM)](concepts/iam) | Guardrails provides a flexible IAM model for authentication and authorization | +| [Policies](concepts/policies) | Policies manage configuration settings | +| [Processes](concepts/processes) | Processes perform work | +| [Resources](concepts/resources) | Resources represent objects that are managed by Guardrails | diff --git 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The `Active` and `Approved` policies specify what action to +take, whether raise and alarm (Check) or delete the offending resource +(Enforce). The business logic for deciding resource age or approved status is +encoded in the `Active > Age` and `Approved > Usage` policies. + +Active and Approved controls are standard for all resources. + +## Are there any limitations to calculated policies? + +Calculated policies can only take the actions encoded in existing controls. +`Active` and `Approved` controls are great for removing unapproved resources or +to raise alarms for an administrator. Guardrails has implemented many common +remediations, such as encryption at rest, tagging, and resource access policies. +If the desired remediation action isn't currently available, reach out to +[Guardrails support](mailto:help@turbot.com) with your use case! + +## How do I set a calculated policy? + +In the example below, we will investigate how to set a VPC Endpoint approved +policy to `Not Approved` if the VPC Endpoint AWS policy has a principal value +set to `*` (You will need an existing VPC endpoint under Guardrails management to +test this calculated policy). + +1. In your AWS account locate an existing VPC endpoint and make note of its ID + (e.g. vpce-05b1912865c21251f). + +1. Navigate to the account where the policy will be set, then click on the + `Policies` tab, then select the `New Setting` button: + +1. Once the Create Policy screen opens up, browse to + `AWS > VPC > Endpoint > Approved > Usage`, click `Go` and then `Next`. + +1. Expand the `Scope` drop down menu by clicking on it. + +1. Search or browse to select the level at which the policy will be set. (e.g + Navigate to a region in your AWS Account). Once the proper level is showing, + click `Go`. + +1. The policy wizard is currently in Standard mode. (e.g. showing the basic + options of `Approved`, `Not approved`, or `Approved if AWS > VPC > Enabled`). + +1. To switch to calculated policy mode: Click on the `Switch to calculated mode` + link. Once switched the layout of the `Edit Policy Setting` dialog box + changes with some additional fields. + +1. Note that `Policy Type` and `Resource Scope` were already set in steps 3 & 4. + +1. In the `Setting` field paste the VPC Endpoint ID that you made note of at the + start. If the endpoint has been discovered by Guardrails searching on the + vpce-xxx... id will find it quickly and allow you to select it. + +1. Our calculated policy is evaluating the a policy attached to a VPC Endpoint, + so we query to return only the policy data. Use the following GraphQL example + for your query: + ``` + { + resource{ + stmts: get(path: "PolicyDocument.Statement") + } + } + ``` +1. Validate that the query result window show a valid result for your VPC + endpoint. A default endpoint policy will have a result set that looks like + this: + + ``` + { + "resource": { + "stmts": [ + { + "Action": "*", + "Effect": "Allow", + "Resource": "*", + "Principal": "*" + } + ] + } + } + ``` + + Note the square bracket in the response - this indicates that the returned + data is an array, and thus will affect the structure of the policy template. + +1. Calculated policies use + [Nunjucks template format](https://mozilla.github.io/nunjucks/templating.html) + to evaluate custom logic and return one of the expected values for this + policy. In this case the allowed values are: `Not approved`, `Approved`, + `Approved if AWS > VPC > Enabled`. The following template checks to see if + any overly broad settings exist in the attached policy: + ``` + {% set starValue = "False" %} {# Initialize a value to False #} + {% for statement in $.resource.stmts %} {# Iterate through all statements in the policy #} + {% if statement.Principal == "*" %} + {% set starValue = "True" %} + {% endif %} + {% endfor %} + {% if starValue == "True" %} {# If true, the policy is in violation #} + "Not approved" + {% else %} + "Approved" + {% endif %} + ``` +1. Verify that the query and template are set and verified by Guardrails to evaluate + correctly; the block text below the template field will show the evaluated + value for the example VPC endpoint you selected, but each VPC endpoint will + be individually evaluated by Guardrails at runtime. + +1. Click the `Create` button to save your calculated policy, it will immediately + take effect and evaluate if the current VPC endpoints are configured + correctly. + +## How can I reference variables that include characters in a calculated policy? + +Most variables referenced in calculated policies are trivial, such as `stage`, +`data`, or `name`. However, some cloud resources include attributes with +characters. These include any attribute with a hyphen (`-`) or in some specific +cases, where the attribute is only characters (`*/*`). + +Let's assume we are doing the following query and template for the policy +`AWS > API Gateway > Stage > Approved > Usage`: + +```graphql +{ + stage { + methodSettings + } +} +``` + +```json +{ + "stage": { + "methodSettings": { + "*/*": { + "loggingLevel": "INFO", + "cachingEnabled": false, + "metricsEnabled": true, + "dataTraceEnabled": false, + "cacheTtlInSeconds": 300, + "cacheDataEncrypted": false, + "throttlingRateLimit": 10,000, + "throttlingBurstLimit": 5000, + "requireAuthorizationForCacheControl": true, + "unauthorizedCacheControlHeaderStrategy": "SUCCEED_WITH_RESPONSE_HEADER" + } + } + } +} +``` + +The goal is to make an evaluation based off the `loggingLevel` attribute. To +call this attribute, we need to use the following syntax in the nunjucks +template: + +`$.stage.methodSettings['*/*'].loggingLevel` + +We can do the same things for attributes that contain hyphens, like so: + +`$.bucket.turbot.tags['this-tag-has-hyphens']` + +## How do I add Terraform to calculated policy templates? + +Using a policy such as `AWS > Backup > Source > Stack`, it is possible to create +a calculated policy template that is Terraform. For example, + +```hcl +resource "aws_iam_role" "{{ $.region.metadata.aws.accountId }}_ec2_backup_role" { + name = "turbot_ec2_backup_role" + assume_role_policy = "" +} +``` + +While the calculated policy will be in the ok state (Assuming the query is +valid), the control `AWS > Backup > Source` will return invalid: + +``` +Failed to convert the stack source from HCL to JSON + +Command failed: PATH=$PATH:. hcl2json + +Failed to convert file: :1,104-122: Invalid single-argument block definition; + +A single-line block definition must end with a closing brace immediately after its single argument definition. +``` + +To remedy this, simply use the pipe character (`|`) at the start of the +terraform resource definition in the calculated policy template: + +```hcl +| + resource "aws_iam_role" "{{ $.region.metadata.aws.regionName }}_ec2_backup_role" { + name = "turbot_ec2_backup_role" + assume_role_policy = "" + } +``` + +## Additional Reading + +- [Calculated Policy 7 minute lab](7-minute-labs/calc-policy) +- [Guardrails Samples Repo with calculated policy examples](https://github.com/turbot/guardrails-samples/tree/master/calculated_policies) +- [Policies concepts page](concepts/policies) +- [Azure resource tagging example with calculated policies and Terraform](guides/managing-policies/config-examples/azure-tags) diff --git a/docs/concepts/policies/default-policy.png b/docs/concepts/policies/default-policy.png new file mode 100644 index 0000000000000000000000000000000000000000..385543ec2334af69dd18b526ba975aac546eb45e GIT binary patch literal 88867 zcmaHS2UJtp_BS9!R6u2vUX-Tv-s_-9FGA=|=`Bd_RRxt^LkFdY5;_tHpeRUJT4({K zMF@mW2=%+nn{np7_kW*jxz^>}d-mDq?0xqB?UL8J+K(u%&|e`SAfQlFeejrofHanX zfSCO>gzNkGGqPT+j(Y>)f^)(tCAyL z-&KX&{5^)16;yL0S@HMRLU&$GCOsrU^53=YdUFqcTXEtIg7*zVfw!!(GKPeK+x@Yk zQ3q}gr`_Iy8_x7P(-+3slM>`Q=NV)@Un5H7=}r0klB~YFq^M3+hk!^Ss`J|QfZ&!? zCI$wQg1!0k`wx8G)euqm^4X?I35FWau3E=eng5T+x~T$1P$2*d1=GLFJz~iS$)$k zf4WKF{pC8@)u&Srpcjf~OkVBh+RV@FJ*i(Ic07zzbQ~Dml&H 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z6KPtbAtoYMg4}o3!PL1-IywK?nP6Qo;%p$fztffbX^e5L1^q5~d+tjUtLt2;6m(kcsLis-c z5%hMu8<*R-jsoBVRuRHh*`}mahCft8A^zq{Zgb!IHZ3+K zepRLXYsM-A8x1bPvR*OdrQSiLcIXBMJT^}D%dPRY+*9m4J=|Rbwp4*ihARy@;#pVEh#u*L=GP z&p0D)iz~~?CEGw%VB_eEW~jL{QvdzZK#KtXG!g$%+G72~`ye16ZG^4eb z_BOewexb-@?e&U(D2`(q&r|H9#V;}{sH5%!HSer#teS0x!)_brl3I%by&c{@RM?nu z$Vlw{yU81mq7t*6BZMy($FcSO=S3-pi{#1D$&ZeSm%HEiwXH7o5Iwx>m6 Folder A > AWS 1111 > us-east-1 > my-bucket` + +which has two smart folders `X` and `Y` attached to it (in that order). + +![](/images/docs/guardrails/sf-inject.png) + +The policy hierarchy would be: + +`Turbot > Folder A > AWS 1111 > us-east-1 > X > Y > my-bucket` + +## Policy Type Defaults + +Each policy type has a default value and precedence which are used until a +specific setting is defined in the policy hierarchy. The policy default is +automatically injected into the policy hierarchy at the top level once a mod is +installed. + +Consider the mod `@turbot/aws-s3` installed in `Turbot`, which defines a number +of policy types: + +### Example + +The effective policy value as default setting would be: + +| Type | Default Value | +| -------------------------------------- | ------------- | +| AWS > S3 > Enabled | "Disabled" | +| AWS > S3 > Bucket > Approved | "Skip" | +| AWS > S3 > Bucket > Approved > Budget | "Skip" | +| AWS > S3 > Bucket > Encryption at Rest | "Skip" | +| AWS > S3 > Bucket > Usage > Limit | "100" | + +![](/images/docs/guardrails/default-policy.png) + +The policy hierarchy for `my-bucket` above would now be: +`Default > Turbot > Folder A > AWS 1111 > us-west-1 > my-bucket` + +## Precedence rules: Required vs Recommended + +Each policy has a precedence, which determines how policies may be overridden on +descendent resources in the hierarchy: + +- **Recommended:** Sets a default value, used by descendant resources unless + they specify an alternative. Recommended policies can be overridden by users + that have Turbot/Admin permissions on the descendent resources. + +- **Required:** Settings are mandated on descendant resources, unless an + exception has been granted by a Turbot/Admin at a higher level. + +The value of a policy is calculated down through the Turbot resource +hierarchy,from most general (e.g. default defined by the Mod) to most specific +(e.g. setting for my-bucket). The most specific Required setting wins. If there +are no **Required** settings, then the most specific **Recommended** setting +wins. + +| parent | child | Status | +| ----------- | ----------- | -------------------------------------------------------------- | +| Recommended | None | parent recommended setting is in effect. | +| Required | None | parent required setting is in effect. | +| Required | Required | child required (Exception ) beats the the higher level setting | +| Required | Recommended | parent required beats the the lower level recommended setting | +| Recommended | Recommended | child recommended setting beats higher level recommended | +| Recommended | Required | child setting beats higher level recommended | + +--- + +#### Policy recommendations are inherited through the resource hierarchy + +![](/images/docs/guardrails/inherit-1.png) + +#### Lower level recommendations take precedence over inherited recommendations + +![](/images/docs/guardrails/inherit-2.png) + +#### Required settings always take precedence over recommendations + +![](/images/docs/guardrails/inherit-3.png) + +#### Required settings create exceptions to inherited required settings + +![](/images/docs/guardrails/inherit-4.png) + +#### Exceptions can be set at any level, even individual resources + +![](/images/docs/guardrails/inherit-5.png) + +#### Smart Folders create automated collections of resources using search + +![smart folders](/images/docs/guardrails/smart-folder.png) + +#### Policies set on Smart Folders are injected into the hierarchy + +![smart folders](/images/docs/guardrails/smart-folder-2.png) + +## Permissions and Policy Management + +To manage the policy settings for a resource, the user must have `Turbot/Admin` +permission for both: + +- The resource itself; and +- Any higher level resources where the policy type already has a required + setting. + +
    The policy type AWS > S3 > Bucket > +Encryption at Rest is Recommended to be Enforce: AWS SSE at Turbot +level. This recommended setting is used for all S3 buckets in the entire +environment unless a more specific setting is provided. To override this recommendation +for a specific AWS account 1234 the user only requires Turbot/Admin permission for that AWS account. +
    + +
    The policy type AWS > S3 > Bucket > +Encryption at Rest has a setting of Required to be Enforce: AWS SSE at +Turbot level. This required setting is in force for all S3 buckets in the +entire environment. To create an exception for this policy on a specific +S3 bucket my-bucket the user would need Turbot/Admin permission at Turbot +level. +
    diff --git a/docs/concepts/policies/index.md b/docs/concepts/policies/index.md new file mode 100644 index 00000000..48ef08a7 --- /dev/null +++ b/docs/concepts/policies/index.md @@ -0,0 +1,88 @@ +--- +title: Policies +sidebar_label: Policies +--- + +# Policies + +Automated controls require a large number of configuration settings from the +biggest decisions (e.g. allowed services) right down to small, but critical, +details (e.g. automated tags for cost management). In Guardrails, **Policies** are +used to manage these settings. + +In Guardrails, policies provide: + +- Clearly defined, validated and managed definitions for all + [Resources](concepts/resources) managed by Guardrails +- Secure enforcement of required settings across large environments. +- Exception management, including automatic expiration +- Shared defaults via recommended settings + +Guardrails Policies can be managed using the Guardrails UI, Guardrails API or software +configuration management tools. + +The [v5 mods directory](mods/) is an invaluable resource for looking up policy +URIs, policy values and policy defaults. (A free, self-registered account is +required.) + +A **control objective** is a business need, for example at rest enforcement for +[S3](mods/aws/aws-s3), [EC2](mods/aws/aws-ec2/), and +[RDS](mods/aws/aws-rds/). Note that a control objective may require +one or many policies to fully implement. + +## Key Concepts + +A [Policy Type](concepts/policies/types-categories) targets one of more resource types. +This defines which type of resources the setting applies to. + +
    + The GCP > Storage > Bucket > Approved policy applies to GCP > Storage > Bucket resource types. +
    + +While the policy type targets a specific resource type, you may set the policy +at any scope in the [Policy Hierarchy](concepts/policies/hierarchy) at or above the +resource. Organizations can define policies such as restricted regions for a +folder in Guardrails which are then inherited by accounts and resources within said +folder. + +
    +Setting the GCP > Storage > Bucket > Approved policy at the Project scope will impact all of the buckets in that Project. +
    + +Policy settings have a precedence, which defines whether they are required or +recommended on descendent resources. + +The [Policy Setting](concepts/policies/values-settings) is the desired value for the +policy. For example, an organization could define +[specific approved RDS database engine types](guides/managing-policies/config-examples/rds-db-approved), +which are three simple policies. Alternatively, another organization might want +to +[tag Azure resources with Terraform](guides/managing-policies/config-examples/azure-tags), +where the power of policies are flexed, utilizing Terraform deployment, +[Guardrails Files](guides/files), and +[Calculated policies](faq/calculated-policies). + +Every policy can have an expiration, after which the policy will no longer be in +effect. + +[Controls](concepts/controls/) implement policies. The policy setting is created, an +applicable resource inherits the value, and the relevant control will check and/ +or remediate the resource. + +## Example + +Consider an S3 bucket Resource called `my-bucket`, an instance of the Resource +Type `AWS > S3 > Bucket`. To define the correct configuration of `my-bucket`, a +few policy settings are required. For example: + +| Type | Setting to define for `my-bucket` | +| -------------------------------------- | --------------------------------- | +| AWS > S3 > Bucket > Approved | "Enforce: Delete if new & empty" | +| AWS > S3 > Bucket > Approved > Regions | [ "us-*" ] | +| AWS > S3 > Bucket > Encryption at Rest | "Enforce: AWS SSE or higher" | + +The above policy settings are then applied directly to the bucket (if the +policies were set at the bucket resource level) as a value or are inherited as a +value (the typical situation). In this case, we are telling Guardrails to +`Enforce: Delete if new & empty` if either encryption is not configured to be +`AWS: SSE or higher` OR the bucket is created in a region outside of the US. diff --git a/docs/concepts/policies/inherit-1.png b/docs/concepts/policies/inherit-1.png new file mode 100644 index 0000000000000000000000000000000000000000..31b647211f5dc48aa15b8d586285a60fc8d8a02e GIT binary patch literal 19572 zcmeIaRb19h+ct`bilU^5fJlSXg_6=B-Q6YK-5rW_cU+(}(%m85-KlhU=bFp=*601+ z-}=^C8{fv-c-`^OFnP|*8OM1H{!$Wx&z|5sfrEp4CM?7!0|y7M3I}(O4e=o;*_`65 z0RJHv@QCxk!4-!hU28o6KNIK($%wu_*(Z$XQXaB!?~aBx_b zNj1{!pfe;RIVD>qaWPgM3p0q8u7$Q9#L>(Ww19(ScVq>hW_q?-1de8=<~FR397Mls zu!3(`F)b0n?<%$?97IauQUtsf)_Met5C+IwBF-lS1O)8Xy85g#d;HcsZYT8=d4HpKsQ@~0m@JsTZsBTHK& z3v&WkzgpTBcD5WuM6iMW{`+U1wnqB@8Ohw{-(`UX(!zd2`wsG!_HW;yDLbr`RYuRo z!qg7dy}Y@REhioO@5=wZ_&=ll(~8%^%+gxV#s)OweD`mY|62Cn>q}Z2>4EjZhWT6n zzn1;?`cj4#wiZCv)CGhjR_u%;h%;#ae{lA*NH8>-=*k_U_5sM9M 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b/docs/concepts/policies/taxonomy.md @@ -0,0 +1,255 @@ +--- +title: Taxonomy +sidebar_label: Taxonomy +--- + +# Taxonomy of Policies + +There's a number of dimensions that can be used to describe a policy. They are: + +- the values the policy accepts +- whether it depends on other policies +- and if it's calculated or not. + +Respectively, these are Simple policies, Compound policies and Calculated +policies. In the course of building policies to satisfy a particular control +objective, all three types may be used + +In ascending order of complexity: Simple, Compound, Calculated, Calculated +Simple, Calculated Compound. + +- **Simple**: A policy that takes a single value without any dependent policies. + + - Simple policies can have the following values: + - Enumerated values + - Text field + - [OCL](guides/managing-policies/OCL) [OCL Reference](reference/ocl) + - [YAML](guides/managing-policies/YAML) + - [HCL/Terraform](guides/network-stack) + +- **Compound**: A policy that depends on values in other policies to determine + what to do. A common examples is the `Active` collections of policies. (Other + examples of policy collections are `Approved`, `Configured`, `Logging`, and + `Permissions` to name a few.) On its own the `Active` policy dictates what to + do when an inactive resource is found. It relies on the `Active > Age` and + `Active > Last Modified` child policies to determine if the resource is + active. + +- **Calculated**: Calculated policies are most often used when a customer needs + to implement business logic when evaluating a resource. In contrast to Simple + and Compound policies, a calculated policy can implement custom logic based on + CMDB information. Any policy in Guardrails can be made into a calculated policy. + +- **Multi-query Calculated**: Some calculated policies benefit from or require + multiple stages of refinement of input data. For example: A control objective + on a particular network resource type depends on the presence of other + resources in the same virtual network. A single-query calc policy approach + would grab all resources of that resource type for the entire workspace then + filter that huge list in the Nunjucks template. Essentially asking "Return all + resources of this resource type everywhere." In large environments, this can + result in thousands or tens of thousands of `items`. Calc policy GraphQL + results are hard limited to 300 results with no paging possible. The + multi-query approach instead starts with the question "What Virtual Network is + this resource in?" then asks "In this virtual network specifically, what + network resources are available?". Now, instead of thousands of `items`, the + calc policy only has to deal with a few relevant resources. The benefit of + multi-query is that policy developers are assured they get exactly the data + they need with the cost of some added complexity in their policies. + +## Examples + +### Simple Policy Example + +Consider +[`AWS > CloudWatch > Alarm > CMDB`](mods/turbot/aws-cloudwatch/inspect#/policy/types/alarmCmdb) +as an example of a simple policy. It accepts one of three policy values: `Skip`, +`Enforce: Enabled`, `Enforce: Disabled`. Selecting one of these values is all +that's required. + +### Compound Policy Example + +Let's look at the +[`AWS > CloudWatch > Alarm > Active`](mods/turbot/aws-cloudwatch/inspect#/policy/types/alarmActive) +policy collection. The patterns described below will hold for other compound +policies. The collection includes with these (truncated for readability) value +sets: + +- `AWS > CloudWatch > Alarm > Active` + +``` +Skip +Check: Active +Enforce: Delete inactive with 1 day warning +Enforce: Delete inactive with 3 days warning +Enforce: Delete inactive with 7 days warning +``` + +- `AWS > CloudWatch > Alarm > Active > Age` + +``` +Skip +Force inactive if age > 1 day +Force inactive if age > 3 days +Force inactive if age > 7 days +``` + +- `AWS > CloudWatch > Alarm > Active > Last Modified` + +``` +Skip +Active if last modified <= 1 day +Active if last modified <= 3 days +Active if last modified <= 7 days +``` + +We can see that the `Active` policy is the only one that asserts what Guardrails +should do with an out of compliance resource. It will `Skip`, `Check` or +`Enforce`. The `Age` and `Last Modified` policies make assertions about the +state of the resource itself. Remember that `Skip` means "ignore" or "do not +evaluate" to Guardrails, and that almost all policies default to `Skip`. + +Setting the `Active` policy alone will put the `Active` control into an +`Invalid` state because dependent policies of `Active > Age` and +`Active > Last Modified` are in `Skip`. There's no information for the `Active` +policy to make a decision on. If we set `Active > Age` to some value other than +`Skip`, then `Active` can make a decision. + +## Calculated Policies + +Any policy in Guardrails can be turned into a +[calculated policy](faq/calculated-policies). A calculated policy is used +anytime the basic action provided by Guardrails needs to be dependent on some other +information. A common example is to make a resource's tag key/value dependent on +whether the resource is in a production or nonproduction environment. More +complex organizational business rules are often implemented in calculated +policies. + +Calculated policies rely on three things: The information contained in the CMDB +for the target resource, the GraphQL query to access that information and the +Nunjucks template to evaluate it. + +CMDB: Definitions for a resource's CMDB entry can be found in the Mods +Repository documentation. For our CloudWatch Alarm example, we would start with +the [Alarm](mods/turbot/aws-cloudwatch/inspect#/resource/types/alarm) resource +summary then go to the +[Alarm resource definition](mods/turbot/aws-cloudwatch/inspect#/definitions/alarm). +The easiest way to explore is to create an instance of the resource you want to +work on, then look at the data provided in the Overview tab. + +GraphQL: Use the Developer console in your Guardrails workspace to explore the +`resource` query. Under the hood, the calculated policy dialog is making a +similar query. Provided you have an example resource already, navigate to that +resource in the Guardrails console. Go to the Overview tab then look for `id` under +the `turbot` section. Include that long number in the `id` field of the resource +query in the Developer Console. + +When working on calculated policies, make sure to select a target resource. The +below examples won't make sense if you don't pick a resource. + +A simple starter query in the Developer Console might look like: + +``` +query SimpleResourceQuery { + resource(id: "196925434872486") { + data + turbot { + id + akas + } + } +} +``` + +The equivalent calculated policy query is: + +``` +{ + resource { + data + turbot { + id + akas + } + } +} +``` + +Note the implicit inclusion of the resource ID that the calculated policy takes +care of for you. + +Nunjucks: The +[Nunjucks docs](https://mozilla.github.io/nunjucks/templating.html) describe the +full capabilities of what it can do. Developers familiar with string +manipulation, `if-else`, `for` and `range` should be able to orient quickly. A +deep discussion of how to script with Nunjucks is outside the scope of this +guide. + +Familiarity with the CMDB data for the target resource, GraphQL and Nunjucks is +essential to quickly making progress on calculated policies. Be aware that +sometimes a deep understanding of how the cloud provider represents a resource +is required. Data that appears in intuitive places in the provider's UI may not +be intuitively placed in the underlying data structure. + +## Compound Calculated Policies + +Calculated compound policies: Any policy in Guardrails can be made into a calculated +policy. A common compound policy configuration is to have the `Active` policy +statically set to `Check` or `Enforce` then have the `Active > Age` policy be +calculated. However, this can sometimes result in the `Active` control going +into an `invalid` state, as they require at least one of the sub policies not be +in `Skip`. To solve this problem, a calc policy can be placed on the `Active` +policy with similar logic to the `Active > Age` policy. This way, evaluation of +the `Active` control as a whole will go to `Skipped` and avoid the `invalid` +state. + +## Multi-query Calculated Policies + +The below Terraform excerpt shows the YAML array of GraphQL+Nunjucks templates. + +```yaml +- | + { + account { + turbot { + id + } + } + } +- | + { + account { + turbot { + id + } + } + trails: resources(filter: "resourceId:{{ $.account.turbot.id }} resourceTypeId:'tmod:@turbot/aws-cloudtrail#/resource/types/trail' $.Status.IsLogging:true $.IsMultiRegionTrail:true limit:300") { + items { + trailName: get(path: "Name") + cloudWatchLogsLogGroupArn: get(path: "CloudWatchLogsLogGroupArn") + eventSelectors: get(path: "EventSelectors") + } + } + } +``` + +Notes: + +- The YAML `- |` symbols are essential as this indicates that this is an array + of queries and the strings in each array element are multi-line. These `- |` + array indicators should be on their own lines. YAML is also particular about + indentation. +- Only the results of the final query are sent to the control. Any intermediate + results must also be included in the final query. The example shows how this + is done. +- GraphQL permits multiple `resources()` queries when they have labels. The + `trails:` label shows how this is done. +- A full example can be found in the + [Guardrails Samples Repo](https://github.com/turbot/guardrails-samples/tree/master/calculated_policies/aws_s3_approved_static_website_hosting_requires_cloud_front). + +## Additional Information + +- [Calculated Policy 7 minute lab](7-minute-labs/calc-policy) +- [Guardrails Samples Repo with calculated policy examples](https://github.com/turbot/guardrails-samples/tree/master/calculated_policies) +- [Policies concepts page](concepts/policies) +- [Azure resource tagging example with calculated policies and Terraform](guides/managing-policies/config-examples/azure-tags) +- [Calculated Policy FAQ](calculated-faq) diff --git a/docs/concepts/policies/types-categories.md b/docs/concepts/policies/types-categories.md new file mode 100644 index 00000000..558d47b8 --- /dev/null +++ b/docs/concepts/policies/types-categories.md @@ -0,0 +1,50 @@ +--- +title: Policy Types & Categories +sidebar_label: Types & Categories +--- + +# Policy Types & Categories + +### Policy Types + +A **Policy Type** defines a specific policy that may be configured for +resources. For example, `AWS > S3 > Bucket > Approved`. + +Each policy type targets a set of +[Resource Types](concepts/resources/types-categories#resource-types). + +
    The policy type AWS > S3 > Bucket > Approved targets a resource type of AWS > S3 > Bucket, thus every instance of AWS > S3 > Bucket will have an AWS > S3 > Bucket > Approved policy. Each of these instances may have its own policy setting, and will have its own policy value. +
    + +Valid values for a policy type are defined through it's JSON schema. + +
    The policy type AWS > S3 > Bucket > Approved has +a specific enumerated list of valid values: `Skip`, `Check: Approved`, `Enforce: Delete unapproved if new & empty`. +
    + +Policy types are defined in a type hierarchy. + +
    The Approved policy type is actually a child of +the AWS > S3 > Bucket resource type and has child policies such as Regions with a full path of AWS > S3 > Bucket > +Approved > Regions. +
    + +Policy types are defined in [Mods](mods). + +### Policy Categories + +Guardrails may include hundreds or thousands of policy types covering similar +concepts (e.g. Approved, Data Protection) across various services (e.g. AWS, +Azure). The policy type hierarchy provides grouping of policies, but in a +structured service oriented manner. **Policy Categories** provide an alternate, +vendor agnostic, categorization of policy types. + +
    The policy category Turbot > Approved includes many Approved style policies including AWS > S3 > Bucket > Approved. +
    + +Policy categories are typically used for reporting, providing useful aggregation +and filtering of data. + +### Example - Policy Types and Categories + +![](/images/docs/guardrails/policy_types_categories-ex.png) diff --git a/docs/concepts/policies/values-settings.md b/docs/concepts/policies/values-settings.md new file mode 100644 index 00000000..6511a056 --- /dev/null +++ b/docs/concepts/policies/values-settings.md @@ -0,0 +1,109 @@ +--- +title: Policy Values & Settings +sidebar_label: Values & Settings +--- + +# Policy Values & Settings + +### Policy Settings + +Each policy type may have many settings for different resources. + +
    The policy type AWS > S3 > Bucket > Approved may be set to `Enforce: Delete unapproved if new & empty` for development accounts, but deliberately limited to `Check: Approved` for production accounts. +
    + +**Policy Settings** are inherited down through the hierarchy of resources. + +
    AWS > S3 > Bucket > Approved may be set +to `Enforce: Delete unapproved if new & empty` at Turbot level - ensuring all buckets are deleted if they don't meet the approval criteria (e.g. in approved region). +
    + +Policy settings are only valid for target resources and their ancestors. + +
    The Policy Type +AWS > S3 > Bucket > Approved may be set at any resource level from Turbot +down to the specific S3 Bucket such as Turbot > Folder A > AWS 1111 > us-east-1 > my-bucket. +
    + +### Policy Values + +A **Policy Value** is the effective policy setting on an instance of a resource +type. Every resource that is targeted by a given policy setting will have its +own value for that policy, which will be the resultant calculated policy for the +"winning" policy in the hierarchy. + +Policy settings are inherited through the resource hierarchy, and values for a +resource are calculated according to policy settings at or above it in the +resource hierarchy. For example, a policy setting at the Turbot level will be +inherited by all resources below. + +While policy settings can exist above the target in the resource hierarchy, +policy values exist only on the target. + +
    + AWS > S3 > Bucket > Approved +
      +
    • A Policy Setting for AWS > S3 > Bucket > Approved can be made on an AWS Account, Region, or individual bucket.
      • +
    • Every S3 bucket has a Policy Value for AWS > S3 > Bucket > Approved. The policy value may have been set at the AWS account, region, and/or individual bucket - this is the effective value for this instance.
      • +
    +
    + +## Expiration + +Policy settings can be set to only be valid for a period of time. This is often +useful for setting temporary exceptions. You can, for instance, specify that an +exception should expire in 30 days, or that a policy should only be in effect +this Saturday from 1:00am to 4:00am to coincide with your organization's change +control policy. + +## Calculating Policy Values for a Resource + +Policy settings are defined as templates. Policy values are calculated from the +policy setting. In most cases the policy setting is a static data value (e.g. +"Check: Approved") which is simply copied to the policy value. But, in some +cases, the template may include variables or calculations allowing the policy +value to change dynamically - e.g. tag templates that pull information about the +AWS Account or Region. + +To create a calculated policy value, you must specify: + +- An **Input Query**. This must be a valid graphql query. For example: + ```graphql + { + resources(filter: "resourceType:bucket") { + items { + title + } + } + } + ``` +- A **Template**. The template can use the results of the input query (reference + with the `$` variable) and transform them into the format expected by the + policy. For example: + ```jinja + {% for item in $.resourceList.items %} + - {{item.title}} + {% endfor %}` + ``` + +## Exceptions + +Policies often have settings that are applicable to a wide number of resources. +There are, however, inevitably **exceptions** that exist, where the account wide +policy does not apply to that specific resource. + +For example, an AWS account might house S3 buckets that have public access +disabled. This account also has a bucket that must have public access enabled. +In Guardrails, we accomplish this with the concept of exceptions. + +**Exceptions** allow you to override a required setting on a resource lower in +the policy hierarchy. In the above example, S3 public access policies are set to +block, but we can set one specific bucket to allow public access. + +![](/images/docs/guardrails/exception.png) + +When set, the overriding policy setting will be signified with **Effective +Setting** and a check mark. + +Head over to our guide detailing +[how to create an exception](guides/managing-policies#creating-an-exception). diff --git a/docs/concepts/processes/index.md b/docs/concepts/processes/index.md new file mode 100644 index 00000000..d860d660 --- /dev/null +++ b/docs/concepts/processes/index.md @@ -0,0 +1,60 @@ +--- +title: Processes +sidebar_label: Processes +--- + +# Processes + +All work done by Guardrails is organized into discrete processes - API handling, +control execution, actions, etc. Each process has a unique identifier and can +be monitored for progress, logs and outcome. Processes provide a single point +to track progress and information about a sequence of backend decisions and +processing in a single place. + +## States + +Processes follow a clearly defined state machine for phases of execution: + +| State | Description | +| ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------ | +| Starting | Process is being started and input gathered for the Running phase. Any triggering event has been received and acknowledged to the sender. | +| Running | Mods are doing process work. Input is passed from Guardrails and commands are sent back. | +| Handling | The Guardrails engine is handling commands issued during the Running phase. | +| Terminated | The process has finished, no further work will be done. Upon termination the process is immutable, with no extra log entries or changes allowed. | + +Ensuring consistent, reliable process execution is a complex problem with many error conditions. Some examples: + +| Error condition | Description | Remediation | +| -- | -- | -- | +| Zombie | A process that is still in "Running" state in Guardrails, but the associated function or state machine defined by the mod has actually completed without successfully informing Guardrails. | Guardrails checks periodically for zombie processes based on the time spent in Running state. If considered as a zombie, Guardrails will update the error log and terminate the process. | +| Retryable error (e.g. throttling) | A retryable error occurred during process handling. | The process phase will be retried multiple times with backoff between attempts. If the error persists then an error is logged and the process is terminated. | + + +## Log + +Workers may log to the process to record data points, decisions and key actions. + +Log entries are recorded in JSON with the following format: + + { + "level": "info", + "message": "I am information.", + "timestamp": "2018-10-19T12:51:36", + "data": { + "ad": "hoc", + "json": true + } + } + +Log levels follow the [syslog standard](https://en.wikipedia.org/wiki/Syslog#Severity_level): + +| Severity | ID | Used by | Description | +| --------- | ----------- | ----------------- | ----------- | +| Emergency | `emergency` | Guardrails Engine | Guardrails is unavailable and automatic recovery is unlikely. | +| Alert | `alert` | Guardrails Engine | Alert from a key component or dependency. Guardrails is unusable, but may automatically recover. | +| Critical | `critical` | Guardrails Engine | Critical conditions. Guardrails may be unavailable or have severely degraded performance. | +| Error | `error` | Mods | Error significant to an action, but not critical to Guardrails. Review and remediation required. | +| Warning | `warning` | Mods | Warning that an error may occur if action is not taken. Review recommended. | +| Notice | `notice` | Mods | Significant, but normal, events such as automated actions. | +| Informational | `info` | Mods | Information about decisions and interim data. | +| Debug | `debug` | Mods | Debug messages used in development only. | diff --git a/docs/concepts/resources/discovery.md b/docs/concepts/resources/discovery.md new file mode 100644 index 00000000..195eb6a5 --- /dev/null +++ b/docs/concepts/resources/discovery.md @@ -0,0 +1,56 @@ +--- +title: Discovery +sidebar_label: Discovery +--- + +# Discovery + +Discovery is Guardrails' method for automatically searching virtual infrastructure, +systems or applications to build a structured, searchable data representation. +For example, resources in an AWS Account are discovered and stored in Guardrails. + +Discovered resources are always mapped to +[Resource Types](concepts/resources/types-categories#resource-types) and stored +in the [Resource Hierarchy](concepts/resources/hierarchy). + +## Discovery & Real-time Updates + +Typically, Discovery & CMDB controls are used in combination to find new +resources and track changes to them over time. + +### Discovery + +Each resource type registers a `Discovery` control on it's parent type. The +`Discovery` control is designed to find all instances of the resource types from +the parent and upsert them into the Guardrails CMDB. + +
    The Resource type AWS > SQS > Queue defines a +control AWS > SQS > Queue > Discovery with a target resource type of AWS > Region. +
    + +In effect, the parent resource is responsible for creating its children. + +### CMDB + +Each resource type also registers a `CMDB` control on itself. The `CMDB` control +queries the source for the latest and complete details about the resource. + +
    The resource type AWS > SQS > Queue defines a +control AWS > SQS > Queue > CMDB with a target resource type of AWS > SQS > Queue. +
    + +In effect, a resource is considered to be an adult child, looking after itself. + +### Real-time Updates via Events + +While Discovery and CMDB controls can find existing resources and update their +details, Guardrails is designed to react in real-time to resource changes. This is +achieved through event handling for create, update and delete events relating to +a resource. + +
    The sqs.amazonaws.com:CreateQueue event is received by Guardrails and +handled with an immediate CMDB upsert. This triggers the CMDB control for the new AWS > SQS > Queue resource, which then fetches full details using the AWS APIs. +
    + +
    The sqs.amazonaws.com:DeleteQueue event is received by Guardrails and handled with an immediate CMDB deletion. No further queries to the AWS APIs are required. +
    diff --git a/docs/concepts/resources/hierarchy.md b/docs/concepts/resources/hierarchy.md new file mode 100644 index 00000000..c19cda80 --- /dev/null +++ b/docs/concepts/resources/hierarchy.md @@ -0,0 +1,79 @@ +--- +title: Hierarchy +sidebar_label: Hierarchy +--- + +# Resource Hierarchy + +## Overview + +All resources in Guardrails are arranged into a hierarchy. Each resource has one +parent, and zero or more children. + +The **Resource Hierarchy** may be many levels deep, but has 3 general tiers: + +| Tier | Purpose | +| ---------------------- | ---------------------------------------------------------------------------------------------------| +| Turbot | Root node of the hierarchy. | +| Folders | Hierarchy of folders defined in Guardrails. Typically used to separate resources by business unit. | +| Discoverable Resources | Resources discovered from various sources such as cloud providers, servers and other services. | + +![Resource Hierarchy](/images/docs/guardrails/resource-hierarchy2.png) + +## Turbot Root + +Turbot Root is the top level resource of the entire hierarchy, and all other +resources are descendants of this node. This resource is the target for various +controls and policies used by the Guardrails system. + +## Folders + +Folders provide a high level arrangement of resources in Guardrails. Common models +for folders include: + +| Model | Example | +| ------------- | ------------------------------------------------ | +| Business Unit | R&D, Commercial, Admin | +| Compliance | GxP production, GxP Development, PCI, Commercial | +| Environment | Development, Testing, Production | + +A typical hierarchy might look something like the following: + +``` +Turbot + {Company Folder} (Folder) + {Top Level Folder} (Folder) + {Intermediate Folder} (Folder) +``` + +- Folders can be renamed and moved. Use names that make sense within the + organization structure. +- Folders are limited to single inheritance only, consider + [Smart Folders](smart-folders) for cross-hierarchy organization. +- Folder structure is best configured in such a way that matches control, + business, and permission requirements! +- Folders can be created an destroyed using the [Turbot Guardrails Terraform + Provider](https://registry.terraform.io/providers/turbot/turbot/latest/docs/resources/folder). + +## Smart Folders + +[Smart Folders](smart-folders) are a collection of +[Policy Settings](concepts/policies/values-settings#policy-settings) that can be +attached to folders. They do not affect the resource hierarchy described above, +but are part of the [Policy Hierarchy](concepts/policies/hierarchy). + +## Discoverable Resources + +The vast majority of resources in Guardrails are created to represent resources in +other tools or systems. Cloud providers, operating systems, SaaS tools - +virtually any system can be a source of Guardrails Resources. + +All discovered resources are added to the Guardrails Resource Hierarchy. +[Mods](mods) define the structure of these resources, Guardrails simply ensures they +are valid and structured according to their definition. + +
    AWS Account 1111 is added as a discoverable resource, +providing Guardrails with permission to query it's resources. The AWS mods in Guardrails then +crawl and discover all resources in that AWS account (e.g. S3 buckets, IAM users, EC2 +instances) and add them to the Guardrails Resource Hierarchy. +
    diff --git a/docs/concepts/resources/index.md b/docs/concepts/resources/index.md new file mode 100644 index 00000000..4b4ed53c --- /dev/null +++ b/docs/concepts/resources/index.md @@ -0,0 +1,29 @@ +--- +title: Resources +sidebar_label: Resources +--- + +# Resources + +**Resources** represent objects that are managed by Guardrails. Typically, these are +mapped to resources in the cloud service, such as an AWS S3 bucket, a GCP +compute instance, or an Azure SQL database. Information about Guardrails resources +is stored in the CMDB. [Policies](policies) can be set to manage the +configuration of resources (or sets of resources). + +| Concept | Definition | +| --------------------------------------------------------- | -------------------------------------------------------------- | +| [Hierarchy](concepts/resources/hierarchy) | Information on resource hierarchy in Guardrails | +| [Smart Folders](concepts/resources/smart-folders) | The new and improved way to group resources and policies | +| [Types & Categories](concepts/resources/types-categories) | Information on properties and categorization of resource types | +| [Discovery](concepts/resources/discovery) | Guardrails and resource discovery | + +
    +
      +
    • AWS > Region
      • +
    • AWS > Account
      • +
    • AWS > S3 > Bucket
      • +
    • Azure > SQL > Database
      • +
    • GCP > Compute > Instance
      • +
    +
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zZG@qL5<$G4zdx?HbQbE3%Y+R7*-th7Pgek(EJ1j}c^wSkU0~3mfHg4huz^_d=mRXR zd%lLh3L?&b=OfSn8XPBoO+hQn3pJ`PP?QATQSQj`0iB=rGXG~Lpgy97y?x9aV*D#) z@8*Ddg4@V-d&hThxL5f$4C7-OV z98t8r)%@Q8{`W9%znrYSlg=`H3$tmf`Gx~KKb$0B8B{j{c7Ra!Ksb$~;*?C43BEG= z9AS ziX1wLpkKEmB=mi2_$ew0D*El8x~R6c@Ah481isZo#We#hk54QU%r@U0xbgM*eF+3Q ziDC-^|Ky2IpaTC1;hzd?I+G)j%G`DAtapBR^>EZ)=SnG|SPPAIs HAmD!iN&{~$ literal 0 HcmV?d00001 diff --git a/docs/concepts/resources/smart-folders.md b/docs/concepts/resources/smart-folders.md new file mode 100644 index 00000000..c77676a4 --- /dev/null +++ b/docs/concepts/resources/smart-folders.md @@ -0,0 +1,100 @@ +--- +title: Smart Folders +sidebar_label: Smart Folders +--- + +# Smart Folders + + + +**Smart Folders** are a flexible container for +[Policy settings](concepts/policies/values-settings#policy-settings). Policies +can be set on smart folders, making it easy to apply collections of policies to +resources across the [Resource Hierarchy](hierarchy). + +**Tip**: An unattached smart folder is inert, making it a safe place to practice +applying policies and ensuring that the policy Terraform is working properly. + +This example shows an example hierarchy with two smart folders created at the +Turbot level. + +``` +Turbot + Enforcement Policies (Smart Folder) + Check Policies (Smart Folder) + {Top Level Folder} (Folder) + {Cloud Account} (Cloud Account) + +``` + +## Smart Folder Attachments + +Attaching smart folders to folders and resources "activates" the policies +contained in the smart folder. Notice that the ordering of smart folder +attachment matters a great deal. When evaluating policies, Guardrails starts at the +resource then ascends the resource hierarchy looking for an applicable policy. A +check-mode policy above the same policy in enforce-mode will have no effect. The +enforce-mode policy is closer to the resource, so it wins. Remember, "the +closest policy wins". + +Along with the concept of attaching a smart folder to resources, if a smart +folder is attached to any resource, it becomes the **Parent** of that resource +and as such the smart folder _cannot be deleted until all resources have been +detached_. + +## Use Case + +The resource hierarchy provides a clear model for sharing/inheriting policy +settings and permissions across resources. For example, a policy setting +`AWS > S3 > Bucket > Approved` on `AWS 1111` will be used by all S3 buckets +beneath it in the resource hierarchy. + +But consider a situation where we wish to have specific policy settings for VPCs +based on their region (e.g. local DNS servers). VPCs are based in different +accounts, so they exist in different branches of the hierarchy: + +![](/images/docs/guardrails/smart-folders-none.png) + +In this case, the resource hierarchy is insufficient and would require +duplication of policy settings to every individual region or VPC. + +Instead, we define a smart folder `US Network` with US specific settings, and a +second smart folder `EU Network` with EU specific settings. For example: + + US Network: + AWS > VPC > DNS Servers = 1.1.1.1 + AWS > VPC > NTP Servers = 1.2.3.4 + + EU Network: + AWS > VPC > DNS Servers = 5.5.5.5 + AWS > VPC > NTP Servers = 5.6.7.8 + +Smart folders are then attached to the region resources: + + Folder A + AWS 1111 + us-east-1 (+ US Network) + eu-west-1 (+ EU Network) + AWS 2222 + us-east-1 (+ US Network) + eu-west-1 (+ EU Network) + +VPCs in each region will now have their region specific policies, while +administrators can maintain those policy settings in a single location. + +![](/images/docs/guardrails/smart-folders-updated.png) + +### Further Reading + +- [Working with Smart Folders](guides/working-with-folders/smart) - Learn how to + attach and detach a smart folder. +- [Guardrails Samples Repo Calculated Policies](https://github.com/turbot/guardrails-samples/tree/master/calculated_policies) - + Each set of policies is deployed via Terraform within a customizable Smart + folder. +- [Guardrails Samples Repo Common Control Objectives](https://github.com/turbot/guardrails-samples/tree/master/control_objectives) - + Common control objectives deployed via Terraform within a customizable Smart + folder. diff --git a/docs/concepts/resources/types-categories.md b/docs/concepts/resources/types-categories.md new file mode 100644 index 00000000..64ed5f1b --- /dev/null +++ b/docs/concepts/resources/types-categories.md @@ -0,0 +1,43 @@ +--- +title: Types & Categories +sidebar_label: Types & Categories +--- + +# Resource Types & Categories + +## Resource Types + +Every resource managed by Guardrails is an instance of a **Resource Type**. The +resource type defines the properties that belong to a resource, as well as the +[Policies](concepts/policies) that apply to it. Each +[Policy Type](concepts/policies/types-categories#policy-types) targets one or +more resource types. + +

    + +Resource types are defined in a type hierarchy. + +
    The AWS > S3 > Bucket resource type is a child of the AWS > S3 resource type. +
    + +Note that the resource type hierarchy is separate and distinct from the +[Resource Hierarchy](hierarchy). + +Resource types are defined in [Mods](mods). + +## Resource Categories + +The Guardrails Resource Type hierarchy provides grouping of resources, but in a +structured, service-oriented manner. **Resource Categories** provide an +alternate, vendor agnostic, categorization of resource types. + +
    The AWS > S3 > Bucket, Azure > Storage > Storage Account, and GCP > Storage > Bucket resource types all have a resource category of Storage > Object. +
    + +Resource categories are typically used for reporting, providing useful +aggregation and filtering of data. + +### Example - Resource Types and Categories + +![](/images/docs/guardrails/resource_types_categories-ex.png) diff --git a/docs/enterprise/FAQ/admin-permissions/index.md b/docs/enterprise/FAQ/admin-permissions/index.md new file mode 100644 index 00000000..09714c94 --- /dev/null +++ b/docs/enterprise/FAQ/admin-permissions/index.md @@ -0,0 +1,175 @@ +--- +title: "Guardrails Admin Permissions" +template: Documentation +nav: + order: 10 +--- + +# AWS Permissions for Turbot Guardrails Administrators + +## Overview + +Turbot Guardrails Administrators require fairly extensive access to the Turbot Guardrails Master AWS account. To help conform with the principle +of least-privilege, the following AWS IAM policy statement should form a starting place for enterprises to establish +their own standards. Turbot Support's expectations are that anyone identified as a "Guardrails Administrator" will be +able to fix any aspect of the application except perhaps for networking outside the Guardrails Master VPC or DNS +management. (No one wants to wait on a prod outage because of missing permissions.) + +A common point of discussion is the creation and management of IAM roles in the Guardrails Master account. Turbot Guardrails +Enterprise creates new ECS and Lambda execution roles with each new deployment. An administrator without this capability +cannot effectively manage or upgrade the Guardrails application. + +## AWS Services Used by Guardrails + +| Service | Purpose | +|--------------------------|---------------------------------------------------------------------------------------------------------------------------| +| ACM | Manage Certificates for the Guardrails ALBs | +| API Gateway | Enable event handling when the Guardrails ALB is internal-only. | +| Application-Autoscaling | Used for scaling ECS containers. | +| Billing | Monitoring of Guardrails operating costs | +| CloudFormation | Review events, resources and parameters for deployed products. Also used for minor parameter updates. | +| CloudWatch | Events, Dashboards, and Logs | +| EC2 | Guardrails uses EC2 instances for ECS. Also used for DB bastion hosts. | +| ECR | Repository for Guardrails Container Images (read-only since Guardrails doesn't create ECR images, merely consumes them.) | +| ECS | Used to run various Guardrails containers. | +| ElastiCache | Instance to cache frequently used or short lived data | +| IAM | Execution roles for Guardrails | +| KMS | Encryption Keys for DBs, S3 buckets | +| Lambda | Used for Guardrails application management and mod controls. | +| RDS | Postgresql Database for data storage | +| RDS Performance Insights | Keep track of top queries and overall DB behavior | +| Route 53 | Hosted zone with records for Guardrails Workspaces | +| S3 | Bucket for logging | +| Service Catalog | Management deployment of TEF, TED and TE. | +| SNS | Topics used for communication within the Guardrails application. | +| SQS | Event Queues used to manage task backlogs. | +| SSM Parameter Store | Used to store configuration information. Used to communicate between the TEF, TED and TE stacks. | + +## Areas of Variation + +- Guardrails creates and destroys IAM roles with the deployment of TEF, TED and TE. Manipulation of Roles and Role Policies + have been included. Blanket denial of read/write permissions on IAM roles prevents Guardrails upgrades from happening. +- In addition to TEF/TED/TE deployments, in emergency troubleshooting situations, a Guardrails bastion in the Guardrails VPC may be required to + directly access to the Guardrails DB. The ability to spin up and manage an EC2 instances is required. +- For Enterprises that use Guardrails Firehose, the ability to create and manage an IAM user is required. This has been + included in the below permissions. +- When deploying Guardrails, read calls must be made against a central Turbot-owned ECR. Permissions to create, update and + write ECR repositories are not required. +- Enterprises with restrictions on specific resources in the Guardrails Master account, should adapt the below baseline to + their needs. +- Billing read-only access is really handy, but not necessary, when questions about costs come up. + +## IAM Policy + +The following permissions are recommended for Guardrails Administrators in the Guardrails Master AWS Account + +``` + { + "Version": "2012-10-17", + "Statement": [ + { + "Sid": "VisualEditor0", + "Effect": "Allow", + "Action": [ + "acm:*", + "apigateway:*", + "application-autoscaling:*", + "aws-portal:ViewAccount", + "aws-portal:ViewBilling", + "aws-portal:ViewPaymentMethods", + "aws-portal:ViewUsage", + "cloudformation:*", + "cloudwatch:*", + "ec2:*", + "ecr:BatchCheckLayerAvailability", + "ecr:BatchGetImage", + "ecr:DescribeImages", + "ecr:DescribeImageScanFindings", + "ecr:DescribeRegistry", + "ecr:DescribeRepositories", + "ecr:GetAuthorizationToken", + "ecr:GetDownloadUrlForLayer", + "ecr:GetLifecyclePolicy", + "ecr:GetLifecyclePolicyPreview", + "ecr:GetRegistryPolicy", + "ecr:GetRepositoryPolicy", + "ecr:ListImages", + "ecr:ListTagsForResource", + "ecs:*", + "elasticache:*", + "elasticloadbalancing:*", + "events:*", + "iam:AttachRolePolicy", + "iam:AttachUserPolicy", + "iam:CreateAccessKey", + "iam:CreatePolicy", + "iam:CreateRole", + "iam:CreateUser", + "iam:DeleteAccessKey", + "iam:DeletePolicy", + "iam:DeleteRole", + "iam:DeleteRolePolicy", + "iam:DeleteUserPolicy", + "iam:DetachRolePolicy", + "iam:GetAccountSummary", + "iam:GetPolicy", + "iam:GetPolicyVersion", + "iam:GetRole", + "iam:GetRolePolicy", + "iam:GetServiceLinkedRoleDeletionStatus", + "iam:GetUser", + "iam:GetUserPolicy", + "iam:ListGroups", + "iam:ListGroupsForUser", + "iam:ListPolicies", + "iam:ListPoliciesGrantingServiceAccess", + "iam:ListPolicyTags", + "iam:ListPolicyVersions", + "iam:ListRolePolicies", + "iam:ListRoles", + "iam:ListRoleTags", + "iam:ListUserPolicies", + "iam:ListUsers", + "iam:ListUserTags" + "iam:PassRole", + "iam:PutRolePolicy", + "iam:PutUserPolicy", + "iam:SimulateCustomPolicy", + "iam:SimulatePrincipalPolicy", + "iam:TagInstanceProfile", + "iam:TagMFADevice", + "iam:TagOpenIDConnectProvider", + "iam:TagPolicy", + "iam:TagRole", + "iam:TagSAMLProvider", + "iam:TagServerCertificate", + "iam:TagUser", + "iam:UntagInstanceProfile", + "iam:UntagMFADevice", + "iam:UntagOpenIDConnectProvider", + "iam:UntagPolicy", + "iam:UntagRole", + "iam:UntagSAMLProvider", + "iam:UntagServerCertificate", + "iam:UntagUser", + "iam:UpdateAccessKey", + "iam:UpdateRole", + "iam:UpdateUser", + "kms:*", + "lambda:*", + "logs:*", + "pi:*", + "rds:*", + "rds-db:*", + "route53:*", + "s3:*", + "servicecatalog:*", + "sns:*", + "sqs:*", + "ssm:*", + ], + "Resource": "*" + } + ] +} +``` \ No newline at end of file diff --git a/docs/enterprise/FAQ/cost-estimate/index.md b/docs/enterprise/FAQ/cost-estimate/index.md new file mode 100644 index 00000000..0248c962 --- /dev/null +++ b/docs/enterprise/FAQ/cost-estimate/index.md @@ -0,0 +1,70 @@ +--- +title: "AWS Usage Estimate" +template: Documentation +nav: + order: 20 +--- + +# Turbot Guardrails Enterprise AWS Usage Estimate + +Turbot Guardrails Enterprise runs a multitude of AWS services, including RDS for PostgreSQL, SQS, S3, and EC2. While +each environment is different with respect to amount of controls, policies, and resources, there is an expected baseline +for costs within the AWS master account in US East 1. + +[Turbot Guardrails Enterprise AWS Usage Cost Estimate](https://calculator.aws/#/estimate?id=b3a10e1d9515faaf10a1a8f7cab73a6fe0249b44) +using the AWS Pricing Calculator: + +## Amazon RDS for PostgreSQL: + +* Quantity: 1 +* Storage Volume: General Purpose SSD (gp2) +* Storage amount: 500 GB per month +* Instance size: db.m5.4xlarge +* Multi-AZ enabled +* Total monthly cost: $2,194.04 + +## AWS Lambda: + +* Number of requests per month: 50,000,000 +* Total monthly cost: $510.00 + +## AWS Elastic Compute (EC2, deployed via ECS): + +* Operating system: Linux +* Quantity: 5 +* Storage type: General Purpose SSD (gp2) +* Storage amount: 30 GB +* Instance type: t3.large +* Total monthly cost: $318.68 + +## Amazon CloudWatch: + +* Total monthly cost: $179.75 + +## Amazon Key Management Service (KMS): + +* Number of customer managed Customer Master Keys (CMK): 3 +* Number symmetric requests: 10,000,000 +* Total monthly cost: $33.00 + +## Amazon Simple Storage Service (S3): + +* S3 Standard Storage: 1 GB per month +* Total monthly cost: $22.02 + +## Amazon Data Transfer: + +* Intra-region: 1 TB per month +* Total monthly cost: $20.48 + +## Amazon Route 53: + +* Hosted Zones: 1 +* Total monthly cost: $8.00 + +## Amazon Simple Queue Service (SQS): + +* Standard queue requests: 15 million per month +* Total monthly cost: $6.00 + +## Total monthly cost: $3,296.97 diff --git a/docs/enterprise/FAQ/disaster-recovery/index.md b/docs/enterprise/FAQ/disaster-recovery/index.md new file mode 100644 index 00000000..ba45bede --- /dev/null +++ b/docs/enterprise/FAQ/disaster-recovery/index.md @@ -0,0 +1,35 @@ +--- +title: "Guardrails DR Considerations" +template: Documentation +nav: + order: 70 +--- + +# Turbot Guardrails Disaster Recovery Information + +Most Guardrails application resources are **stateless**, such as Lambda functions, meaning they +can be rebuilt in any region on the fly. See our +[Enterprise Installation](enterprise/installation/) guide on how to install +Guardrails. However, RDS databases are not stateless. Guardrails uses standard AWS +product features and procedures to store, backup, and restore RDS instances. + +AWS publishes a +[best practice](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_BestPractices.html) +guide with basic operational guidelines, as well as documentation for +[Backing Up and Restoring an Amazon RDS DB Instance](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_CommonTasks.BackupRestore.html). + +By default, RDS instances have automated backup enabled, backing up once daily +for 14 days. Manual snapshots are not subject to the backup retention period - +they will not expire. In Multi-AZ configurations, AWS manages the replication +and fail-over of the database. During certain types of planned maintenance, or in +the unlikely event of DB instance failure or Availability Zone failure, Amazon +RDS will automatically fail over to the standby so that you can resume database +writes and reads as soon as the standby is promoted. + +In the event of the accidental deletion of the TED stack, a new stack can be +created with the added specification of a DB Snapshot and the KMS key used (if +not using the AWS default). + +Turbot Support is happy to consult with Enterprise customers to help +determine a strategy to manage these scenarios. Contact us at +[help@turbot.com](mailto:help@turbot.com). diff --git a/docs/enterprise/FAQ/domain-update/index.md b/docs/enterprise/FAQ/domain-update/index.md new file mode 100644 index 00000000..fde42e65 --- /dev/null +++ b/docs/enterprise/FAQ/domain-update/index.md @@ -0,0 +1,100 @@ +--- +title: "Workspace URL Change" +template: Documentation +nav: + order: 80 +--- + +# Updating Your Turbot Guardrails Installation Domain + +In some situations, you may be required to change the URL for your workspace due +to a domain name change, or a migration from internal DNS to Route 53. This +guide outlines the full process of moving to a new URL/domain. + +## Limitations +Given a complete workspace URL like `https://console.prod.turbot.customer.com`, an enterprise customer would be able to +change the installation domain of `prod.turbot.customer.com` to something else. The `console` portion cannot be +changed since it is also the name of the Postgresql table schema that stores the workspace data. If a workspace +absolutely requires a new name, then create a new workspace with the desired name. Migrate all cloud accounts from +the old workspace to the new. + + +## Prerequisites + +1. Create a hosted zone for the new domain. +2. Create a new matching TLS certificate and upload it to AWS Certificate + Manager. Your certificate names will need to include: + - Domain name + - Workspace URL (e.g. `{workspace_name}.{domain}`) + - API Gateway (e.g. `gateway.{domain}`) -- only if applicable + +## Phase 1: + +1. Navigate to CloudFormation. +2. Select the workspace stack and select "Update". +3. When prompted, choose "Replace Workspace Template" and upload the latest + [workspace template](enterprise/installation/workspace-manager). +4. Do not change any values from your current workspace template. +5. Apply the stack and wait for it to finish. + +## Phase 2: + +1. Navigate to Service Catalog > Provisioned Products. +2. Select the Turbot Guardrails Enterprise Foundation (TEF) product and update using the + same version as is currently deployed. +3. Change the installation domain to the new domain. +4. Change the certificate ARN to match the new certificate. Update and wait for + it to complete. + +#### Verification + +- Verify that the SSM parameter `/turbot/enterprise/installation_domain` is set + to the new domain in Systems Manager. + +## Phase 3: + +1. Navigate to Service Catalog > Provisioned Products. +2. Open the Turbot Guardrails Enterprise (TE) product. +3. Click Actions > Update. +4. Scroll to the bottom and change the Parameter Deployment Trigger to the + opposite of its current value. This will force the SSM parameters to be + reevaluated. +5. Run the update and wait for it to complete. + +#### Verification + +- Verify that a CNAME record was created for + `turbot-$version.your.new.domain.com` that points to the ALB in your new + hosted zone. +- Verify that a CNAME record was created for + `workspace_name.your.new.domain.com` that points to + `turbot-$version.your.new.domain.com` in your new hosted zone. +- Verify that a new SSM parameter + `/turbot/tenant/workspace_name.your.new.domain.com` is created in Systems + Manager. +- Test connectivity to the workspace. + +
    + Note: If you are not using Route53 for DNS management, you will need to create/update the above CNAME records manually. +
    + +# If using API gateway: + +- Complete the Prerequisites. +- Prior to Phase 2: + 1. Navigate to API Gateway in AWS. Open your API Gateway and delete any + custom domain names that exist. + 2. Run an update to the TEF stack in Service Catalog, deprovisioning the API + gateway by setting the `Create public API gateway` parameter to + `Disabled`. + 3. Run the update with no other changes. + 4. Verify that all events completed successfully via the linked + Cloudformation stack. +- Complete Phase 2, making sure to set the API Gateway parameter to Enabled to + provision the new API gateway. +- Complete Phase 3. +- Open your Guardrails workspace and update the policy + `Turbot > Workspace > Gateway Domain Name` with the value from the API Gateway + Invoke URL in AWS. 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These pauses are most often used when +making changes to a Guardrails database(s) to avoid lost events. + +The central hub of the Guardrails application are the Worker Lambdas, identified with the `_worker_*` suffixes. When the triggers for +these Lambdas are disabled, event processing halts. + +This document will assume the resource prefix is `turbot_`. Your environment may use a different resource prefix. + +## Implications of Paused Event Processing + +When event processing is disabled, Guardrails will be unable to run controls, apply policy settings nor make remediations in +managed cloud accounts. After processing has restarted, the backlog of changes will be processed. How long will depend on +Guardrails' provisioned throughput capacity and the amount of environment change during the pause. The Guardrails console will +still be available during the outage except for the periods where the database is unresponsive. + +## Disable Event Processing + +Disabling the SQS triggers for the TE worker Lambdas are sufficient to pause processing. (No changes should be made to +mod lambdas.) In environments with multiple TE deployments, event processing must be halted for all TE versions using +the concerned hive/database. (Get a list of which TEs are associated with which databases by examining the TE and Hive +parameters in all Workspace CloudFormation templates.) + +Navigate to AWS Lambda service and search for the functions with suffix `_worker`, `_worker_priority` +and `_worker_retry`. No changes are required to any other Guardrails deployed Lambdas. + +Below are some examples of such Lambda functions: + +* `turbot_5_39_12_worker_priority` +* `turbot_5_39_12_worker` +* `turbot_5_39_12_worker_retry` + +![](/images/docs/guardrails/function_overview.png) + +* Navigate to each of these Lambda functions and click on the "Configuration" tab. +* Select "Triggers" sub-tab and look for the trigger corresponding to the function. +* Choose the trigger by clicking on the checkbox and click on Edit. +* In the "Trigger configuration" page, uncheck the "Activate trigger" option to push the events to backlog queue. + +![](/images/docs/guardrails/disable-trigger.png) + +## Enable Event Processing + +As soon as the database changes are done, navigate to Lambda service and enable the triggers for the functions which +were disabled earlier. If the changes are related to database storage, the database can be in "storage-optimization" +state, you can still enable the lambda triggers. + +* Navigate to each of these Lambda functions and click on the "Configuration" tab. +* Select "Triggers" sub-tab. Look for the trigger corresponding to the function. +* Choose the trigger by clicking on the checkbox and click on Edit. +* In the "Trigger configuration" page, check the "Activate trigger" option to enable the events. + +![](/images/docs/guardrails/enable-trigger.png) + +### Need help? + +Please reach out to [Turbot Support](mailto:support@turbot.com) if there are questions or issues. diff --git a/docs/enterprise/FAQ/redis-caching/index.md b/docs/enterprise/FAQ/redis-caching/index.md new file mode 100644 index 00000000..6f31f7b4 --- /dev/null +++ b/docs/enterprise/FAQ/redis-caching/index.md @@ -0,0 +1,118 @@ +--- +title: "Redis Caching" +template: Documentation +nav: + order: 60 +--- + +# Redis Caching + +## What is Amazon ElastiCache? + +Amazon ElastiCache is a web service that makes it easy to set up, manage, and +scale a distributed in-memory data store or cache environment in the cloud. It +provides a high-performance, scalable, and cost-effective caching solution. At +the same time, it helps remove the complexity associated with deploying and +managing a distributed cache environment. + +## Why use Caching? + +Caching reduces database load and IOPS considerably while also improving process +and query performance. Long term data is not stored in Redis, for example, +process data and logs are archived to S3. + +## What information does Guardrails Cache? + +Guardrails uses AWS ElastiCache for Redis, in order to store short term data (e.g. +process data) and caching. + +## How do I start Caching? + +- Though ElastiCache for Redis is now fully supported from TE + [v5.35.0](releases/te#v5350-2021-01-22) which requires TEF v1.31.0 and TED v1.9.1. + +- Upgrading TEF, TED and TE will automatically enable this feature unless it's + deliberately disabled in both TEF and TED parameters. + +- Note that this is currently optional as of TE 5.35.x but Redis + may become a requirement in some future release. + +## What Redis mode does Guardrails use? + +AWS ElastiCache for Redis is available in two modes. + +1. Single Node (Cluster Mode Disabled) +2. Multi-Node (Cluster Mode Enabled) + +As of TED 1.17.x, Guardrails defaults Single Node configuration though Multi-Node clusters are supported too. + +## Are the connections encrypted? + +Yes, both Encryption-at-transit and Encryption-at-rest are enabled by default. +The same Hive KMS Key is used for encrypting Redis as well. However, the option +to use customer managed CMK for encryption at rest is not available in AWS +GovCloud (us-gov-east-1 and us-gov-west-1) regions. Please click +[here](https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/at-rest-encryption.html#at-rest-encryption-constraints) +for more details. + +## How is the authentication managed? + +Guardrails makes use of the Role-Based Access Control (RBAC) for authenticating +users. For more information about RBAC please click +[here](https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/Clusters.RBAC.html). + +## Is my ElastiCache undersized or oversized? + +It is recommended that you use choose a node type with: Memory needed + 25% +reserved memory (for Redis) + some room for growth (optional 10%). With that +being said, the Guardrails TED Dashboard on AWS CloudWatch captures metrics related +to ElastiCache which helps you understand about the ElastiCache usage. + +## How can I scale Redis-based ElastiCache clusters? + +From TED v1.17.x vertical scaling is supported on Redis-based ElasticCache. +Below are the steps to vertically scale up and scale down the node type of the +Redis-based ElastiCache Cluster. + +## Steps to perform vertical scaling + +Please be cautioned that this needs a minimal downtime. The steps remain same +for scaling up and down. + +- Navigate to the Guardrails Master Account, open the AWS Console and navigate to + the Service Catalog service. +- Select the hamburger menu in the top left and click on **Provisioned + products** list. +- There should be three provisioned products: a TEF product, a TED product, and + a TE product. Different organizations may have different naming conventions. +- Select the TED product. If it is not obvious via the name of the product, + selecting a product itself will open the details page. The product type will + be listed here. +- While looking at the Turbot Guardrails Enterprise Database product, select Actions and + then click Update. +- Select the desired version of TED and scroll down to the label **Cache**. +- Under the Cache Node Type drop down menu, select the desired cache node type + and click on Update. +- This may take 15-20 minutes and while the ElastiCache cluster is being + modified, the cache may be unavailable. +- After the update is complete, verify that the `VIEW LOG` on a Control Page is + not graded out, and the ElastiCache Cluster is in the available status on the + master AWS account. + +**WARNING**: Whenever the redis cache cluster is resized, the user-group +defaults to Redis Auth Default User which needs to be manually changed to the +hive user-group. + +- Select the cluster and click on the Actions drop down button. +- Click on Modify. +- Under **Access Control Option** drop down, change from "Redis AUTH Default + User" to "User Group Access Control List" +- Select the user-group of the respective hive for **User Group Access Control + List**. The user-group has a naming convention of <prefix>-<hive> + +## How can I connect to Redis Cluster? + +Guardrails Bastion host comes with all the pre-requisites installed in order to +connect to RDS/Redis. Please refer to the +[README](https://github.com/turbot/guardrails-samples/tree/master/installation/turbot_bastion_host) +for instructions and usage. diff --git a/docs/enterprise/FAQ/workspace-usage.png b/docs/enterprise/FAQ/workspace-usage.png new file mode 100644 index 0000000000000000000000000000000000000000..a6a3541421792228ca18f91e447b0cbcd53f8fee GIT binary patch literal 11904 zcmch7cUV*JvThUw3&jSAfHVQ6D!n5jy-JlDQ36sz3!w)T6{JY-ReC29NT>l7r4xD$ zMSgSw1PLJ!+Ku}>_ny0-z0cj}-1bMF^{nz`&CHr_=ACyY!cbp>?#i7j004kaOY^A_ z0C3(505}J@L`}IOEtL74aySPu(s%->#;~nZPA)jA=&1kzHL+KZ?JiQzFMDWOKmY*x z_CLRKo$jUf0DuUi)>9P|KijR@tA4k}PR@S22MnRwxVLiey*V$HA42t1M1c9(;FbFm zp&!kjx;Z~nsjCXTwAQBf_yYLDB_>hH&mWOpYJ;EePnTZud)tLH)#SY&_ug{He>z_| z^Gwzevx(95skP_=(agbD)A^4S#pUa5W*JudHj9%5&jSE&1`ktCu2PP1TwUh?fcLjl z=m7xE!b=pz09u(x3%|u0#P?AvqlAOCF3Ph1MGrd^b(;L8;f1jD6qq{wJzr!~QR_;v ziN~fC_^3gj@U!g<@^n9$Es5iFfb=S?u`tXGYG5r8CPR78;t;9L7a@Uh<)mqoakV;5 zxZ)KclYEULh+&|2+R;Ef+;zFLpCb3amYDlrC^=>sCm(bW*9Tkj9Y$L@I{Et;uTQon zN3%l;TxY&uL?|YDV?U}Lhpl;)Ny|29tgncS5VA=T#hzITvCd)nRKsmVNd{-1F8lE# zhIx6G`WAYNM#m|VnLb-o(I@>_ kjH0WZaf~Oekm$|Qg^j@2^NU8EOox?WR+6ID= zV2VvH!O?-FwBwsmZWDwGoli84CCmyBUb&ql*S#L> zKS6)@IalAhWj*e2d3hN{oE-IwvqEhS3|Ad3qayW4!`VKT#?`5mubC%(R--Uw)zZnl zGIOm2OFXWtlNbrEbXMqsole=#dpIj36DR*Tf?98i?CvI{R~Md1@BZ^=Zbn;^EpZp; z5DYE*&1nv|RXi&73TNOz#cp7VAAI_w=&>|=l1M6U;I$A>YSJWiC*^X{VG@ID5sZ^m zww&Q88L3N_or^Js8LJW~W+}99jF#w)j${67X5q#D&+7KPalA!+&Ng)@|(JHl3rCnUvFE})d_!G-<=3n{+JpYN4aiBJsJ(PWv zk%Xu6w`;K7hc&+k0q47#8rClW4C%a|Te-H+@Y={z)NmUvOt;AopqR*Iej!wVF1_`X zESO-^iT2te>)r5o`EbimxtqkK^EUGGMZt-~??1{F;;)}zAlf(8$z9ttQoYsrCz!h5 z4BU&Bz3Jb6arQ1(dvc5Sd-;2T!od53TyBHLilB}#*zV|O-LZVC49m01*rl7kCpu%T zWTDjG7PvyVeA^mN`V=&ScK1Wc4gUqZc;0x>elOVqeb4=~vgUf+v=)A`W6euPUA_4Y z@f3Q;H%Flji>dFtLtCw(O7jrCy{1&Y_}a};ph(9{&GtY60Sv&}>48UbH4daUQky!k!Z)C|+qDes)yF>hMLt*UK38CsoyXqo40Ec(sSkzi53~ zD0Y=uforzO#@m3KO$$rd9%n}-e%21 zLa(Vjj@VgoCu2&z1K_Xyp{lM$;~4EGpu3ko27I|B-A?BzF1^zIS@$SEm8sWl{Q*oA zlhlR%Jo~({({``QeK3#d>D;r;QHQg=L&7F-$=XjAo*5ma#izk!(yLe+YWJ;Q?Cd$i1%SsB zY%9#gUWV8oN*8Z8zR~i^wBk2sN!!c9KvK?%pk}DA`)j!${b{FG>*FV4Sff--V(Z38 z>x*W(i%qL~A3|HDf%hFtAJ_HxfRne$j|+8-onA&l5#^lM5Y~@E^X58OSQt|z_C;8( zU-oRxX^Jj(KB@o(g~!dL)aS zysGSdMowKe8YD7!)k@O|u=GRmOEie)y~*>2i7AR|IU9*DO3gkzRMd5jwTruwvfLc0 z7h5)^42j9+Ey#jgw*%Iv*JrJU%=R_L3$^km8f?(%jV#lrg6_#X*Jv|`TYer zq1}e(+zU15v|)PI5w|L>g>A?-zxHmV=S|%6MxJ|E`pbbu!VT%2Eh*mNf%Er@Wfwqi z(DJwZXsQ-|6i8`iJ}#y~X|88F$5z@NCzQk-Ai-fJ*A7PCW)z z=4h9#N@yb$MVcVvx)qn!Mf%{_g%8=o$sP#wUIFEOqeRpYTXk-+9Oh?@+ZE~-q zyMHpv8?s%ke<1C#_3P0?c;@yA?cI0cip%VLGyu-aQMpzdS3O0f`_>Qh4$1MH?9(&d zfp5q-4I}P8khd9^9z&I|Z(xOtwpz!4F54&{f8!&>8jT4`DN`5m|ya8w6#UuP3A3001^Bn4|NW=p|nC?*4oVEcMOjwp(gLVuTu;z~_y2biCjO&h6$pk;h#QB$T(?^HD7n%?u6WWiF;TV2w&-GVjNOu`&K7!r z@a>zHe>>l#lg%t2Vyb*5>4iBxg!8-RNZKx`%sMdF%;0`A(e4I|+PF;3i3VT*08Nn7 zvX(atJiT92r-0)}X$xbOPn+vppea@QLgcG&<*PPDaf*3#Dr9|gSmM*XD_^b8r~##S zvSCJCz#rJyBwRd|^ZP*bFP2Wf#0vnxgZG@_i+wa+zz?}oh>5G@)?;SCn;o961(^{O z%Z=QrNNYkd|7yl}8xr;3ZpAI$`2!qf8r1)wHObKb8BG2YXqIdeCx2Lo?}_IDPW?gM zl3VjWDg8vcgH4BfAF>Bva&{N!b#Ct9JR92Pt*Y~@x#{) zdM^-=E#Hyy!p~vrIStgx)uQQi!S)mwN&g4rYSPVYQV#ze(*6@E{uK)Tzq2ISta`HZ zGK?^P)}!1iBXo8;aGh}bk4~%Dd2&k7Ss=g830XNQv6aA%y+bjKpzOhi%N`}iJ0VN* z^QWjkxbd;x!MuBGJVNyJ!MyUJeYfk*E6SszgBxw9u=jt1%R1gG+GoFGb*ZCx%Q#Eq z@s~U)Z$N4|!u_a9|G%2SX*m*>W%%s3k}T4$sVZhRCR-kK(8apkE812k{2Sz$E39*N z%&(=RQ%i~D0RFH6h9oVskq%U3`3NVeYeu7g-l}uv<*Av&*bnAooeu;mVM&ePGCdGtvsh}FyHj7fD$YorKUzC=o?F;4$X<|AfpC`* zIZIS$c5v=VpIGO`V_j?(I6$jwPo`?d(wQ7*1#NKmF2U}RR%f_-dt5DeoL{k0T&a3A zIPT~eB1;_YaF9W&9?9M21B=^kyS?HN1iNQ(Gb`3wN@4F%N-3cR7h-K&50*JcxMWH! 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This type of infrastructure sharing provides safe reuse +(e.g. VPC, EC2 instances) while supporting isolation of data. + +Collectives should be configured with 1 to 3 geographically and politically +similar regions, allowing free and fast movement of data. + +Collectives are deployed and managed via the +[Turbot Guardrails Enterprise Foundation (TEF)](enterprise/installation/tef-installation) +product in the AWS Service Catalog. At Turbot, collectives are typically named +after a famous bridge or tunnel (connection) in the area. + +

    + +Most Turbot Guardrails Enterprise customers require only a single collective. + +## Hives + +A **Hive** defines the physical data storage and caching resources used in +Turbot Guardrails Enterprise. + +A hive may be shared by multiple workspaces, but a single cannot span multiple +hives. Within each hive (physical database), workspaces are separated into +different logical schemas to support data isolation and movement between hives +if required. + +Hives are deployed and managed via the +[Turbot Guardrails Enterprise Database (TED)](<(/docs/enterprise/installation/ted-installation)>) +product in the AWS Service Catalog. At Turbot, hives are named after a famous +scientist in the area(e.g. newton, edison -- as in “hive mind”.) + +Multiple hives may be used to create physical data separation (e.g. isolate +critical tenants) and for scalability through physical sharding, but most Turbot +Enterprise customers will start with a single hive. + +## Versions + +Each Collective has zero or more **Versions** of Turbot installed. Each version +is installed separately and immutable. For example, versions 5.1.0, 5.1.1 and +5.2.0 may all be installed and in use simultaneously. All changes are done +through installation of new versions - existing versions are never updated. + +Each Version in the Collective may be used for zero or more Tenants at any time. + +
    +
      +
    1. 1-Nov: v5.1.0 is installed.
      2. +
    2. 1-Nov: Tenant A is upgraded to use v5.1.0.
      3. +
    3. 2-Nov: Tenants B, C are upgraded to use v5.1.0.
      4. +
    4. 5-Nov: All Tenants D-Z are upgraded to use v5.1.0.
      5. +
    5. 8-Nov: v5.0.0, with zero remaining tenants, is uninstalled.
      6. +
    +
    + +Versions define the majority of their own infrastructure in a standalone, +reproducible manner. For example, load balancers, IAM roles, Lambda functions +and container instances are all defined separately in each version. This +separation improves reproducibility and accuracy while reducing the risk of +installations and upgrades. + +Versions are deployed and managed via the +[Turbot Guardrails Enterprise (TE)](enterprise/installation/te-installation) product in the +AWS Service Catalog. Versions are immutable – as Turbot releases new versions, +you should install them via a new instance of the product, not an update to the +previous version. + +## Workspaces + +A **Workspace** is an independent tenant of turbot, with its own version and its +own schema (logical shard) in a hive. Each Workspace has its own Turbot root, +its own set of mods, and its own web console endpoint. + +Workspaces may be hosted in the same collective, and share the same hive, but +are independent of each other. Each workspace can be upgraded or downgraded +independently, and no data is shared across workspaces. + +Workspaces are deployed and managed using +[Turbot Workspace Manager](enterprise/installation/workspace-manager), +implemented as a CloudFormation custom resource. + +Customers may have multiple workspaces. For instance, you may wish to separate a +development instance of Turbot Guardrails Enterprise from the production instance, in order +to test new Turbot versions, modules, etc. + +
    + Workspaces per lifecycle phase for the brooklyn collective for vandelay.com : +
      +
    • dev.brooklyn.vandelay.com
      • +
    • qa.brooklyn.vandelay.com
      • +
    • prod.brooklyn.vandelay.com
      • +
    +
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mode 100644 index 00000000..4baf13b6 --- /dev/null +++ b/docs/enterprise/index.md @@ -0,0 +1,16 @@ +--- +title: Enterprise +--- + +# Turbot Guardrails Enterprise + +![Turbot Guardrails High-Level Physical Architecture](/images/docs/guardrails/physical-architecture.png) + +Turbot Guardrails Enterprise is a standalone installation of Turbot, designed to run inside your organization's network and infrastructure. It provides the full capabilities of Turbot, but with full control over the network architecture, upgrade process, security configuration and environment access. + +Guardrails Enterprise is a cloud-native application, built from the ground up on Amazon Web Services (AWS). + +The Guardrails Enterprise installation is highly customizable, allowing you to deploy Guardrails in the way that most appropriately balances your availability, performance, security, and cost requirements. +- Guardrails can be installed in up to 3 availability zones per region. +- Guardrails was designed as a multi-tenant application, providing logical and physical separation of workspaces. +- Guardrails leverages AWS native services, containers, and serverless compute to minimize costs and administrative overhead. diff --git a/docs/enterprise/installation/index.md b/docs/enterprise/installation/index.md new file mode 100644 index 00000000..d6cc2e93 --- /dev/null +++ b/docs/enterprise/installation/index.md @@ -0,0 +1,72 @@ +--- +title: Installation +sidebar_label: Installation +--- + +# Getting Started with Turbot Guardrails Enterprise + +
    +Turbot Guardrails Enterprise is a cloud-native application, built from the ground up on Amazon Web Services (AWS). A dedicated AWS account is recommended for installing Turbot Guardrails Enterprise. +
    + +## Installation Overview + +At a high level, the installation process involves 3 stages: + +1. Installing Turbot Guardrails Enterprise via Turbot Portfolio Manager and AWS Service + Catalog: + + - Install the Collective via the + [Turbot Guardrails Enterprise Foundation](enterprise/installation/tef-installation) + product + - Install the Hive via the + [Turbot Guardrails Enterprise Database product](enterprise/installation/ted-installation) + - Install a version via the + [Turbot Guardrails Enterprise product](enterprise/installation/te-installation) + +2. Creating Workspaces via the + [Turbot Guardrails Workspace Manager](enterprise/installation/workspace-manager) + CloudFormation Custom Resource. + +3. Performing one-time + [post-installation](enterprise/installation/post-installation) steps + +### Prerequisite – Importing a Portfolio + +Turbot Guardrails Products are published through +[AWS Service Catalog](https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html). + +Portfolios provide a collection of products that can be installed and configured +via the Service Catalog. Turbot Guardrails portfolios are only available to customers after +being shared / given permission – Contact your Turbot Guardrails Solutions Engineer if you +require permission to a Turbot Guardrails Portfolio. + +### To import the portfolio(s) + +1. In your Turbot Guardrails master account, import the portfolio into each region that you + will install into. [Portfolio links](#portfolios) are provided below. +2. After importing the portfolio, you must grant access to the portfolio in + Service Catalog so that users may deploy the products. +3. Once the portfolio is imported, and you have been granted access, you can + provision Turbot products from Service Catalog Product List. + +--- + +### Turbot Guardrails Portfolio + +| Region | Portfolio | +| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- | +| ap-south-1 | [port-neo73tqls24he](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=ap-south-1#portfolios/import?id=port-neo73tqls24he) | +| ap-southeast-1 | [port-i4uxfyvlszine](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=ap-southeast-1#portfolios/import?id=port-i4uxfyvlszine) | +| ap-southeast-2 | [port-mqrb5j263sbnu](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=ap-southeast-2#portfolios/import?id=port-mqrb5j263sbnu) | +| ca-central-1 | [port-oqi3phgemnvho](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=ca-central-1#portfolios/import?id=port-oqi3phgemnvho) | +| eu-central-1 | [port-gsp6rwefdjhjk](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=ca-central-2#portfolios/import?id=port-gsp6rwefdjhjk) | +| eu-west-1 | [port-r2f6tscrxgoz2](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=eu-west-1#portfolios/import?id=port-r2f6tscrxgoz2) | +| eu-west-2 | [port-c3xxvwv4dlvtm](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=eu-west-2#portfolios/import?id=port-c3xxvwv4dlvtm) | +| eu-west-3 | [port-52avvwkyky5kk](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=eu-west-3#portfolios/import?id=port-52avvwkyky5kk) | +| sa-east-1 | [port-ssp6vdgvkgghy](https://sa-east-1.console.aws.amazon.com/servicecatalog/home?region=sa-east-1#/portfolios/import?id=port-ssp6vdgvkgghy) | +| us-east-1 | [port-3vneddg6vujhq](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=us-east-1#portfolios/import?id=port-3vneddg6vujhq) | +| us-east-2 | [port-weusplgp6bmua](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=us-east-2#portfolios/import?id=port-weusplgp6bmua) | +| us-west-1 | [port-lot26rdlx4iry](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=us-west-1#portfolios/import?id=port-lot26rdlx4iry) | +| us-west-2 | [port-u4rbevxpzwj3m](https://console.aws.amazon.com/servicecatalog/home?isSceuc=false®ion=us-west-2#portfolios/import?id=port-u4rbevxpzwj3m) | +| us-gov-west-1 | [port-akp7iklcswqba](https://console.amazonaws-us-gov.com/servicecatalog/home?region=us-gov-west-1/portfolios/import?id=port-akp7iklcswqba) | diff --git a/docs/enterprise/installation/post-installation/index.md b/docs/enterprise/installation/post-installation/index.md new file mode 100644 index 00000000..b99a2571 --- /dev/null +++ b/docs/enterprise/installation/post-installation/index.md @@ -0,0 +1,82 @@ +--- +title: Post Installation +sidebar_label: Post Installation +--- + +# Post Installation Steps + +## Set Workspace Policies + +If you are using the **Public Api Gateway** option, you should ensure that +gateway is set in the **Turbot > Workspace Gateway Domain** name policy to your +gateway DNS name. You can find the value in the **ApiGatewayEventsURL** output +of the TEF stack. The policy should be set to the DNS name only, without the +protocol or path. This is usually `gateway.{installation domain}` – for example +if your installation domain is “turbot.mycompany.com”, the gateway would be +“gateway.turbot.mycompany.com”. + +
    If you are using the API Gateway option, you must set the Turbot > Workspace Gateway Domain policy! If you are NOT using a gateway (the default configuration), you should leave the policy blank! +
    + +## Update DNS Records + +If you chose not use Route53 to manage the DNS during the TEF, TE, or Workspace +Manager Installation, you will need to create/update the DNS records yourself. +If you have opted to use Route53-managed DNS during the installation (the +default option), Turbot will manage the records for you - you can ignore this +section. + +#### API Gateway DNS + +If you chose to create public API gateway, but did not choose to use Route53 to +manage DNS, then you must register a DNS alias for the api gateway in your DNS +server. You should create a record for the gateway DNS name (from the +`ApiGatewayEventsURL` in the TEF stack output - `gateway.{installation domain}`) +to point to the regional endpoint, listed in the `ApiGatewayRegionalDomainName` +stack output variable. + +#### Workspace DNS + +If you chose not to enable **Manage DNS Records in Route 53**, then you must +manually create (or modify) a CNAME record for your workspace to point to the +load balancer for the new version after running workspace manager. You can +obtain the version-specific load balancer DNS name from the `LoadBalancerDNS` +variable in the TE output. + +
    If you are managing your own DNS, you must update the dns alias for your workspace every time you update the workspace with a new version (after running Workspace Manager)! +
    + +## Update Turbot Mods + +After installing a new workspace, you should always update the `turbot` and +`turbot-iam` mods to the latest version. These core mods will already be +installed into your blank workspace, but they must be updated when the workspace +is first created: + +1. **turbot** +2. **turbot-iam** + +Note that the `turbot-iam` mod depends on `turbot`, so they should be installed +in order - `turbot` first, then `turbot-iam`. The **turbot** and **turbot-iam** +mods cannot be removed. + +A guide for installing additional mods can be found +[here](guides/managing-mods/install-mods). + +## Importing AWS, GCP, and Azure accounts into Turbot + +Turbot supports importing an account from any of the three major cloud +providers. More information about required policy settings and mod installations +can be found in the [Integrations](integrations). + +## Setting up Single Sign On access + +Customers are encouraged to [setup SSO](guides/directories) access into their +Turbot workspaces as soon as possible. In case of break-glass or workspace +bootstrapping, customers can use the default Turbot Local directory. Be aware +that Turbot Local user passwords expire after a default of 90 days. Customers +should develop a plan for how they will regain access should the password +expire. + +Credentials, password and API keys, for the `admin@turbot.io` user should be +securely stored. diff --git a/docs/enterprise/installation/pre-installation/external-role/index.md b/docs/enterprise/installation/pre-installation/external-role/index.md new file mode 100644 index 00000000..2422a453 --- /dev/null +++ b/docs/enterprise/installation/pre-installation/external-role/index.md @@ -0,0 +1,107 @@ +--- +title: Custom Roles +sidebar_label: Custom Roles +--- + +# Using External IAM Roles to Install Turbot + +Organizations with strict role requirements will be unable to use the +pre-defined roles in the TEF, TED, and TE stacks. This guide provides +instructions for creating roles using AWS CloudFormation templates. + +## Create Turbot Parameters Custom Resource IAM Role + +Start by creating the role required for Turbot Parameters. The link below +contains the necessary CloudFormation template: + +-     Turbot + Parameters Custom IAM Roles YAML + +Refer to +AWS +Documentation for how to create a new CloudFormation stack. + +Once the template is downloaded, create a new CloudFormation stack in the AWS +account designated as the install account. Label the stack to make it +recognizable, such as **Turbot Parameter IAM Role**. + +## Create Turbot Guardrails Enterprise Foundation (TEF) Customer IAM Roles + +Again, Turbot provides a CloudFormation template that can be used to deploy +roles required for a successful installation. Both the above Turbot Guardrails Parameters +Custom Resource IAM role and the TEF customer IAM role **MUST BE CREATED PRIOR +TO BEGINNING THE TURBOT INSTALL!** Follow the below link for the TEF Custom IAM +Roles CloudFormation template: + +- TEF + Custom IAM Roles YAML + +Refer to +AWS +Documentation for how to create a new CloudFormation stack. + +Once the template is downloaded, create a new CloudFormation stack in the AWS +account designated as the install account. Label the stack to make it +recognizable, such as **TEF IAM Role**. + +## Install TEF Stack with Custom Options + +Install TEF using the +[Turbot Guardrails Enterprise Foundation Installation Guide](enterprise/installation/tef-installation) +with the following custom options: + +- **Turbot Parameter Role**: The ARN of the Turbot Parameters Custom Resource + IAM Roles +- **Role Creation Scheme**: `None` + +## Install Turbot Guardrails Enterprise Database (TED) Stack + +No custom options are necessary for the TED stack. Follow the +[Turbot Guardrails Enterprise Database Installation Guide](enterprise/installation/ted-installation) +to complete this step. + +## Create IAM Roles and Policies For Turbot Guardrails Enterprise (TE) Stack + +Use the below provided CloudFormation template to create the required roles and +policies for the TE stack. This step is **REQUIRED** to successfully install the +TE stack: + +- TE + IAM Roles and Policies YAML + +Refer to +AWS +Documentation for how to create a new CloudFormation stack. + +Once the template is downloaded, create a new CloudFormation stack in the AWS +account designated as the install account. Label the stack to make it +recognizable, such as **TE Custom Roles and Policies**. + +## Install the Turbot Guardrails Enterprise (TE) Stack + +After the TEF and TED stack, along with all IAM roles and policies, are created, +it is time to move onto installing the TE stack. Refer to our +[Turbot Guardrails Enterprise Installation Guide](enterprise/installation/te-installation), +setting the following custom option: + +- **Role Creation Scheme**: `None` + +## Completing the Turbot Install + +Once the TEF, TED, and TE stacks are successful and in the OK state, the +Workspace stack can be configured and subsequent post installation steps taken +care of. Post installation steps can include updating internal DNS records, +[installing and updating mods](mods) and +[creating a new directory](guides/directories) for authentication. + +- [Guide to install the Workspace Manager](enterprise/installation/workspace-manager) +- [Post Installation](enterprise/installation/post-installation) + +### Additional Resources + +- [Guardrails Samples Repo](https://github.com/turbot/guardrails-samples) - Public + repository with Terraform and GraphQL examples. +- [7-Minute Labs](7-minute-labs) - Labs to help further the understanding of + Turbot and its features. +- [Turbot Guides](guides) - Multitude of guides covering a wide range of topics, + from policy examples, Turbot files, and folders. diff --git a/docs/enterprise/installation/pre-installation/index.md b/docs/enterprise/installation/pre-installation/index.md new file mode 100644 index 00000000..ea1a1b86 --- /dev/null +++ b/docs/enterprise/installation/pre-installation/index.md @@ -0,0 +1,247 @@ +--- +title: Pre-install Checklist +sidebar_label: Pre-install Checklist +--- + +# Turbot Guardrails Enterprise Pre-Installation Checklist + +## For all enterprise installations +1. **Installation Domain Name**: Decide on the base domain for your environment. (e.g. `.cloudportal.company.com`, `.guardrails.acme.com`) +1. **Console Name**: Decide on the name of your web console. (e.g. `prod` => `https://prod.cloudportal.company.com` or `console` => `https://console.guardrails.acme.com`) +1. **ACM Certificate**: Use Amazon Certificate Manager (ACM) to create a wildcard SSL/TLS certificate for your chosen domain (e.g. `*.cloudportal.company.com`), or have the certificate issued by your certificate authority and then upload into ACM. +1. **HA/DR Config**: Decide on your HA/DR configuration. Guardrails can be installed in up to 3 availability zones across 3 regions for mission critical production applications or in a single region/az for dev/sandbox environments. +1. **Networking**: Decide on how you will configure your networking. Turbot Support recommends that you use the Turbot Guardrails Enterprise Foundation (TEF) product to create the VPC and necessary Security Groups for your initial deployment. After successful initial install of the environment you can then progressively harden the VPC to enterprise standards. If you choose to install Guardrails into a custom VPC, it must be set up BEFORE installation starts. +1. **Security Groups**: If using a custom VPC, the Guardrails Samples repo contains a [CloudFormation template](https://github.com/turbot/guardrails-samples/blob/master/installation/security_groups.yml) to create the three required security groups with the required ports. If a proxy is in use, the security group rule for the proxy port must be added to the `OutboundInternetSecurityGroup` resource. +1. **Event Handling**: Plan out how events will get from the managed cloud accounts back to Guardrails for processing. Turbot Support recommends using an API Gateway when the Guardails console is only reachable from internal networks. +1. **DNS**: Guardrails can use Route53 or third party DNS resolution. Turbot Support recommends Route53 for ease of maintenance during upgrades. Private Route53 hosted zones may be used with proper inbound resolvers. +1. **Custom IAM Roles**: If the organization requires custom external roles not created by Guardrails, refer to the guide for creating [Custom Guardrails IAM Roles](pre-installation/external-role). +1. **Turbot License Key**: Turbot Support will provide a license key for the Guardrails installation. + +## AWS AutoScaling Role +Ensure that the IAM service role called `AWSServiceRoleForAutoScaling` already exists in the account. If it doesn't, create then immediately destroy a throw-away autoscaling group to have AWS create it for you. Manually creating a service role will generate a role named `AWSServiceRoleForAutoScaling_{some number}` which Guardrails won't use. + +## Custom network pre-install checklist +1. **Network Infrastructure as Code** - Turbot Support recommends building the Custom VPC via Terraform or Cloudformation to ensure accuracy and repeatability. Building the Guardrails security groups with the [CloudFormation template](https://github.com/turbot/guardrails-samples/blob/master/installation/security_groups.yml) works best. Any changes to the configuration should be updated in the source template and redeployed to prevent errors and to allow the template to be shared with Turbot Support for troubleshooting. +1. **Configuration Crib Sheet** - After deployment of your VPC and security groups, record the IDs/Values of the key resources that will be used as inputs to the TEF product. An example: + + ``` + Installation Domain: cloudportal.company.com + Certificate ARN: arn:aws:acm:{region}:{accountId}:certificate/{certificateId} + Turbot License Key: -----BEGIN TURBOT LICENSE-----{redacted}-----END TURBOT LICENSE----- + + VPC ID: vpc-0f3e50fad8a67dbb5 + VPC CIDR Range: 10.10.0.0/23 + + LB Subnet IDs: subnet-0024a21029654500e,subnet-091f6dfc55269a679 + App Subnet IDs: subnet-0bd06d20b6d54857d,subnet-061c8fbc8f88dfa66 + DB Subnet IDs: subnet-0a2d7f12a0357d850,subnet-0f5d3436eb1cff5c6 + + Security Groups: + LoadBalancerSecurityGroup: sg-04904bbac705630f4 + ApiServiceSecurityGroup: sg-056a37a3f2ebc3453 + OutboundInternetSecurityGroup: sg-0711d5475ece2e659 + + HTTP_PROXY: http://{proxy_address}:{proxy_port} + HTTPS_PROXY: http://{proxy_address}:{proxy_port} + ``` + +1. **Access to the Guardrails Console UI/API** - Ensure a network path exists from your desktop clients to the Guardrails Loadbalancer Subnets. That can be accomplished with public access via an IGW (Turbot recommends using IP address restrictions when using public routing), or via a private network link (e.g. VPN, Direct Connect, Transit Gateway, Bastion). If using private connectivity: + + a) Ensure that route tables for the Load Balancer Subnets have a path to your private network. + b) Ensure the Load Balancer Security Group allows **ingress** to port `443` (https) from your private IP space. (e.g. 10.0.0.0/8) + c) Ensure the Load Balancer Security Group also allows **ingress** on port `443` from at least one of the following: [VPC CIDR, App Subnet CIDRs, Egress Security Group] + d) Ensure the Load Balancer Security Group allows **egress** on port range `32768` to `65535` to at least one of the following: [VPC CIDR, App Subnet CIDRs, API Security Group] + +1. **Outbound Internet Access (OIA)** - Ensure a network path exists from the Guardrails VPC to the Internet. To perform its governance function Guardrails requires access to cloud service APIs for AWS, Azure, GCP and any other SaaS/PaaS/IaaS service that it is configured to provide governance for. Due to the size and rate of change of the cloud service IP space it is not practical to restrict this traffic via IP addresses/CIDRs. Ensure that one of the following network connectivity paths exist: + + - **IGW & NAT Gateway**: This scenario allows internet egress via a standard AWS Internet Gateway and NAT Gateways attached to the VPC. Please note that in VPC Lambda functions run in private address space and require the presence of a NAT gateway (or Proxy/TGW) to have internet connectivity. + - Ensure public subnets exist in each availability zone in use for the App Subnets. + - Ensure that the Route Table for the public subnets has a path for the default route (`0.0.0.0/0`) to an IGW. + - Ensure a NAT gateway exists in each of those public subnets. + - Ensure that the App Subnet Route Tables have a path for the default route (`0.0.0.0/0`) to the NAT gateway in the same availability zone. + - Test external connectivity prior to install [See Below](#testing-internet-connectivity-prior-to-installation) + + - **Transit Gateway**: In this scenario, Internet connectivity is routed through a Transit Gateway. We do not cover configuration of the Transit Gateway as it is beyond the scope of this document and there are many possible variations. For a simple TGW outbound internet solution, please see [AWS documentation](https://aws.amazon.com/blogs/networking-and-content-delivery/creating-a-single-internet-exit-point-from-multiple-vpcs-using-aws-transit-gateway/). + - Ensure the Transit Gateway is attached to the VPC. + - Ensure Transit Gateway route table can egress data to the VPC CIDR(s). + - Ensure the Route Tables for the `App Subnets` have a path for the default route (`0.0.0.0/0`) to the Transit Gateway. + - Ensure the `Egress Security Group` allows https (port 443) to the Default Route + - Test external connectivity prior to install [See Below](#testing-internet-connectivity-prior-to-installation) + + - **Internet access via on prem network**: In this scenario traffic will be routed from the VPC via Direct Connect or a VPN to your on-premise network. Network routing rules there will allow OIA like any other device on the corporate network. For performance and cost optimization Turbot Support recommends configuring VPC Endpoints for high volume services that Guardrails will use to manage itself when using on premise networking. + - Ensure a Virtual Private Gateway (VGW) exists and is attached to your VPC. + - Ensure the Route Tables for the `App Subnets` have a path for the default route (`0.0.0.0/0`) to the VGW. + - Ensure the `Egress Security Group` allows https (port 443) to the Default Route (`0.0.0.0/0`) + - If using VPC Endpoints with this configuration, please read and review the section on VPC endpoints before testing connectivity. + - Test external connectivity prior to install [See Below](#testing-internet-connectivity-prior-to-installation) + + - **Internet access via an http proxy**: Guardrails uses several AWS services that *do not* support inclusion of the third party certificates necessary for Man-in-the-middle (MITM) SSL interception proxies to work. Additionally, the AWS SDK does not support specifying a proxy and also specifying regional excpetions to the proxy. If a proxy is set, all AWS-bound traffic will use the proxy. Contact Turbot Support to discuss any specific considerations. + - Add the proxy configuration details to your **configuration crib sheet**: + ``` + HTTP_PROXY: http://10.1.1.1:7000 or http://internal.proxy.com:2011 + HTTPS_PROXY: http://10.1.1.1:7000 or http://internal.proxy.com:2011 #these should never start with https, see above statement on MITM SSL proxies. + NO_PROXY: 169.254.169.254,localhost + ``` + - Ensure the Route Tables for the `App Subnets` have a path to the proxy server. + - Ensure the `Egress Security Group` allows https (port 443) to egress to the proxy server. + - Ensure the `Egress Security Group` allows https (port 443) to egress to the VPC CIDR. + - If using VPC Endpoints with this configuration, please read and review the section on VPC endpoints before testing connectivity. + - Test external connectivity prior to install [See Below](#testing-internet-connectivity-prior-to-installation) + + - **Considerations for VPC Endpoints**: When OIA is not using the IGW/NAT Gateway it will improve performance and reduce cost to setup [VPC Endpoints](https://docs.aws.amazon.com/vpc/latest/userguide/vpc-endpoints.html) in the Guardrails VPC. If using a proxy configuration with no alternate Internet egress from the VPC. It is required to use VPC Endpoints for AWS services that are not proxy aware. Care should be taken to ensure that any custom configuration of your VPC Endpoint Policies does not interfere with the Guardrails installation or operations; the following are examples of common misconfiguration: + - **S3 Gateway Endpoint configured to only allow access to specific buckets**: Guardrails requires access to Create, Describe, Get and Put objects in it's own account, and for logging buckets in accounts that it is governing. Guardrails also requires access to list and get objects from Turbot-owned software buckets to allow for installation of mods. Depending on the S3 bucket policy settings, Guardrails may also require the ability to List, Describe and/or Put bucket configuration for all buckets in all accounts under management. + - **S3 Gateway Endpoints configured to forbid access to CloudFormation response buckets**: During the configuration of the TED stack, the Guardrails `hive_manager` Lambda needs access to the regional CloudFormation response buckets as described in [Setting Up VPC Endpoints for AWS CloudFormation](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/cfn-vpce-bucketnames.html) documentation. Ensure that the proper endpoint policy allows access to the proper regional response bucket. Specifically, this means the ability to do an HTTPS `PUT`. The S3 endpoint policy should allow a `PutObject` to `cloudformation-custom-resource-response-` of the [desired regions](https://docs.aws.amazon.com/general/latest/gr/rande.html#cfn\_region). + + This is an example resource section of the S3 VPC endpoint policy. Be sure to include the `/*` at the end of the resource arn. + ```json + "Resource": [ "arn:aws:s3:::cloudformation-custom-resource-response-*/*", + "arn:aws:s3:::cloudformation-waitcondition-*/*", + "arn:aws:s3:::other-permitted-s3-buckets/*" + ] + ``` + + - **CloudWatch Endpoints configured to only allow access to limited APIs or to specific log groups**: Guardrails requires the ability to create log groups, log streams, write to log streams, create/update CloudWatch events, create CloudWatch Dashboards, etc. Turbot Support recommends that you configure the endpoint with the default Full Access policy. + - **Interface Endpoints configured with a restricted security group**: [Interface Endpoints](https://docs.aws.amazon.com/vpc/latest/userguide/vpce-interface.html) are configured with a security group to optionally restrict traffic. The security group attached must minimally allow port `443` (https) **egress** to the default route (`0.0.0.0/0`), and allow port `443` (https) **ingress** from the VPC CIDR (or from the `egress security group`). + - `Recommended/Required VPC Endpoints`: + - Cloudwatch + - com.amazonaws.{region}.logs + - com.amazonaws.{region}.monitoring + - com.amazonaws.{region}.events + - ECS + - com.amazonaws.{region}.ecr.api + - com.amazonaws.{region}.ecr.dkr + - com.amazonaws.{region}.ecs + - com.amazonaws.{region}.ecs-agent + - Others + - com.amazonaws.{region}.kms + - com.amazonaws.{region}.cloudtrail + - com.amazonaws.{region}.s3 + - com.amazonaws.{region}.ssm + - com.amazonaws.{region}.sts + - com.amazonaws.{region}.sns + - com.amazonaws.{region}.sqs + +## Testing internet connectivity prior to Installation + Because custom network configuration is a complex and multifaceted, it is critical to perform practical tests to ensure connectivity prior to starting the install process. The install process is automated and several steps take extended periods of time; diagnosing issues, uninstalling services and reinstalling is time-consuming and frustrating; in contrast, taking the time to perform the following tests is a relatively painless process that can provide a higher probability of "first run success" and eliminate many variables if troubleshooting is needed. Pre-install testing process: + + 1. **Launch Linux Instance**: Launch a linux test instance into each App subnet. + + 1. **DNS Resolution for Instance**: If using private DNS (or a non-Guardrails managed Route53 hosted zone) register an `A` record for one of the test instances (e.g. `test-a.cloudportal.company.com` => `10.10.0.10`). + + 1. **Outbound Security Group**: Attach the `OutboundInternetSecurityGroup` to the instances in addition to the security group used for inbound ssh access. Ensure that the security group used for SSH access does not provide any Egress rules to prevent false positives when testing. + + 1. **Instance Profile**: Attach an instance profile with the aws managed `Administrator` role to the instances. + + 1. **Install Required Utiltiies**: Log into the instances and install NetCat, Curl, AWS CLI utilities. + + 1. **Public DNS resolution**: Test DNS resolution to the public internet: + + ``` + > nslookup google.com + + Non-authoritative answer: + Name: google.com + Address: 172.217.7.174 + + > nslookup amazonaws.com + + Non-authoritative answer: + Name: amazonaws.com + Address: 207.171.166.22 + Name: amazonaws.com + Address: 72.21.210.29 + ``` + + 1. **Private DNS resolution**: Test DNS resolution to private DNS + ``` + > nslookup test-a.cloudportal.company.com #substitute your domain and hostname + + Name: test-a.cloudportal.company.com + Address: 10.10.0.10 + ``` + + 1. **VPC Endpoint Resolution**: Test DNS resolution to VPC Endpoints: *Only test if using VPC endpoints*. **Expected Result**: If configured correctly, this should resolve to a private IP address within the VPC. If it resolves to a public IP, please check the configuration of [Private DNS for VPC Endpoints](https://docs.aws.amazon.com/vpc/latest/userguide/vpce-interface.html#vpce-private-dns). Note that VPC endpoints are region specific so in this example only the us-east-1 endpoint resolves to a private address, us-east-2 resolves to a public IP because the VPC in the example is in us-east-1. + ``` + > nslookup logs.us-east-1.amazonaws.com + + Name: logs.us-east-1.amazonaws.com + Address: 10.10.0.8 + + > nslookup logs.us-east-2.amazonaws.com + + Name: logs.us-east-2.amazonaws.com + Address: 52.95.18.172 + ``` + + 1. **Public Internet Connectivity**: Test connectivity to the public Internet: + ``` + > curl https://google.com + + + 301 Moved +

    301 Moved

    + The document has moved + here. + + ``` + + + 1. **AWS Connectivity**: Test connectivity to AWS + ``` + > curl amazonaws.com + + + + 301 Moved Permanently + +

    Moved Permanently

    +

    The document has moved here.

    + + ``` + + 1. **AWS Service Connectivity**: Test connectivity to AWS services using NetCat: **If not using VPC endpoints** the two tests below will suffice; **If using VPC endpoints** make sure to test both the VPC region and a secondary region and repeat for each VPC Endpoint configured and at least one service that does not have an endpoint. + ``` + > nc -vz logs.us-east-1.amazonaws.com 443 + + Connection to logs.us-east-1.amazonaws.com port 443 [tcp/https] succeeded! + + > nc -vz logs.us-east-2.amazonaws.com 443 + + Connection to logs.us-east-2.amazonaws.com port 443 [tcp/https] succeeded! + + > nc -vz s3.us-east-1.amazonaws.com 443 + + Connection to s3.us-east-1.amazonaws.com port 443 [tcp/https] succeeded! + + > nc -vz s3.us-east-2.amazonaws.com 443 + + Connection to s3.us-east-2.amazonaws.com port 443 [tcp/https] succeeded! + ``` + + 1. **AWS CLI Commands**: Test the ability to execute AWS API commands: If any of the following tests fail, Guardrails will not be able to install correctly; follow-up and diagnose any errors **prior to beginning the installation process**. + ``` + > aws s3 ls + ... (list of buckets) + > aws s3 mb s3://{some_random_bucket_name} --region {installation_region} + > touch test.file + > aws s3 cp test.file s3://{some_random_bucket_name} + > aws s3 rm s3://{some_random_bucket_name}/test.file + > aws s3 rb s3://{some_random_bucket_name}/ + + > aws logs create-log-group --log-group-name /turbot/test-logging --tags test=tag + > aws logs create-log-stream --log-group-name /turbot/test-logging --log-stream-name test001 + > aws logs create-log-stream --log-group-name /turbot/test-logging --log-stream-name test001 + > aws logs put-log-events --log-group-name /turbot/test-logging --log-stream-name test001 --log-events timestamp=1433190184356,message=test-event-1 + + > aws kms list-keys + ``` + + 1. **CloudFormation Custom Resource Response**: If using S3 endpoints or a proxy, test connectivity to the CloudFormation custom resource response URL using the following curl. + + ``` + curl 'https://cloudformation-custom-resource-response-{region}.s3.amazonaws.com/?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-SignedHeaders=host&X-Amz-Expires=7200' + ``` + + **WARNING**: If this test to the CloudFormation Response bucket fails, resolve before proceeding with installation. If CloudFormation can't receive responses that the custom resources are complete then the CloudFormation stack will stall for 30 minutes to an hour. Clean up of the stalled custom resources can be quite time consuming. + + The `{region}` value will be the AWS region that Guardrails is being installed into. An unauthorized response is ok - the purpose is to test network connectivity to the endpoint. Once this has been verified, along with the rest of this list, the Guardrails installation can move forward. diff --git a/docs/enterprise/installation/te-installation/index.md b/docs/enterprise/installation/te-installation/index.md new file mode 100644 index 00000000..49d918e4 --- /dev/null +++ b/docs/enterprise/installation/te-installation/index.md @@ -0,0 +1,55 @@ +--- +title: TE Installation +sidebar_label: TE Installation +--- + +# Turbot Guardrails Enterprise (TE) Installation + +**Turbot Guardrails Enterprise (TE)** provides automated configuration and management of +Turbot infrastructure to be used when running the Turbot software application. +For example, TE provides the setup of load balancers, SQS queues, ECS, etc. +while Turbot provides the software to run in the container. + +TE deploys a new version of the Turbot software -- Every Turbot release requires +a new TE version. + +
    Turbot Guardrails Enterprise v5.8.6 is a TE release. To install it, you must lauch a new TE stack, and then update your workspaces for the new version. +
    + +## Install + +### Launch the TE Service Catalog item + +1. In the AWS Console, navigate Service Catalog in the region into which you + wish to install TE. + +1. Select **Turbot Guardrails Enterprise** from the Products list and click “Launch + Product.” + +1. Select a **Name** for the provisioned project. Typically, this will start + with “te” and will include the version number, for example: `te-5-8-6` + +1. Select a **Version**. Usually, you will want the latest version. + +### Advanced - Foundation Parameters + +The Foundation Parameters allow the TED stack to use SSM parameters defined in +the TEF stack. You should only change these values if you did not use the +default **Resource Name Prefix** (turbot) in the TEF stack. + +### Advanced - Foundation Overrides + +The Foundation Overrides allow you to override values defined in the TEF stack. +Normally, these should all be blank. + +### Advanced - Deployment + +1. Select a **Resource Name Prefix**. This prefix will be added to all Turbot + resources, and should match the prefix used in the TEF and TED stacks + +
    + The Resource Name Prefix must match the Resource Name Prefix used in the Turbot Guardrails Enterprise Foundation (TEF) stack! +
    + +2. Select the portfolio **Release Stream** (development, staging, or + production). This should usually be "production". diff --git a/docs/enterprise/installation/ted-installation/index.md b/docs/enterprise/installation/ted-installation/index.md new file mode 100644 index 00000000..5cdc5984 --- /dev/null +++ b/docs/enterprise/installation/ted-installation/index.md @@ -0,0 +1,192 @@ +--- +title: TED Installation +sidebar_label: TED Installation +--- + +# Turbot Guardrails Enterprise Database (TED) Installation + +**Turbot Guardrails Enterprise Database (TED)** provides an automated configuration and +management of Turbot database infrastructure to be used when +installing/upgrading an enterprise deployment of the Turbot Software. + +TED deploys a Turbot Hive, which defines physical database and caching resources +shared by multiple workspaces. + +## Install in the primary (alpha) region + +### Launch the TED Service Catalog item + +1. In the AWS Console, navigate to Service Catalog in the region into which you + wish to install TED. +1. Select **Turbot Guardrails Enterprise Database** from the Products list and click Launch + Product. +1. Select a **Name** for the provisioned project. Typically, this will be `ted`. +1. Select a **Version**. Usually, you will want the latest version. + +### Hive Configuration + +1. Enter the **Database Hive Name**. +1. Select the **Primary Region**. In this case, it should be the current region + (You should run the primary install from the region into which you are + installing). + +### Database - Configuration + +1. Choose an **Instance Type for DB**. The correct RDS instance type depends on + many factors, including the number of resources and controls, the required + performance, and cost considerations. `db.m5.2xlarge` is a common starting + point. +1. Choose the amount of **Allocated Storage in GB** for your database. As with + instance type, needs vary depending on the specific environment. Note that + depending on the storage type you select, the storage size may also impact + the storage throughput. + +### Database - Replication + +1. Leave the **Primary endpoint** blank because this is the first region being + installed. This is field is only needed when adding a replica in an + additional region. + +### Database - Advanced - High Availability Settings + +1. **Multi-AZ Failover Enabled:** If true, and this region includes the primary + instance, then create a failover instance in a different availability zone to + the primary instance. + +
    + In production, a failover instance is recommended! +
    + +1. **Read Replica Enabled for this region:** If true, create a read replica for + the hive in this region. + +
    + In production, it is recommended to have a read replica instance in each region where Turbot is running, including the region where the primary instance resides +
    + +### Database - Advanced - Engine + +1. The **DB Engine** must be postgres. +1. The **DB Engine Parameter Group Family** must be postgres11. +1. Currently supported **DB Engine Version** appera in the dropdown. +1. You may choose whether you would like RDS to **Allow major version + upgrades.** If enabled and the engine version requests it, major version + upgrades will be applied to the database through CloudFormation. +1. You may choose whether you would like RDS to **Automatically upgrade minor DB + versions.** If enabled, RDS automatically performs minor version upgrades of + the database during the scheduled maintenance window. + +### Database - Advanced - Storage + +- Select the desired **Storage Type**. Storage throughput needs may vary + significantly, but GP2 provides a decent starting point if you are uncertain. +- If you selected the IO1 storage type, enter the **Provisioned IOPs.** This is + only used if **Storage Type** is io1. Review the + [relevant Amazon documentation](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-rds-database-instance.html#cfn-rds-dbinstance-iops) + for valid values and rations. + +### Database - Advanced - Encryption + +1. In the **Use AWS KMS DB Encryption** field, select a KMS key to encrypt the + hive. + - Select `aws/rds` to use the predefined AWS KMS key for RDS. + - Select `Hive CMK` to create a customer managed key specific to the hive. + This is typically considered more secure and is the recommended option. + +### Database - Advanced - Authentication + +1. Enter a **Master User Name**. This field defaults to **master**. +1. If running TED for the first time, keep the **MasterPassword** field blank. + If a custom password is required, wait for the stack to finish, update the + master password on the database itself, then update the TED stack with the + custom password. +1. You may choose to **Use AWS IAM for DB Access**. This is the recommended + approach, as no secrets need to be stored / rotated. + +### Database - Advanced - Backup & Snapshots + +1. It is recommended to enable **Deletion Protection** to protect database + resources from deletion. You must explicitly set this to `false` before + decommissioning. +1. You may set the **Backup Retention Period** in **Days.** Automated backups + will be retained for the number of days specified. +1. You may choose to **Delete Automated Backups** automatically when the primary + instance is deleted. The recommended value is `false`. +1. You may choose to **Copy DB tags to snapshots** automatically. + +### Database - Advanced - Logging + +1. Select the **Type of statements to be logged.** Note that database storage + and performance may be impacted by this setting. You may select: + - **all** – log ALL statements. This is typically only used for debugging. + - **ddl** - log all data definition language (DDL) statements (CREATE, ALTER, + DROP, etc). + - **mod** - log all DDL and data modification language (DML) statements + (INSERT, UPDATE, DELETE, Etc). + - **none** : logging is off – no statements are logged. +1. Set the **Minimum Duration to log statement in ms**. Statements that exceed + this execution time above which statements will be logged. +1. Set a value for **Delete logs older than N minutes.** Amazon RDS will delete + PostgreSQL log that are older than the specified number of minutes. +1. Enable or disable **Performance Insights** for your database instances. +1. Set the **Maximum number of concurrent connections**. The maximum number of + concurrent connections to the database instances.The current recommended + setting is 600. +1. Set the **Alarm threshold for maximum number of concurrent connections**. The + value that determines alarm to be triggered when the number of concurrent + connections are reached.The current recommended setting is 500. +1. Set the **Deadlock timeout period in ms**. The time to wait on a lock before + checking for deadlock. The current recommended setting is 2000. +1. Set the **Duration of Idling Transaction Session in ms**. The maximum allowed + duration of any idling transaction.The current recommended setting is 900000. +1. Set the **Maximum Allowed Duration of Statement in ms**. The maximum allowed + duration of any statement to execute. The current recommended setting + is 60000. +1. Set a value for **RDS Admin logging level**. The PostgreSQL engine starts + capturing queries executed by the admin user. +1. Set a value for **Function-level database activity tracking**. It enables + tracking of function call counts and time used. +1. Set a value for **Dynamic Bucket Name specified in TEF**. You should only + change these values if you did not use the default **Resource Name Prefix** + (turbot) in the TEF stack. +1. Set a value for **Log Bucket Name format specified in TEF**. You should only + change these values if you did not use the default **Resource Name Prefix** + (turbot) in the TEF stack. + +### Advanced - Foundation Parameters + +The Foundation Parameters allow the TED stack to use SSM parameters defined in +the TEF stack. You should only change these values if you did not use the +default **Resource Name Prefix** (turbot) in the TEF stack. + +### Advanced - Foundation Overrides + +The Foundation Overrides allow you to override values defined in the TEF stack. +You will likely want to leave these blank. + +### Advanced - Infrastructure + +1. Select a **Resource Name Prefix**. This prefix will be added to all Turbot +resources. Because this prefix will be used across many resource types and +different resource types have different name restrictions, you should avoid +special characters and uppercase letters. This prefix should match the name +prefix you used in the TEF stack. +
    +It is HIGHLY RECOMMENDED that you use the default prefix! The TEF Stack will export the parameters that you have select to an SSM parameter, and they will use this prefix. Using the default will greatly simplify TE deployments and upgrades. +
    + +--- + +### Termination Protection + +21. To ensure that the TED stack is not accidentally deleted, it is strongly + recommend that termination protection is enabled. This can be done via the + following steps once the stack is in the OK state: + 1. Log into the AWS account containing the Turbot install. + 2. Navigate to the CloudFormation Service. + 3. Select the TED stack. The description of the correct stack should say + **Turbot Guardrails Enterprise Database**. + 4. Click **Stack Actions**. + 5. Click **Edit Termination Protection**. + 6. Switch the setting from **Disabled** to **Enabled**, then click the + **Save** button. diff --git a/docs/enterprise/installation/tef-installation/index.md b/docs/enterprise/installation/tef-installation/index.md new file mode 100644 index 00000000..f189c1d1 --- /dev/null +++ b/docs/enterprise/installation/tef-installation/index.md @@ -0,0 +1,258 @@ +--- +title: TEF Installation +sidebar_label: TEF Installation +--- + +# Turbot Guardrails Enterprise Foundation (TEF) Installation + +**The Turbot Guardrails Enterprise Foundation** stack creates networking components that +will be shared by all workspaces. + +## Install + +### Launch the TEF Service Catalog item + +1. In the AWS Console, navigate to Service Catalog in the region into which you + wish to install TEF. +1. Select **Turbot Guardrails Enterprise Foundation** from the Products list and click + "Launch Product." +1. Select a **Name** for the provisioned project. Typically, this will be "tef". +1. Select a **Version**. Usually, you will want the latest version. + +### Installation + +1. Enter the **Installation Domain Name**. + + - This should be the base domain name for the installation (for example, + `turbot.mycompany.com`). This should be unique per Turbot installation – + you cannot share an Installation Domain Name across multiple collectives. + - Workspaces will be set up as subdomains of this installation domain (for + example, `dev.turbot.mycompany.com`). + - If you elect to create a public API gateway, it will also be a subdomain of + the installation domain (for example, `external.mycompany.turbot.com`). + - Domain names **CANNOT** be shared across multiple TEF installs if the API + Gateway is deployed. Attempting to do so will result in connection errors. + +1. Enter the **Turbot Certificate ARN** to be used for the Turbot Console (and + gateway, if applicable) in this region. + + - This **_must_** be the ARN of an **_ACM certificate in this region_**. + - The certificate domain name must match the **Installation Domain Name**. + - Wildcard certificates should include entries for the base **Installation + Domain Name** and a wildcard for workspaces. Example: + `turbot.mycompany.com` and `*.turbot.mycompany.com`. + - For environments where wildcard certs are not allowed, the certification + should include the base **Installation Domain Name**, all workspace domain + names and any public API gateways. +
    + A wildcard certificate is highly recommended. Without a wildcard cert, the certificate will need to be updated with the new workspaces as they are brought online. +
    + +1. Select whether Turbot domain names should be managed in Route53. + + - When enabled, Turbot will manage blue/green deployments by swapping DNS + names during version upgrades + - If the API gateway feature and Route53 management are enabled, Turbot will + manage routing to the nearest regional gateway. + - To use this feature, _you must host the DNS zone for the Installation + Domain Name in Route 53 in the Turbot account_. + +
    + It is highly recommended that you allow Turbot to manage DNS records in Route53. If you choose not to do so, you must manually update DNS records every time you install a new version in your workspaces. +
    + +1. Each region must be given a different **Region Code** identifier, allowing + the stacks to be automatically coordinated for peering etc. Select "Alpha" as + the **Region Code** for this first region. + +### Logging + +1. Select the **Turbot Handler Log Retention Days** or keep the default. +1. Select the **Audit Trail Log Retention Days** or keep the default. + +### Network + +If desired, the Turbot Guardrails Enterprise Foundation setup can create the VPC to host +Turbot. Alternatively, you can install Turbot into an existing VPC. + +#### Network - This Region [Option A - Created in this Stack] + +
    +To have TEF create the Turbot VPC, enter the required information in Network - This Region [Option A - Created in this Stack] and leave all fields in Network - This Region [Option B Predefined] blank!. +
    + +1. Enter the CIDR ranges for the TEF Subnets. These CIDR ranges must all fall + within the range specified for the VPC in the previous step. + + - CIDRS fall into 3 categories – any subnet with an empty CIDR will NOT be + created: + - **Public Subnets** will route through an Internet Gateway, allowing + public IP addresses to be used. If you wish to access the Turbot Console + via the Internet, on a public IP address, then you should configure one + or more public subnets to host the load balancers. + - **Turbot Subnets** are configured as private subnets that may route + outbound to the internet via a NAT gateway, but not inbound. Turbot + application servers and containers will be launched in these subnets. + - **Database Subnets** are configured as private subnets with no inbound or + outbound access – only VPC traffic is routed to and from these subnets. + These subnets can be used to host the Postgres database instances. + - Note that for each subnet type, there are 3 possible subnets. These + correspond to 3 different availability zones. As stated previously, a + subnet with an empty CIDR will not be created – If you wish to create a 2 + AZ network, only enter CIDRs for subnets #1 and #2, for example. + +
    Any subnet with an empty CIDR will NOT be created. +
    + +1. Enter the desired **NAT Gateway High Availability** configuration.  For a + production deployment, you should choose **Multi-AZ**. + +#### Network - This Region [Option B - Predefined] + +To install Turbot into an existing VPC, enter the required information in +**Network - This Region [Option B - Predefined]** + +
    +Note that Turbot requires outbound https to the Internet from the load balancer and application (Turbot) subnets. This can be routed through your proxy if desired. +If using a proxy, you must also create VPC endpoints to allow fargate to access the following AWS services: +
      +
    • ECR API
      • +
    • CloudWatch Logs
      • +
    • ECR DKR
      • +
    • S3
      • +
    +
    + +1. Enter the VPC ID that will be used to host Turbot in the **VPC** field. This + VPC must already exist. If empty, then a new VPC will be deployed by this + stack, per **Network - This Region [Option A - Created in this Stack]**. +1. In the **Load Balancer Subnets** field, enter a comma separated list of + subnet IDs where the load balancers will be deployed. These subnets may be + public facing or internal facing, and can be identical to the Application + Subnet IDs. Id you have selected a pre-defined VPC, you MUST specify Load + Balancer Subnet Ids here. +1. In the **Application (Turbot) Subnets** field, enter a comma separated list + of subnet IDs where the Turbot Containers and private lambda functions (such + as the workspace manager) will be deployed. If you have selected a + pre-defined VPC, you MUST specify Application (Turbot) Subnet IDs here. These + subnets must be able to route https outbound to the Internet, either directly + or through a proxy. +1. In the **Database Subnets** field, enter a comma separated list of subnet IDs + where the databases will be deployed. If you have selected a pre-defined VPC, + you MUST specify Database Subnet IDs here. + +#### Network – Load Balancer + +Enter load balancing and gateway information. + +1. Select the load balancer **scheme.** The scheme determines if the load + balancer is internal or internet-facing. If internet-facing then the load + balancer subnets must be "public". Otherwise, the subnets should be "turbot". +1. Enter a **CIDR for inbound access from Clients / Users**: The CIDR range for + inbound traffic to the Turbot load balancer (i.e. end users). Typically this + will be 0.0.0.0/0, but may be updated for environments with limited access + requirements. +1. If you choose to use an internal load balancer, you should set **Create + public API gateway** to **Enabled**. This will create an API Gateway that + allows Turbot to receive real-time events. + +#### Network - Proxy + +Enter **Network – Proxy** information if you wish to configure Turbot +application containers and VPC lambdas to use a proxy server for outbound HTTPS. +_Note that controls and calculated policies running in most Lambda functions do +not use the proxy configuration since they are outside the VPC._ + +1. **HTTP_PROXY**: HTTP_PROXY configuration used by the Turbot application + containers for HTTP requests, e.g. http://internal.proxy.com:2011. Default is + null (no proxy). +1. **HTTPS_PROXY**: HTTPS_PROXY configuration used by the Turbot application + containers for HTTPS requests, e.g. http://10.5.6.7:890 or + http://internal.proxy.com:2011. Default is null (no proxy). +1. **NO_PROXY**: NO_PROXY configuration used by the Turbot application + containers as exceptions to the HTTPS_PROXY and HTTP_PROXY settings, e.g. + 169.254.169.254, localhost. \*Be aware that the node.js AWS SDK does not + support passing some AWS services through the proxy but not others. Either + the proxy handles all traffic to the AWS service endpoints, or it should + handle none of them. + +#### Network - Security Groups + +If you are using a pre-defined VPC, you will need to create security groups +that allow access appropriate to your environment. The Guardrails-Samples repo +contains Cloudformation to [build these for you](https://github.com/turbot/guardrails-samples/blob/main/installation/security_groups.yml). +Add additional ports to these three security group to meet your organizational needs. Do not remove ports or security group +relationships. + + +1. **Custom Outbound Security Group ID** A security group that allows the + container services outbound access to the database and aws services. If you + use an http proxy, you will need to add an egress rule to the custom + security group to be able to allow the containers to access it. You may also + need outbound access for other infrastructure services, such as DNS. + + A. Minimum Requirements + - Ingress: None + - Egress: HTTPS (443), HTTP (80), DNS (tcp,udp:53), NTP (123) + +2. **Custom Load Balancer Security Group ID** A custom load balancer Security + Group id that has ingress rules for accessing the turbot application. + + A. Minimum Requirements + - Ingress: HTTPS (443) + - Egress: ECS API Tasks (port range: 32768 to 65535) to the API Service Security Group only + +3. **Custom Api Service Security Group** A custom Api service Security Group id + that has restricted outbound access and inbound access to load balancer. + + A. Minimum Requirements + - Ingress: Loopback HTTPS (443) + - Egress: ECS API Tasks (port range: 32768 to 65535) to the Load Balancer Security Group only + +#### Advanced - Scaling + +Set **Scaling** options. The defaults are usually sufficient: + +1. **Autoscaling target CPU utilisation**: Target CPU Utilization for ECS EC2 + instances in Turbot Autoscaling Group. The current recommended setting is 50. +1. **API Desired Scale Size**: The number of simultaneous API tasks that you + want to run on the cluster. The current recommended setting is 1. +1. **API Minimum Scale Size:** The minimum value that API Auto Scaling can use + to scale a target during a scaling activity. The current recommended setting + is 1. +1. **API Maximum Scale Size**: The maximum value that API Auto Scaling can use + to scale a target during a scaling activity. The current recommended setting + is 2. + +#### Advanced - Deployment + +17. Select the portfolio lifecycle **Release Phase** for deployment + (development, staging, or production). This should usually be "production". + +18. Select a prefix to be used for all resources created in the stack or use the + default (turbot). Because this prefix will be used across many resource + types and different resource types have different name restrictions, you + should avoid special characters and uppercase letters. + +
    + It is HIGHLY RECOMMENDED that you use the default prefix! The TEF Stack will export the parameters that you have select to an SSM parameter, and they will use this prefix. Using the default will greatly simplify TE deployments and upgrades. +
    + +### Run the Stack + +19. Click through to review your changes and then launch the stack. +20. Verify that the stack completes successfully. + +### Termination Protection + +21. To ensure that the TEF stack is not accidentally deleted, it is strongly + recommend that termination protection is enabled. his can be done via the + following steps once the stack is in the OK state: + 1. Log into the AWS account containing the Turbot install. + 2. Navigate to the CloudFormation Service. + 3. Select the TEF stack. The description of the correct stack should say + **Turbot Guardrails Enterprise Foundation**. + 4. Click **Stack Actions**. + 5. Click **Edit Termination Protection**. + 6. Switch the setting from **Disabled** to **Enabled**, then click the + **Save** button. diff --git a/docs/enterprise/installation/workspace-manager/index.md b/docs/enterprise/installation/workspace-manager/index.md new file mode 100644 index 00000000..9ac1b928 --- /dev/null +++ b/docs/enterprise/installation/workspace-manager/index.md @@ -0,0 +1,283 @@ +--- +title: Workspace Manager +sidebar_label: Workspace Manager +--- + +# Guardrails Workspace Manager + +A **Workspace** is an independent tenant of Guardrails, with its own version and its +own schema (logical shard) in a hive. Each Workspace has its own Turbot root, +its own set of mods, and its own web console endpoint. + +Your workspaces will use the Collective, Hive, and Versions that you deployed +previously, using the TEF, TED, and TE products in the Service Catalog. + +Workspaces are deployed and managed using **Guardrails Workspace Manager**, which is +implemented as a CloudFormation custom resource. + +

    Turbot recommends enabling Termination Protection on the Workspace Manager CloudFormation stack. This can be done at creation by expanding the Stack creation options and enabling Termination Protection.

    This can also be configured post CloudFormation stack deployment. Select the stack while viewing the CloudFormation service in the AWS console, click Stack actions in the top right, then click Edit termination protection. Set this to enabled and click Save!

    + +## Create a Workspace + +1. In the AWS Console, navigate to the CloudFormation service in the alpha + region. + +1. Create a new stack, using the + [Sample Workspace Manager CloudFormation Template](#sample-workspace-manager-cloudformation-template) + +1. Enter the appropriate parameters: + + - **Name:** The name of workspace, which will be used as the first part of + the console URL. For instance, if you specify “dev” as the workspace name, + and you set up the TEF stack using `mycompany.turbot.com` as the domain + name, the console URL will be `dev.mycompany.turbot.com` + + - **Version:** The version of Turbot Guardrails Enterprise to install in the workspace. + This must match an installed (via TE) version exactly, For example: + `5.0.0-beta.18` + + - **Hive:** The Hive name where the database is hosted. This should be the + Hive name that you specified when setting up TED + + - **UseRoute53:** If set to `True`, the stack will automatically update the + DNS alias for the console URL to point to the newly installed version. If + you do not use Route53 to manage the DNS, choose “False”. You will need to + create (or modify) a CNAME record for your workspace to point to the load + balancer for the new version (available as `LoadBalancerDNS` in the stack + output variables). + + - **FoundationStackOutputPrefix:** This must match the resource prefix that + you specified in the Turbot Guardrails Enterprise Foundation stack so that this stack + can use exported outputs from the TEF stack. + +1. Currently, the Workspace Manager generates the initial Turbot Admin account + and password, as well as a key pair. You should login and change the password + and keys as soon as the stack is complete. a. The Console URL for the + workspace is available in the `WorkspaceUrl` output variable. Go to the stack + outputs and click the link to go to the web console. b. The admin username + and password are displayed in the `WorkspaceManagerOutput` variable in the + stack outputs. Login using the admin username and password. c. Once logged + in, change the admin password and delete the generated keys. You can do this + from the profile settings page. i. In the top right of the Turbot Console, + you will see currently logged in user, “Turbot Admin”. Hover over this link, + and then click “Profile” from the popup menu to take you to the profile page. + ii. In the list of access keys, click the [X] button to delete the access key + generated during the install. If desired, you can generate new access keys by + clicking the New access key button iii. On the left side of the page, click + the Reset Password button to change the admin password + +
    + You should login and change the password and keys as soon as the stack is complete: +
      +
    • The username, password, and keys will appear in plain text in the CloudFormation stack output variables
      • +
    • If you re-run the stack, the stack output variable will be overwritten
      • +
    +
    + +### Sample Workspace Manager CloudFormation Template + +While the sample template provides a simple, out-of-the box mechanism for +deploying a single workspace, it is merely a starting point. You may wish to +deploy ALL your workspaces from a single template, so that you can manage +versions for all workspaces from a single stack, for instance. + +This template can also be found on the Guardrails Samples Repo - +[Workspace Manager CloudFormation Template](https://github.com/turbot/guardrails-samples/blob/master/installation/workspace-template.yml) + +```yaml +AWSTemplateFormatVersion: 2010-09-09 + +Description: Workspace Manager, manage workspace creation & upgrades + +Metadata: + AWS::CloudFormation::Interface: + ParameterGroups: + - Label: + default: "Workspace Data" + Parameters: + - Name + - Version + - VersionSafe + - Hive + - UseRoute53 + - FoundationStackOutputPrefix + - AlternateURL + - InstallationDomainSsmValue + +Parameters: + Name: + Type: String + Description: Name of workspace + + AlternateURL: + Type: String + Description: Alternate URL for Workspace (Leave empty if not needed) + + Version: + Type: String + Description: Version + Default: "5.0.0" + + Hive: + Type: String + Description: Hive Name + + UseRoute53: + Description: Use Route 53 DNS Management + Default: true + Type: String + AllowedValues: [true, false] + + # This can be removed for simplicity + FoundationStackOutputPrefix: + Description: > + Name of the resource prefix used by the Turbot Foundation stack, which is + a prefix for exported outputs from that stack. + Type: String + Default: turbot + + InstallationDomainSsmValue: + Description: > + Name of the SSM Param that holds the installation domain name, which is + exported from the TEF foundation stack. + Type: "AWS::SSM::Parameter::Value" + Default: "/${FoundationStackOutputPrefix}/enterprise/installation_domain" + +Conditions: + UseRoute53DnsManagement: !Equals [true, !Ref UseRoute53] + CreateAlternateUrl: !Not [!Equals ["", !Ref AlternateURL]] + +Resources: + Workspace: + Type: Custom::CustomResource + Properties: + ServiceToken: + Fn::Sub: "arn:aws:lambda:${AWS::Region}:${AWS::AccountId}:function:${FoundationStackOutputPrefix}_workspace_manager" + WorkspaceId: !Ref Name + Version: !Ref Version + Hive: !Ref Hive + # This section is not normally required + Options: + FoundationStackOutputPrefix: !Sub "${FoundationStackOutputPrefix}" + + # + # Example how to use Route 53 to manage workspace DNS + # + # This is tricky, nesting Fn::Import within Fn::Sub, this article helps: + # + # https://www.fischco.org/technica/2017/cloud-formation-sub/ + # + WorkspaceDnsAlias: + Type: AWS::Route53::RecordSet + Condition: UseRoute53DnsManagement + Properties: + HostedZoneName: + Fn::Sub: + - "${hostedZone}." + - hostedZone: !Ref InstallationDomainSsmValue + Name: + Fn::Sub: + - "${workspace}.${hostedZone}." + - workspace: !Ref Name + hostedZone: !Ref InstallationDomainSsmValue + Type: CNAME + TTL: 30 + ResourceRecords: + - Fn::Sub: + - "${FoundationStackOutputPrefix}-${version}.${hostedZone}." + - version: !Join ["-", !Split [".", !Ref Version]] + hostedZone: !Ref InstallationDomainSsmValue + + # + # If the Param AlternateURL is set then create an SSM Parameter to match the url with the workspace. + # + WorkspaceParam: + Type: AWS::SSM::Parameter + Condition: CreateAlternateUrl + Properties: + Description: SSM Parameter the matching a workspace to a url + Name: !Sub "/${FoundationStackOutputPrefix}/tenant/${AlternateURL}" + Type: String + Value: + Fn::Sub: + - '{"hive":"${Hive}","id":"${Name}.${hostedZone}","name":"${Name}","version":"${Version}","schema":"${Name}","log_level":"debug","trace":"true"}' + - hostedZone: !Ref InstallationDomainSsmValue + + # + # Minute tick per workspace. + # + # NOTE: this needs to be replaced with a new design, the current per-workspace minute tick + # is not sustainable (limit on the number of rules) and not efficient, each minute we tick + # all the workspaces. + # + WorkspaceMinuteTick: + Type: AWS::Events::Rule + Properties: + Name: + Fn::Sub: + - "${WorkspaceId}_minute_tick" + - WorkspaceId: !Ref Name + Description: + Fn::Sub: + - "Minute tick scheduler for workspace ${WorkspaceId}" + - WorkspaceId: !Ref Name + ScheduleExpression: "cron(1/1 * * * ? *)" + State: ENABLED + Targets: + - Arn: + Fn::Sub: + - "arn:aws:sqs:${AWS::Region}:${AWS::AccountId}:${FoundationStackOutputPrefix}_${VersionSafe}_events" + - VersionSafe: + !Join [ + "_", + !Split [".", !Join ["_", !Split ["-", !Ref Version]]], + ] + Id: + Fn::Sub: + - "${WorkspaceId}_minute_tick" + - WorkspaceId: !Ref Name + InputTransformer: + InputPathsMap: + account: "$.account" + "detail-type": "$.detail-type" + detail: "$.detail" + id: "$.id" + region: "$.region" + resources: "$.resources" + source: "$.source" + time: "$.time" + version: "$.version" + InputTemplate: + Fn::Sub: + - > + { + "time":

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zGePCx(Q>L!1EN>QSb5U}83)~OoYjt%G5$?p?-Y&1NDk(}PrV-TuW;o=0%S^Z5pe$; z*<7b{Ok@DkiUpi z*%zRjS}m-oq+`HJy%1e~wt~uERu(EgqZ4|GO5*q+yn~78rhx$}e=%rFN<$|Uj{hnnUyNQ8@L5ml zE{`-Hga{;&AOA~pVdEPwO|20&WXcMN;#9j{{wSH%sl`A literal 0 HcmV?d00001 diff --git a/docs/enterprise/FAQ/general-purpose-gp3/index.md b/docs/enterprise/FAQ/general-purpose-gp3/index.md new file mode 100644 index 00000000..3f4a9ff5 --- /dev/null +++ b/docs/enterprise/FAQ/general-purpose-gp3/index.md @@ -0,0 +1,112 @@ +--- +title: "General Purpose SSD (gp3)" +template: Documentation +nav: + order: 30 +--- + +# General Purpose SSD (gp3) + +## When to use this guide? + +Use this guide to modify your RDS storage type to General Purpose SSD (gp3). + +## Why gp3 storage? + +AWS announced availability of General Purpose gp3 storage volumes for AWS RDS in November 2022. The new GP3 drives are +cheaper, higher performant and more flexible than `io1` and `gp2` storage. + +On gp3 for storage volumes less than 400GB, Amazon RDS provides a baseline storage performance of 3000 IOPS and 125 +MiBps, included with the price of storage. For storage volumes of 400GB or higher, the baseline storage performance +increases to 12,000 IOPS and 500 MiBps. This can be further scaled up to 64,000 IOPS for an additional cost. You can +find more details about gp3 +storage [here](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html#gp3-storage) and pricing +details [here]( +https://aws.amazon.com/rds/postgresql/pricing/#Database_Storage). + +## What is the process involved? + +The storage type change process is fairly smooth and involves the below steps: + +1. Disable the events from being processed. +2. Upgrade the TED product in Service Catalog to 1.28.0 version. +3. Enable the events. +4. Login to the workspace and perform a sanity check. + +## Disable the events + +We do not want to miss the events for the time period that database is under change. Hence, we hold the events in the +SQS backlog queue by deactivating the Lambda triggers. If you are running a multi TE setup, you need to hold the events +for all the TE versions that are pointing to the concerned hive. Navigate to AWS Lambda service and search for the +functions that have the suffix `_worker`, `_worker_priority` and `_worker_retry`. + +Below are some examples of how the Lambda Functions would look like: + +* `turbot_5_39_8_worker_priority` +* `turbot_5_39_8_worker` +* `turbot_5_39_8_worker_retry` + +In the above example, the installation prefix is "turbot" and the TE version pointing to the hive is 5.39.8. The prefix +or the TE version could be different from case to case. + +* Navigate to each of these Lambda functions and click on the "Configuration" tab. +* Select "Triggers" sub-tab. Look for the trigger corresponding to the function. +* Choose the trigger by clicking on the checkbox and click on Edit. +* In the "Trigger configuration" page, uncheck the "Activate trigger" option to disable the events. + +## Upgrade TED to 1.28.0 + +* In the primary (alpha) region of your installation, go to Service Catalog. +* Select the TED stack from the Provisioned products list. +* Select Actions > Update. +* Under Product versions, select the version v1.28.0 or higher. +* Under "Database - Advanced - Storage" section, update the necessary values as shown in the below example. + + If the Allocated Storage is less than 400GB: + + * Storage Type: gp3 + + * Provisioned IOPS: 0 + + * Storage Throughput: 0 + + ![gp3-baseline](/images/docs/guardrails/gp3-baseline.png) + + If the Allocated Storage is 400GB or higher: + + * Storage Type: gp3 + + * Provisioned IOPS: 12000 + + * Storage Throughput: 500 + + ![gp3-baseline-custom](/images/docs/guardrails/gp3-baseline-custom.png) + +* Scroll to the bottom of the page and click on "Update" to make the above changes to the provisioned product. + +When the storage or IOPS of an instance is changed, the RDS instance goes to "storage-optimization" state for about 6 +hours or until the optimization is done. The database is operational at this point but any changes you make to the +database will error out "InvalidDBInstanceState" until the DB comes back to "available" state. The CloudFormation stack +and the Service Catalog product will be in "Updating.." status till the database comes to "available" status. This is +normal. For more details, please visit +this [link](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PIOPS.StorageTypes.html#USER_PIOPS.ModifyingExisting). + +## Enable the events + +As soon as the database storage allocation changes are done, navigate to Lambda service and enable the triggers for the +functions which were disabled earlier. It is okay if the database is in "storage-optimization" state, you can enable the +events now. + +* Navigate to each of these Lambda functions and click on the "Configuration" tab. +* Select "Triggers" sub-tab. Look for the trigger corresponding to the function. +* Choose the trigger by clicking on the checkbox and click on Edit. +* In the "Trigger configuration" page, check the "Activate trigger" option to enable the events. + +This concludes the changes. The Guardrails console should be accessible, login should succeed and controls can be rerun. + +## Facing issues? + +Open a ticket with us on https://support.turbot.com and attach the below information. + +* A screenshot of the RDS instance's Configuration tab. +* A screenshot of the RDS instance's "Logs & events" tab showing the "Recent events". diff --git a/docs/enterprise/FAQ/index.md b/docs/enterprise/FAQ/index.md new file mode 100644 index 00000000..2c5f8f62 --- /dev/null +++ b/docs/enterprise/FAQ/index.md @@ -0,0 +1,565 @@ +--- +title: "FAQs" +template: Documentation +nav: + order: 80 +--- + +# Enterprise FAQs + +--- + +- [I do not use AWS - Can Turbot Guardrails Enterprise run in Azure, GCP, or in my own data center?](#i-do-not-use-aws---can-turbot-guardrails-enterprise-run-in-azure-gcp-or-in-my-own-data-center) +- [What AWS services does Turbot Guardrails Enterprise require?](#what-aws-services-does-turbot-guardrails-enterprise-require) +- [Do I need to use Route53 for Turbot Guardrails?](#do-i-need-to-use-route53-for-turbot-guardrails) +- [How does Turbot Guardrails use AWS Elastic Container Service (ECS)?](#how-does-turbot-guardrails-use-aws-elastic-container-service-ecs) +- [How does Turbot Guardrails secure local disk storage?](#how-does-turbot-guardrails-secure-local-disk-storage) +- [Do I need to use AWS ACM for the Turbot Guardrails Enterprise Certificate?](#do-i-need-to-use-aws-acm-for-the-turbot-guardrails-enterprise-certificate) +- [Do Turbot Guardrails Lambda functions run inside a VPC?](#do-turbot-guardrails-lambda-functions-run-inside-a-vpc) +- [Can Turbot Guardrails traffic be directed through an HTTP proxy?](#can-turbot-guardrails-traffic-be-directed-through-an-http-proxy) +- [What URIs does Turbot Guardrails need access to via a proxy?](#what-uris-does-turbot-guardrails-need-access-to-via-a-proxy) +- [My organization uses SSL/TLS inspection - is this supported for Turbot Guardrails Enterprise?](#my-organization-uses-ssltls-inspection---is-this-supported-for-turbot-guardrails-enterprise) +- [Does Turbot Guardrails support encrypted ECS AMIs?](#does-turbot-guardrails-support-encrypted-ecs-ami) +- [How do I update the AMI used by the ECS Hosts?](#how-do-i-update-the-ami-used-by-the-ecs-hosts) +- [How do I configure the Turbot Guardrails Load Balancer to log to my central logging bucket?](#how-do-i-configure-the-turbot-guardrails-load-balancer-to-log-to-my-central-logging-bucket) +- [Can Aurora be used instead of RDS for the Turbot Guardrails database?](#can-aurora-be-used-instead-of-rds-for-the-turbot-guardrails-database) +- [How to add launch constraint to Turbot Guardrails portfolio](#how-to-add-launch-constraint-to-turbot-guardrails-portfolio) +- [Would it be possible to have the Turbot Guardrails lambdas use the turbot_foundation kms key to encrypt the environment variables?](#would-it-be-possible-to-have-the-turbot-lambdas-use-the-turbotfoundation-kms-key-to-encrypt-the-environment-variables) +- [What does Service catalog provides over CloudFormation?](#what-does-service-catalog-provides-over-cloudformation) +- [How do I increase the connection timeout for the primary database?](#how-do-i-increase-the-connection-timeout-for-the-primary-database) +- [How do I increase the connection timeout for the Application Load Balancer (ALB)?](#how-do-i-increase-the-connection-timeout-for-the-application-load-balancer-alb) +- [Where does Turbot Guardrails store security and audit logs for failed login attempts to the console?](#where-does-turbot-guardrails-store-security-and-audit-logs-for-failed-login-attempts-to-the-console) +- [Is there one or more system/user accounts that exist in the enterprise database used by Turbot?](#is-there-one-or-more-systemuser-accounts-that-exist-in-the-enterprise-database-used-by-turbot) +- [How does the Turbot Guardrails application access its database?](#how-does-the-turbot-guardrails-application-access-its-database) +- [How do I update the Turbot Guardrails Enterprise license key?](#how-do-i-update-the-turbot-guardrails-enterprise-license-key) +- [Troubleshooting Long Running Lambda Workers](#troubleshooting-long-running-lambda-workers) +- [Do I need to use a wildcard certificate?](#do-i-need-to-use-a-wild-card-certificate) +- [How do I copy tags to Mod Lambdas and SNS topics?](#how-do-i-copy-tags-to-mod-lambdas-and-sns-topics) + +--- + +## I do not use AWS - Can Turbot Guardrails Enterprise run in Azure, GCP, or in my own data center? + +While Turbot Guardrails can manage resources in AWS, Azure, GCP, the Turbot Guardrails Enterprise installation must run +in AWS. Turbot also offers a Software-as-a-Service (SaaS) product that _does not_ require you to use AWS. + +## What AWS services does Turbot Guardrails Enterprise require? + +Turbot Guardrails Enterprise utilizes the following services in your Turbot master account: + +| Service | Purpose | +| -------------------- | --------------------------------------------------- | +| ACM | SSL/TLS Cert for the web console/api | +| API Gateway | Used for Event Listener | +| AWS Auto Scaling | Scale ECS containers | +| CloudFormation | Run CloudFormation templates from Service Catalog | +| CloudWatch | CloudWatch Events, Dashboards, and Logs | +| EC2 | ALBs and Security Groups | +| ECR | Repository for Turbot Container Images | +| ECS | EC2 Cluster for Turbot Core | +| Elasticache | Instance to cache data | +| IAM | Roles for Turbot | +| KMS | Encryption Keys | +| Lambda | Functions for setup and custom controls | +| Performance Insights | Monitor the RDS instance | +| RDS | Postgres Database | +| Route 53 | Hosted zone with records for Turbot Workspaces | +| S3 | Bucket for logging | +| Service Catalog | Share Turbot product CloudFormation templates | +| SNS | Topics used for sending events to Turbot | +| SQS | Event Queue | +| SSM | Parameter Store for installation configuration data | + +## Do I need to use Route53 for Turbot Guardrails? + +It is recommended that you allow Turbot to manage DNS records in Route53 as it +greatly simplifies the deployment and upgrade process, however you are not +required to do so. + +If you elect to use your own DNS infrastructure, you will need to +[update DNS records every time you install a new version in your workspaces](enterprise/installation/post-installation#update-dns-records). + +## How does Turbot Guardrails use AWS Elastic Container Service (ECS)? + +The Guardrails ECS clusters are run in private VPCs with no task or service publicly +accessible. Guardrails has three types of containers that run in ECS: + +1. **API Containers**: These are long-running containers that have inbound + connectivity from the ALB and serve API requests. +2. **Events Containers**: Responsible for ingesting incoming events from managed cloud accounts. Enables the Guardrails + real-time event model. +3. **Terraform Factory Containers**: Single use containers that compose Terraform + templates dynamically and are terminated at the end of execution, which is + typically less than 1 minute. + +## How does Turbot Guardrails secure local disk storage? + +API Container root filesystems are mounted as read-only, and no additional +volumes are attached to an ECS task. + +Terraform Factory Containers use the local filesystem to dynamically compose a +Terraform template and then execute a Terraform plan and apply. These containers +have no inbound connectivity and are terminated at the end of their task. + +## Do I need to use AWS ACM for the Turbot Guardrails Enterprise Certificate? + +Yes, customers will need an ACM certificate, even if DNS is hosted by the +organization. + +- The ACM certificate must exist in the same region as the Turbot Guardrails Enterprise + installation. +- The certificate domain name must match the Installation Domain Name. +- The certificate must have an additional name that is a wildcard for the + Installation Domain Name + +## Do Turbot Guardrails Lambda functions run inside a VPC? +Turbot Guardrails Lambda functions fall into two categories: Management Lambdas and Mod Lambdas. +Management Lambdas are deployed by the TEF, TED and TE stacks. These are always deployed inside the Guardrails VPC. +Mod Lambda functions generally interact directly with cloud +service providers. They are not connected to a VPC for improved performance and +efficient use of VPC IP space. + +As of [Turbot Guardrails Enterprise 5.20.0](releases/te#5200-2020-05-28), Guardrails supports +running Mod Lambdas within a VPC. This is primarily aimed at organizations wishing +to inspect and control all network traffic. + +## Can Turbot Guardrails traffic be directed through an HTTP proxy? + +Guardrails has the ability to run behind a proxy, as long as it can still reach +cloud service provider APIs via that outbound internet access proxy. +[Proxy options](enterprise/installation/tef-installation#network---proxy) can be +selected during [installation](enterprise/installation), or can be updated by +re-running the [TEF](enterprise/installation/tef-installation) and +[TE](enterprise/installation/te-installation) stacks. + +Please note that typically the HTTPS proxy points at an `http://address:port` to +avoid certificate issues. Note also that `169.254.169.254` should be in the +`NO_PROXY` list, as it is a static route used to reach AWS internal metadata +service. + +Some AWS services are not proxy-aware. If using a proxy, you must also create +VPC endpoints to allow EC2 to access the following AWS services: + +- ECR API +- ECR DKR +- CloudWatch Logs +- S3 + +## What URIs does Turbot need access to via a proxy? + +Amazon Web Services URIs must be accessible for the local Turbot master account +regardless of the cloud service providers you are using Turbot to manage: + +- `https://*.amazonaws.com` +- `https://signin.aws.amazon.com` + +The web proxy/filter that Turbot connects to must whitelist the following URIs +for access to each cloud service: + +**Amazon Web Services** + +- `https://*.amazonaws.com` +- `https://signin.aws.amazon.com` + +**Microsoft Azure** + +- `https://login.microsoftonline.com` +- `https://login.windows.net` +- `https://management.azure.com` +- `https://graph.windows.net` + +**Google Cloud Platform** + +- `https://accounts.google.com` +- `https://*.googleapis.com` + +Alternatively, you can micro-segment if needed + +- `https://accounts.google.com` +- `https://www.googleapis.com` +- `https://cloudresourcemanager.googleapis.com` +- `https://logging.googleapis.com` +- `https://servicemanagement.googleapis.com` +- `https://iam.googleapis.com` + +## My organization uses SSL/TLS inspection - is this supported for Turbot Guardrails Enterprise? + +Guardrails does not currently support the use of MITM SSL interception proxies. Customers requiring traffic +introspection should use a Proxy instead. Guardrails uses several AWS services that do not support inclusion +of the third party certificates necessary for these solutions to work. You will need to create exceptions +for the VPC hosting Guardrails to allow outbound traffic to AWS, GCP, and Azure API endpoints. + +## Does Turbot Guardrails support encrypted ECS AMI? + +Turbot Guardrails uses the Amazon Linux 2 AMI for ECS hosts by default. Customers +requiring encrypted EBS volumes for the Guardrails ECS hosts can use one of two approaches: + +**EBS Default Encryption** +1. Enable "Default KMS Key for EBS Encryption" using the AWS + [instructions](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSEncryption.html). + Ensure the CMK has + [sufficient permissions](https://docs.aws.amazon.com/kms/latest/developerguide/services-ebs.html#ebs-cmk). +2. Create a new SSM parameter `/turbot/enterprise/ecs_ami` with the value of the + AMI created in the previous step. +3. Update the TEF template from Service Catalog. +4. In the TEF template, replace the value of `ECSAMI` with + `/turbot/enterprise/ecs_ami`. +This approach assumes an unencrypted AMI but the resulting volumes are encrypted by default. +No special considerations for the AMI need to be made beyond using a recent release. + +**Create an Encrypted AMI** + +1. Create an encrypted Amazon Linux 2 AMI using these + [instructions](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/CopyingAMIs.html). + Ensure the CMK has + [sufficient permissions](https://docs.aws.amazon.com/kms/latest/developerguide/services-ebs.html#ebs-cmk) + that the ECS and Autoscaling services can decrypt the volumes. +2. Create a new SSM parameter `/turbot/enterprise/ecs_ami` with the value of the + AMI created in the previous step. +3. Update the TEF template from Service Catalog. +4. In the TEF template, replace the value of `ECSAMI` with + `/turbot/enterprise/ecs_ami`. + - In the event of a rollback, the default value is: + `/aws/service/ecs/optimized-ami/amazon-linux-2/recommended/image_id` +5. Finish updating the TEF template. + - Cloudformation will do a rolling update of the ECS hosts. No downtime is + expected. +6. Verify that the EC2 instances have restarted and are using the new encrypted + AMI. +7. Verify that the Turbot console is working and events are being processed. + +### Ongoing Maintenance when using encrypted AMI Customers with encrypted + +Volumes should follow the [Amazon Linux 2 release notes](https://aws.amazon.com/amazon-linux-2/release-notes/). +On a periodic basis, a new AMI should be rebuilt to include the latest +updates. + +## How do I update the AMI used by the ECS Hosts? + +The AMI used by the Guardrails ECS hosts can be updated independent of a TEF version upgrade. + +1. In Service Catalog, go to Provisioned Products. +2. Select the TEF stack. +3. In the top right corner, under the "Actions" menu, choose "Update". +4. A big list of TEF releases will appear. If your intent is to only update ECS AMIs, then choose the currently deployed + TEF version. +5. In the TEF stack, there's a parameter called "AMI type for EC2 ECS host". The default value + is `/aws/service/ecs/optimized-ami/amazon-linux-2/recommended/image_id`. + 1. If you're still using the custom AMI, then you'll need to update the AMI cited in the SSM parameter to the newest + golden ECS AMI. + 2. AWS automatically updates the value of the ECS Recommended Image ID. +6. If it's the standard AWS ECS AMI, then scroll down to the "Parameter Deployment Trigger" and toggle it from Blue to + Green or Green to Blue. +7. Click the orange Update button at the bottom. +8. CloudFormation will update the TEF ASG Launch Template to use the current value of the ECS AMI SSM parameter. Wait + 10-ish minutes for the ASG to do its thing. When the TEF stack completes, you'll be running the latest ECS AMIs. + +## How do I configure the Turbot Guardrails Load Balancer to log to my central logging bucket? + +Some customers may wish to specify an alternate logging bucket for the Guardrails +Load Balancers (ALB); this answer describes how to override the default value +when installing a new version of Turbot Guardrails Enterprise (TE). + +When installed, the TE Product creates an ALB and enables access logging to an +existing bucket that was created as part of the TEF install. The default bucket +name is stored in the ssm parameter: `/turbot/enterprise/log_bucket`. When +installing the TE stack you can override the value of this SSM Parameter to a +predefined bucket. To do so, follow the same process you would use for a Turbot +Guardrails Enterprise upgrade: + +1. Navigate to the AWS Service Catalog service +2. Choose `Products` > `Turbot Guardrails Enterprise` > `Launch Product` +3. Select a version +4. Name the product and click `Next` +5. Scroll down to the section named: `Advanced - TEF Overrides` +6. Look for the param named `Log Bucket Name` +7. Specify the name of your custom bucket. (Notice: Your custom bucket must have + a bucket policy that allows the AWS ALB service to log to that bucket) +8. Finish any other TE configuration needed and launch the product. +9. The ALB created by the stack will use your specified bucket for logging. + +## Can Aurora be used instead of RDS for the Turbot Guardrails database? + +No. Guardrails makes extensive use of the `ltree` extension in Postgres for +hierarchy management. That extension is not currently supported in Aurora. + +## How to add launch constraint to Turbot Guardrails portfolio + +Log into the AWS account with the portfolio share. Navigate to Service Catalog, +then click the `Portfolios` tab in the `Administration` section, and finally +click the `Imported` tab. + +Click the Turbot portfolio. You should now see the TEF, TED, and TE products. At +this point, select one product by clicking the product name, then click Actions, +then Copy product. Select the same region which the portfolio currently resides +and click ok. + +After a few moments the product should appear under the Administration product +list. From here, you can create a local portfolio and add the copied products. +To apply a launch constraint to this new, local portfolio, Please refer to +[AWS Documentation](https://docs.aws.amazon.com/servicecatalog/latest/adminguide/constraints-launch.html). + +## Would it be possible to have the Turbot lambdas use the turbot_foundation kms key to encrypt the environment variables? + +turbot_foundation kms keys are only used for short term encryption data that +flows through SNS/SQS and not to encrypt the Turbot Lambda’s environment +variables. + +## What does Service catalog provides over CloudFormation? + +Service catalog allows us to distribute a bundle of lambdas, containers etc. So +there is only one bundle to distribute instead of many things separately. It +uses CFN behind the scene. The benefit if it is that we can simply publish new +versions of TEF, TED and TE to the catalog, making it easy for customers to +install/upgrade. + +## How do I increase the connection timeout for the primary database? + +If you're getting the error `Network error: Unexpected token < in JSON` at +position 0 when doing something heavy, like importing a large account, you may +need to increase the connection timeout for the primary database. Anytime we +increase the connection timeout, we want to be reasonable about the increase +(e.g., go from 1 minute to 2 minutes, not 1 minute to 60 minutes) + +- In the primary (alpha) region, go to Service Catalog. +- Select the TED stack from the Provisioned products list (note the version). +- Select `Actions > Update`. +- On the first update page, keep the version the same as what it's currently at + and select `NEXT`. +- Find the parameter `Maximum Allowed Duration of Statement` and then increase + it accordingly (2 minutes is a safe first update, so 120000). +- Select `NEXT` and then `UPDATE` to apply the change. Once the DB has updated + with the newly updated param group, you can try the action again. If you want + the UI / API to not timeout, you should make the ALB timeout match. + +**Note**: Don't forget, once you are done with the blocked action, revert these +changes immediately. + +## How do I increase the connection timeout for the Application Load Balancer (ALB)? + +Changes to the ALB and ECS container timeouts are best done concurrently with updates to +the TED `statement_timeout` parameter. ALB and ECS Container timesout are specified via SSM +parameter, as there is no parameter in the TE Serivce Catalog product to increase +HTTP timeout. The ECS containers look for the SSM parameter +called `/${ResourceNamePrefix}/overrides/enterprise/alb_idle_timeout` on launch to +establish their internal HTTP timeouts. + +1. Create a new SSM Parameter in the AWS region that hosts the Guardrails install. + This can be done manually, via CFN, Terraform, or by whatever method is preferred. + For convenience, a CloudFormation template can be found below. + Override the value to match the DB's statement_timeout parameter; `300` seconds is common. + The default value for `${ResourceNamePrefix}` is `turbot`. + +```yaml +AlbIdleTimeoutParameter: + Type: AWS::SSM::Parameter + Properties: + Name: !Sub "/${ResourceNamePrefix}/overrides/enterprise/alb_idle_timeout" + Description: "ALB Idle Timeout" + Type: String + Value: 130 +``` + +2. Update the TE stack, flipping the Blue/Green parameter to force a + re-evaluation of the SSM parameters. +3. The ECS containers for this TE stack should bounce. +4. After the TE stack finishes with the update, test again. + +When you update the TE stack, the ALB's parameters are updated. Importantly, the +timeout parameters are also updated on the HTTP services running on the API +containers. If you manually edit the ALB only, the API containers will still +have the default value of 120 seconds. + +**Note**: Don't forget, this should not be a permanent change, so revert these +changes as soon as possible. Consult with Turbot Support if this becomes a long term +requirement. +**Note**: The shortest timeout between the DB, ALB and ECS containers dictates +the maximum timeout for an HTTP call. + + +## Where does Turbot Guardrails store security and audit logs for failed login attempts to the console? + +Turbot API calls, including failed login attempts are logged to a CloudWatch Log +Group. The name is of the form `/turbot/{hive}/api/audit`. The log stream name +is the workspace name, followed by a prefix, and by TE version. Like this +`acme_turbot_5_34_5_7ec6b4b0`. Here is an example of a failed login (401 +response) from one of our workspace. + +``` +{ + "id": "b50002ed-da79-4a67-ad46-ab944325067b", + "processId": null, + "workspace": "acme-turbot.cloud.turbot.com", + "version": "5.34.4", + "eventTimestamp": "2020-12-11T20:55:42.318Z", + "type": "api.turbothq.com:CreateTurbotDirectoryProfileToken", + "detail": { + "source": { + "ipAddress": "173.54.210.135", + "userAgent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36", + "proxyIpAddresses": [ + "173.54.210.135" + ] + }, + "request": { + "method": "POST", + "protocol": "https", + "host": "acme-turbot.cloud.turbot.com", + "path": "/api/v5/directories/198049522322404/local/callback", + "params": { +``` + +## Is there one or more system/user accounts that exist in the enterprise database used by Turbot Guardrails? + +- There is a `master user` (standard in all PostgreSQL DBs) and the `turbot user` created as a part of +initial DB configuration during TED deployment. +- We only use `master user` for setup, and reset it + automatically when needed. No one knows the master password, if we need to use + the master password we usually reset it first, and then use it. We don't + store the password. +- The `turbot user` doesn't have password, we use the `RDS IAM Authentication` + to connect to the database. + +## How does the Turbot Guardrails application access its database? + +- Guardrails uses the `turbot user` through IAM authentiation for general application operation. +- The `master user` is used for initial setup. + +## How do I update the Turbot Guardrails Enterprise license key? + +The Turbot Guardrails Enterprise license key will need to be occasionally rotated. This can +be done via the Turbot Service Catalog portfolio. + +1. Log into the AWS account with the Turbot installation and sufficient rights + to update the Service Catalog product. +2. Select the Turbot Guardrails Enterprise Foundation (TEF) provisioned product, click + **Actions** in the top right, then select **Update**. +3. Scroll down to the Parameters and find the **Turbot License Key**. Paste the + key into the text field. Note that all line breaks will need to be removed + prior to pasting in the value! +4. Scroll to the bottom of the page and click **Update**. Click through the + following page(s) to confirm the update. +5. Once the product moves back into the `Available` status, log into the Turbot + console with admin permissions. +6. Select the **Controls** tab at the very top of the console, then search + `Workspace Usage`. +7. Click the `Turbot > Workspace > Usage` option. + +![](/images/docs/guardrails/workspace-usage.png) + +8. On the **Control Type** page, click the **Controls** tab under the control + type name. Click the `Turbot > Workspace > Usage` control. +9. Click the **Actions** button then **Run Control**. +10. That's it! If the control does not go into the OK state, try waiting ~15-20 + seconds and running the control again. If the control goes into error and + stays there, contact [Customer Support](mailto:help@turbot.com). +11. The `Turbot > Workspace > Usage` control will need to be ran in each + workspace associated with the AWS Master account. + +## Troubleshooting Long Running Lambda Workers + +Queries can sometimes cause the Worker Lambda to run long or time out. These +show up as the red line in the Worker Lambda - Duration widget in the TE +Cloudwatch dashboard. Ideally, all queries would run very fast, less than 2 +seconds. Long-running queries can be an early warning indicator of scalability +concerns or bugs. + +[Turbot Guardrails Enterprise 5.35.0](releases/te#v5350-2021-01-22) added graph lines for +`Average`, `p90`, `p99` and `Maximum` in Worker Lambda - Duration widget. The +bigger the spread between across all graphs, the greater percentage of worker +runs are taking a long time. Brief increases due to heavy DB load are expected. +The below instructions are targeted at persistent, and/or periodic long-running +worker runs. + +The provided queries are tuned for hunting down queries that take over two +minutes, but can be used to troubleshoot any duration. Workers time out at 7.5 +minutes or 450,000ms. The default RDS `statement_timeout` period is 60000 ms. Be +aware that the shorter one sets the `@duration` value, the more results there +will be. + +In order to find the long-running worker runs, do the following: + +1. Go to the Log Insights page in the Cloudwatch dashboard in the primary region + of the Turbot Master account. Search for the log group named + `{resource_prefix}_worker\_5\_{minor}_{patch}`. You want to be searching + through the appropriate logs. + +2. Get list of long-running queries by searching through the worker CloudWatch + logs: The value of `120000` can be adjusted to whatever value is required. + +``` +fields @timestamp, @message +| filter ispresent(@duration) and @duration > 120000 +| sort @timestamp desc +| limit 20 +``` + +3. Copy the request ID into the @requestId field in the below query + +``` +fields @timestamp, @message +| filter ispresent(@requestId) and @requestId like "55f48b1d-70c6-57af-9848-d31f9e505116" +| sort @timestamp desc +| limit 100 +``` + +4. The request record from step 2 will have resource, policy and control IDs. + Look those up in the Turbot console. + + - Controls: `{turbot_host_name}/controls/{controlID}` + + - Resources: `{turbot_host_name}/resources/{resourceID}` + +5. Troubleshoot from there. + +Long worker lambda times can be attributed to database load, network congestion, +policy values, scope, and more. If Lambda duration continues to be an issue +after investigation, reach out to [Turbot Support](mailto:support@turbot.com) + +## Do I need to use a wildcard certificate? + +No. While Turbot recommends a wildcard certificate to simplify configuration and +adding new workspaces, it is not strictly required. Those customers with a +private ALB and an API gateway must generate a single certificate with an entry +for each workspace hosted on the TEF deployment and for the API gateway. Even if the +`gateway.{installation.domain.name}` hostname won't be used for event handling because of DNS +considerations, it must still be included in the certificate. +For an installation with a single workspace and an API gateway, the certificate must contain: + +``` +{console_a}.{installation.domain.name} +gateway.{installation.domain.name} +``` + + For an installation with multiple workspace and an API gateway, the single +certificate must contain: + +``` +{console_a}.{installation.domain.name} +{console_b}.{installation.domain.name} +{console_n}.{.installation.domain.name} +gateway.{installation.domain.name} +``` + + For an installation with a public ALB, the +`gateway.{installation.domain.name}` entry can be excluded. The value of +`{installation.domain.name}` must match the value provided to the +"Installation Domain Name" parameter in the TEF stack. The `{console}` value +must match the workspace parameter in the Workspace CFN template. + + +## How do I copy tags to Mod Lambdas and SNS topics? +Guardrails will automatically copy the tags applied to the Service Catalog Turbot Guardrails Enterprise Foundation (TEF) product over to the Mod Lambdas and SNS topics. This process does not require TEF/TED/TE version updates. +1. Log into your Turbot Master account then head over to Service Catalog. +2. Identify the TEF product in the Provisioned Products list. +3. Update the TEF product. Stay on the current version. +4. Scroll all the way to the bottom. You'll see a place to put in your tags. +5. Set the required tag keys and values. +6. Click "Update". +7. When the TEF stack has finished updating, switch over to the Guardrails console. +8. The Type Installed controls are responsible for deploying the SNS topics and Lambda functions that execute each control. They are also responsible for copying the tags from the TEF stack. +9. Run all the `Turbot > Mod > Installed` controls at 5 minute intervals. This will download the zip file that holds the Lambda code. The zip file must be present in order to run the Type Installed controls. Running a `Turbot > Mod > Installed` control automatically reruns the `Turbot > Type Installed` controls for that mod. + - The easiest way to run all the Turbot > Mod > Installed controls is with the run_controls_batches script found in the [Guardrails-Samples Repo](https://github.com/turbot/guardrails-samples/tree/master/api_examples/graphql/clients/python/run_controls_batches). + - `python run_controls_batches.py -b 1 -d 300 --filter "controlTypeId:'tmod:@turbot/turbot#/control/types/modInstalled'"` +10. Some `Turbot > Type Installed` controls may be in an `error` state with an error message like "Rate Exceeded". Rerun those Type Installed controls. + - `python run_controls_batches.py -b 10 -d 60 --filter "controlTypeId:'tmod:@turbot/turbot#/control/types/controlInstalled' state:error"` diff --git a/docs/enterprise/FAQ/monitoring-alarms/index.md b/docs/enterprise/FAQ/monitoring-alarms/index.md new file mode 100644 index 00000000..50f95c37 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/index.md @@ -0,0 +1,28 @@ +--- +title: "Monitoring and Alarms" +template: Documentation +nav: + order: 40 +--- + +# Monitoring and Alarms + +As a part of effective monitoring, the TEF, TED and TE products include +CloudWatch dashboards and alarms. This guide will walk through some of the +CloudWatch Alarms as well pointers to the alarm SNS topics. + +You can find the complete list of CloudWatch Alarms in +`AWS > CloudWatch > All Alarms` under the alpha region of the installation. Upon +opening the CloudWatch Alarm Details, it will give you information about what +the alarm is looking for, the interval and the threshold. + +Based on the Alarm conditions, all the alarms have an action to send a +notification to a SNS Topic. The notifications for TEF and TE alarms are pushed +to the SNS Topic `turbot_alarms` whereas the notifications for TED alarms are +pushed to the SNS Topic `turbot__alarms` (example: +`turbot_newton_alarms`). Please make sure to subscribe to these two SNS Topics. + +Details for each product. + +- [TE](enterprise/FAQ/monitoring-alarms/te) +- [TED](enterprise/FAQ/monitoring-alarms/ted) diff --git a/docs/enterprise/FAQ/monitoring-alarms/te/elb-5xx-errors.md b/docs/enterprise/FAQ/monitoring-alarms/te/elb-5xx-errors.md new file mode 100644 index 00000000..364efe53 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/te/elb-5xx-errors.md @@ -0,0 +1,41 @@ +--- +title: "ELB 5xx errors" +template: Documentation +nav: + title: "ELB 5xx errors" + order: 30 +--- + +# ELB 5xx errors + +**AlarmName**: `__elb_5xx_error_alarm` (example: `turbot_5_40_0_elb_5xx_error_alarm`). + +**Description**: Incoming requests to the ALB, including both UI and events. + +**Condition**: HTTPCode_ELB_5XX_Count >= 3 for 1 datapoints within 1 minute. + +**Healthy**: Steady low traffic with occasional bursts for online users. + +**Event flood**: Sustained high volume of requests, indicating a noisy publisher. + +**Instability**: Many 5XX errors, continuing over time. + +## Troubleshooting + +We can get 5XX errors when the status checks for underlying EC2 host machine fail or the instance loses network +connectivity. Though these are rare, once the health check of the instance fails, the autoscaling will immediately +launch a new instance and replace the faulty instance. + +If the 5XX errors have nothing to do with the status checks of the EC2 instance then navigate to CloudWatch and search +for the API log group of the current TE installation (example: `/turbot/5_40_0/api`). For the given time period, please +check if there are any errors in the API log group and share the same with Turbot Support. + +### Need help? + +Please reach out to [Turbot Support](mailto:help@turbot.com) with the collected information. + +* The current TE version being used. +* CloudWatch logs from API log group `/turbot/5_40_0/api`. +* A screenshot of the CloudWatch TE Dashboard with the widgets "Load Balancer" and "Guardrails Response Time" under + the "API" section. +* A screenshot of the `Instance Management` tab from the `EC2 > Auto Scaling groups > turbot-auto-scaling-group` window. diff --git a/docs/enterprise/FAQ/monitoring-alarms/te/events-queue-backlog.md b/docs/enterprise/FAQ/monitoring-alarms/te/events-queue-backlog.md new file mode 100644 index 00000000..91f24601 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/te/events-queue-backlog.md @@ -0,0 +1,77 @@ +--- +title: "Events Queue Backlog" +template: Documentation +nav: + title: "Events Queue Backlog" + order: 60 +--- + +# Events Queue Backlog (Count) + +**AlarmName**: `__events_queue_messages_visible_alarm` +(example: `turbot_5_40_0_events_queue_messages_visible_alarm`). + +**Configuration**: The Lambda reserved concurrency is configured in the +"Advanced - Worker" section of TEF. All the new TE installations will pick the +value from the TEF. You can also over ride this value at the TE by giving it a +new value. When making any changes to the `WorkerLambdaReservedConcurrency` at +the TEF, please remember to flip the "Parameter Deployment Trigger" of the TE +from Blue to Green or vice-versa. + +**Condition**: ApproximateNumberOfMessagesVisible >= 5000 for 3 datapoints +within 15 minutes. + +**Healthy**: Backlog (red) and running tasks (orange) are low (often zero) with +short buildups (< 30 mins) associated with events like resource imports, mod +updates, etc. + +**Overloaded**: Sustained backlog growth (red) indicating that ECS workers +cannot keep up with incoming events. Increase capacity or check for a flood of +unnecessary events. + +**Stalled processing**: Running tasks (orange) appear for long periods. +Typically indicates a misconfigured mod failing to terminate the task. + +## Troubleshooting + +- **How many events are in the events queue?**: 10K, 100K, 1 million? +- **When did the event backlog start?**: To the nearest 15 minutes, when did the + backlog start? +- **Worker Concurrency**: Is the worker concurrency maxed out? +- **Policy Changes**: Were any policy changes made before the start of the + backlog? +- **Guardrails Master Changes**: Were any changes made to the Guardrails application? + +Answer to these questions will come from the Turbot Guardrails Enterprise (TE) Cloudwatch +dashboard. + +If the backlog is not consistent and can be co-related to an activity that was +just performed on the workspace, then no action is needed. Give it some time for +the backlog to clear. Activities such a installing/upgrading a mod, importing an +account, setting a policy that effects thousands of resources usually generates +a lot of queue backlog and should settle down soon. + +Crosscheck the settings of the environment and make sure there is no +misconfiguration. The Lambda Concurrency should not be too high and should be +fine tuned by observing for a couple of days. Lambda concurrency of 80 is a safe +number, but depends on the size of the installation. Also look for the TEF +parameters `WorkerLambdaMessageBatch` and `WorkerLambdaMaxDBConnections`, these +should be the same value and most of the time it is 2. It is configured to 4 in +rare occasions. The lambda concurrency should not be too high to overwhelm the +DB connections. Keep an eye on the number of DB connections when you are +increasing the lambda concurrency. + +If the backlog is consistent and you see a pattern in the backlog queue getting +flooded, please refer to the +[event flood](enterprise/troubleshooting/event-flood) documentation. + +### Need help? + +Please reach out to [Turbot Support](mailto:support@turbot.com) with the +following information on your Guardrails environment: + +- Turbot Guardrails Enterprise (TE) Version(s)?: (e.g. v5.40.0) +- Turbot Guardrails Master Account: (e.g. 111222333444) +- The `WorkerLambdaMessageBatch`, `WorkerLambdaMaxDBConnections` and + `WorkerLambdaReservedConcurrency` parameter values from TEF. +- A screenshot of the events queue backlog in CloudWatch. diff --git a/docs/enterprise/FAQ/monitoring-alarms/te/index.md b/docs/enterprise/FAQ/monitoring-alarms/te/index.md new file mode 100644 index 00000000..f97aebc6 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/te/index.md @@ -0,0 +1,18 @@ +--- +title: "TE" +template: Documentation +nav: + title: "TE" + order: 10 +--- + +# Monitoring and Alarms - TE + +The alarms related to TE are forwarded to the SNS Topic `{prefix}_alarms` (example: `turbot_alarms`). Please make sure to subscribe to the SNS Topic for notifications. + +Below are the list of supported alarms for Turbot Guardrails Enterprise. + +* [ELB 5xx errors](te/elb-5xx-errors) +* [Events Queue Backlog](te/events-queue-backlog) +* [Guardrails Response Time](te/turbot-response-time) +* [Worker Lambda duration](te/worker-lambda-duration) diff --git a/docs/enterprise/FAQ/monitoring-alarms/te/turbot-response-time.md b/docs/enterprise/FAQ/monitoring-alarms/te/turbot-response-time.md new file mode 100644 index 00000000..77890b13 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/te/turbot-response-time.md @@ -0,0 +1,39 @@ +--- +title: "Guardrails Response Time" +template: Documentation +nav: + title: "Guardrails Response Time" + order: 90 +--- + +# Guardrails Response Time + +**AlarmName**: `__turbot_response_time_alarm` (example: `turbot_5_40_0_turbot_response_time_alarm`). + +**Description**: Response Time for API & UI requests to the ALB. + +**Condition**: TargetResponseTime >= 3 for 1 datapoints within 1 minute. + +**Healthy**: Steady, low response times below 1s. Includes periods with no data / traffic. + +**Hot Spots**: Spikes of slow performance, indicating overloading or slow handling. + +## Troubleshooting + +Go to CloudWatch Insights and filter for the log group `/turbot/{hive}/api/audit` and run the following query. The below +will give long-running queries, please share the same with Turbot Support so that we can troubleshoot further and +fine tune the queries. + +``` +fields @timestamp, detail.request.body.operationName as Operation, detail.request.host as workspace, toMillis(@ingestionTime-@timestamp) as duration, @message +| filter toMillis(@ingestionTime-@timestamp) > 2000 +| sort @timestamp desc +| limit 100 +``` + +### Need help? + +Please reach out to [Turbot Support](mailto:support@turbot.com) with the collected information. + +* The current TE version being used. +* A screenshot of the widget "Guardrails Response Time" under the "API" section of the CloudWatch TE Dashboard. diff --git a/docs/enterprise/FAQ/monitoring-alarms/te/worker-lambda-duration.md b/docs/enterprise/FAQ/monitoring-alarms/te/worker-lambda-duration.md new file mode 100644 index 00000000..4e9be3f7 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/te/worker-lambda-duration.md @@ -0,0 +1,39 @@ +--- +title: "Worker Lambda Duration" +template: Documentation +nav: + title: "Worker Lambda Duration" + order: 100 +--- + +# Worker Lambda duration + +**AlarmName**: `__worker_lambda_duration_alarm` (example: `turbot_5_40_0_worker_lambda_duration_alarm`). + +**Configuration**: The amount of time that worker lambda function code spends processing an event. The billed duration for an invocation is the value rounded up to the nearest millisecond. The "Timeout for Worker Lambda" is configured in the "Advanced - Worker" section of TEF. All the new TE installations will pick the value from the TEF. You can also over ride this value at the TE by giving it a new value. When making any changes to the `WorkerLambdaTimeout` at the TEF, please remember to flip the "Parameter Deployment Trigger" of the TE from Blue to Green or vice-versa. + +**Condition**: Duration >= 350000 for 1 datapoints within 1 minute. + +**Healthy**: All metrics are consistently low with a relatively small difference from Average to p90 and p99. Occasional, non-periodic spikes on the Max metric are okay. + +**Periodic Slow Running Queries**: If the max metric is high but all other metrics are low, this indicates that a single or small set of queries are taking a long time. Investigate by looking at the Worker Lambda CloudWatch for durations matching the Max metric. + +**Large Spread in Metrics**: A large spread in metrics from Avg to p90, p99 and Max indicates a greater portion of Worker Lambda runs are taking longer. + +## Troubleshooting + +This is the duration taken for Lambda function execution. The worker lambda has a max timeout in seconds defined by the parameter `WorkerLambdaTimeout` (defaults to 350 seconds) and the executions are supposed to finish within these 350 seconds. + +* The function duration take take long for various reasons. Always make sure the DB is not overwhelmed and there is enough room for CPU/memory. +* The lambda concurrency is too high and trying to process to many executions than the DB can actually handle. +* The SQS queue is pushing too many messages to the lambda causing a delay in executions. Try to make use of the "SQS Trigger concurrency" to set the concurrency for Lambda SQS Triggers. This should not be higher than the Lambda concurrency. +* If there are too many messages at all times, probably the environment is too busy and there are multiple workspaces pointing to the same TE version. It is recommended to use multiple TEs to split the load evenly. +* There could be a mod or a query that is consuming too much time to finish, though the DB utilization is under threshold. Please pass on the query to Turbot Support so that we can fine tune the query. + +### Need help? +Please reach out to [Turbot Support](mailto:support@turbot.com) with the collected information. + +* The current TE version being used. +* The `WorkerLambdaTimeout` parameter value from TEF and `WorkerLambdaTimeoutSsmValue` parameter value from TE. +* A screenshot of the CloudWatch TE Dashboard with the widgets "Events Queue Activity", "Events Queue Backlog" and "Worker Lambda - Duration". +* A screenshot of the CloudWatch TE Dashboard with all the widgets/tables under the "Activities" section. diff --git a/docs/enterprise/FAQ/monitoring-alarms/ted/cpu-utilization.md b/docs/enterprise/FAQ/monitoring-alarms/ted/cpu-utilization.md new file mode 100644 index 00000000..02e548e9 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/ted/cpu-utilization.md @@ -0,0 +1,40 @@ +--- +title: "CPU Utilization" +template: Documentation +nav: + title: "CPU Utilization" + order: 30 +--- + +# CPU Utilization (Percent) + +**AlarmName**: `__cpu_util_alarm` (example: `turbot_einstein_cpu_util_alarm`) + +**Configuration**: You can change the CPU and memory available to a DB instance by changing its +DB [instance class](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.DBInstanceClass.html). The DB +Instance class is configured in the "Database - Configuration" section of TED. + +`InstanceClass`: Instance Type for DB. Defaults to db.t3.small but almost all production installations have a basic +graviton instance. + +**Condition**: CPUUtilization >= 70 for 3 datapoints within 15 minutes + +**Healthy**: The Hive CPU is overloaded when it is consistently above 50% or higher. + +**Under-provisioned**: When there are no errors in Guardrails operations and CPU is very high, the Hive instances may be +too small for the workload. + +**Over-provisioned**: When CPU is consistently very low and the largest load spikes are below 50%. + +## Troubleshooting + +If you are seeing spikes in CPU utilization, check the performance insights of the database. Check for the Top SQL +running on the database. See if there are any custom mods in place or any queries that are using free search query. +Share the query with Turbot Support so that the team can fine tune it wherever possible. + +### Need help? + +Please reach out to [Turbot Support](mailto:support@turbot.com) with the collected information. + +* A screenshot of the RDS instance's Configuration tab. +* A screenshot of the RDS instance's Monitoring tab showing the "CPU Utilization (Percent)" metric. diff --git a/docs/enterprise/FAQ/monitoring-alarms/ted/db-connections.md b/docs/enterprise/FAQ/monitoring-alarms/ted/db-connections.md new file mode 100644 index 00000000..26d3351a --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/ted/db-connections.md @@ -0,0 +1,50 @@ +--- +title: "DB Connections" +template: Documentation +nav: + title: "Database Connections" + order: 40 +--- + +# Database Connections (Count) + +**AlarmName**: `__db_max_connections_alarm` (example: `turbot_newton_db_max_connections_alarm`) + +**Configuration**: The maximum concurrent connections allowed to a specific database(hive) and the threshold limit can +be configured in the "Database - Advanced - Parameters" section of TED. + +`MaxConnections`: Maximum number of concurrent connections. Defaults to 600. + +`MaxConnectionsAlarmThreshold`: Alarm threshold for maximum number of concurrent connections. Defaults to 500. + +**Condition**: DatabaseConnections >= 500 for 3 datapoints within 15 minutes + +**Details**: Connection counts should roughly correlate with the number of ECS Tasks and invoked Lambdas. + +**Healthy**: Connections should slowly churn over time as Lambdas and Guardrails ECS Tasks spin up and down. + +**Abnormal Spike**: An abrupt spike in connections may indicate a failure in the Tasks or Lambdas that caused lots of +reconnections. + +**Connections Flood**: Should the connections count continually increase over time, this may indicate stale connections +from processes that can't finish. + +## Troubleshooting + +If you see a sudden spike, please check if there were any recent changes to the Lambda Concurrency in the TE. Also look +for the TEF parameters WorkerLambdaMessageBatch and WorkerLambdaMaxDBConnections, these should be the same value and +most of the time it is 2. It is configured to 4 in rare occasions. For immediate fix, try reducing the lambda +concurrency as this does not require and downtime. + +To permanently make changes to increase the number of connections, please update the TED and increase the value for +MaxConnections to a desirable number along with the MaxConnectionsAlarmThreshold. This will reboot the database and you +do not want to miss the events when the instance is not available, hence it is highly recommended to stop the events +from flowing to the system and backed up in the queue during the database changes. + +### Need help? + +Please reach out to [Turbot Support](mailto:support@turbot.com) with the collected information. + +* A screenshot of the RDS instance's Configuration tab. +* A screenshot of the RDS instance's Monitoring tab showing the "DB Connections (Count)" metric. +* The configuration values of the parameters `MaxConnections` and `MaxConnectionsAlarmThreshold` for the database. diff --git a/docs/enterprise/FAQ/monitoring-alarms/ted/free-storage-space.md b/docs/enterprise/FAQ/monitoring-alarms/ted/free-storage-space.md new file mode 100644 index 00000000..d1e3625a --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/ted/free-storage-space.md @@ -0,0 +1,93 @@ +--- +title: "Free Storage Space" +template: Documentation +nav: + title: "Free Storage Space" + order: 50 +--- + +# Free Storage Space (MB) + +**AlarmName**: `{prefix}_{hive}_free_storage_alarm` (example: `turbot_einstein_free_storage_alarm`) + +**Configuration**: The DB allocated storage and the max allocated storage are configured in the "Database - Advanced - +Storage" section of the TED in Service Catalog. Once the storage is allocated, you can not reduce it. + +**AllocatedStorage**: The initial storage (in GB) that will be allocated to the database. To enable storage auto-scaling +specify Max Allocated Storage parameter higher than the Allocated Storage. AWS will automatically resize the allocated +storage up to the Max Allocated Storage capacity. + +**MaxAllocatedStorage**: To enable storage autoscaling, specify the maximum DB Storage limit to which the instance can +be auto-scaled, this should be greater than the Allocated Storage size but less than 65536 (GB). Leave the value to +default 0, to disable storage autoscaling. Note that storage autoscaling is supported only for General Purpose SSD or +Provisioned IOPS SSD storage type. + +**Condition**: FreeStorageSpace <= 100000 for 3 datapoints within 15 minutes + +**Healthy**: There is sufficient storage headroom for future growth. + +**Low Space**: Low free space may cause errors in Guardrails. Zero free space may lead to data loss and missed events. + +## Troubleshooting + +### What is the usual storage growth? + +You should see a gradual increase in the storage(in GB) utilization over the months. In other words, you should notice a +gradual decrease in the Free Storage Space. You may also observe a small drop and raise in the free storage at regular +intervals. This is due to recreation of the indexes as part of the maintenance cleanup job. + +### What does the maintenance cleanup job do? + +The Maintenance Cleanup job re-creates the indexes (based on bloat factor) and when the indexes are re-created, it +shrinks the indexes and thus prevents the database from unbounded growth. The cleanup job logs can be found in the +maintenance log group. Example: `CloudWatch > Log groups > /turbot/5_39_6/maintenance > All events`. The drop and +reclaim size may vary from one environment to another. If you have multiple TE versions running simultaneously, check +the maintenance logs of the latest TE version. If you find any errors in the maintenance logs, please report to [Turbot +Support](mailto:help@turbot.com) with the TE version and the log files. + +### What is the recommended setting? + +Storage type of `gp3` with storage autoscaling and adequate free storage space is recommended. Please consider the below +points as well. + +Storage once allocated can not be reduced, so make sure the max allocated storage is neither too high nor too low. Turn +on the storage autoscaling with a considerable max limit. + +The TED parameter `AllocatedStorage` is the allocated storage and `MaxAllocatedStorage` is the maximum allocation it can +autoscale to. If the parameter `MaxAllocatedStorage` is not set, then the autoscaling is turned off. + +If the Autoscaling is turned on, the Storage autoscaling can happen based on the following criteria. The additional +storage is in increments of whichever of the following is greater: + +* 5 GiB +* 10 percent of currently allocated storage +* Storage growth prediction for 7 hours based on the FreeStorageSpace metrics change in the past hour. For more + information on metrics, see Monitoring with Amazon CloudWatch. + +If storage autoscaling happens, the Service Catalog, CloudFormation stack and the actual RDS resource will go out of +sync. Make sure to update the Service Catalog with the new storage allocation value to sync the resource with the stack. +If the disk size in in Service Catalog is less than RDS, Cloudformation will error out in an attempt to decrease the +disk size. + +### Can I increase the storage without using Autoscaling? + +To increase the storage on demand, update the parameter `AllocatedStorage` in TED to a new desired value. + +### Things to Note before making changes to Storage/IOPS? + +When the storage or IOPS of an instance is changed, the RDS instance goes to "storage-optimization" state for about 6 +hours or until the optimization is done. The database is operational at this point but any changes you make to the +database will error out "InvalidDBInstanceState" until the DB comes back to "available" state. Hence, make the Storage +related changes at the end if you have any other TED changes to make. + +When the database is down for storage increase, you do not want to miss the events, hence it is highly recommended to +stop the events from flowing to the system and backed up in the queue during the database changes. Event flow can be +halted by disabling the triggers of the worker lambdas. Halting event processing will cause a backlog in the Events +queue but this will come down after restoring worker lambda concurrency. + +### Need help? + +Please reach out to [Turbot Support](mailto:support@turbot.com) with the collected information. + +* A screenshot of the RDS instance's Configuration tab. +* A screenshot of the RDS instance's Monitoring tab showing the "Free Storage Space (MB)" metric. diff --git a/docs/enterprise/FAQ/monitoring-alarms/ted/freeable-memory.md b/docs/enterprise/FAQ/monitoring-alarms/ted/freeable-memory.md new file mode 100644 index 00000000..ce42f6f0 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/ted/freeable-memory.md @@ -0,0 +1,49 @@ +--- +title: "Freeable Memory" +template: Documentation +nav: + title: "Freeable Memory" + order: 60 +--- + +# Freeable Memory (MB) + +**AlarmName**: `__primary_freeable_memory_alarm` ( +example: `turbot_einstein_primary_freeable_memory_alarm`) + +**Configuration**: You can change the CPU and memory available to a DB instance by changing its +DB [instance class](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.DBInstanceClass.html). The DB +Instance class is configured in the "Database - Configuration" section of TED. + +`InstanceClass`: Instance Type for DB. Defaults to db.t3.small but almost all production installations have a basic +graviton instance. + +**Condition**: FreeableMemory <= 1024 for 1 datapoints within 15 minutes + +**Healthy**: Available memory is in a consistent range with plenty of extra space to absorb spikes Sawtooth patterns are +also common. + +**Memory Starved**: When a DB instance has consistently low memory available, there can be significant performance +penalties as the DB uses swap disk space. + +## Troubleshooting + +To increase the DB memory allocation, please increase the database to a higher instance type through the TED parameter +Instance Type for DB. + +If there is enough memory available with low CPU utilization but the workspace is still performing slow, try increasing +the shared_buffer from default 25% to 40%. In order to do so, update the TED parameter "Shared Buffers" +from `{DBInstanceClassMemory/32768}` to `{DBInstanceClassMemory/20480}`. Flip the TE "Parameter Deployment Trigger" +switch from Blue <-> Green once the TED changes are done. PostgreSQL relies heavily on the operating system for its +caching (double buffering). As a result, allocating more than 40% of RAM to shared_buffers is unlikely to perform better +than a smaller value. + +Increasing the shared_buffer to 40% on an installation where there are multiple large workspaces running on a same +database, might not help. This may require to split the workspace to its own database. + +### Need help? + +Please reach out to [Turbot Support](mailto:support@turbot.com) with the collected information. + +* A screenshot of the RDS instance's Configuration tab. +* A screenshot of the RDS instance's Monitoring tab showing the "Freeable Memory (MB)" metric. diff --git a/docs/enterprise/FAQ/monitoring-alarms/ted/index.md b/docs/enterprise/FAQ/monitoring-alarms/ted/index.md new file mode 100644 index 00000000..12589063 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/ted/index.md @@ -0,0 +1,20 @@ +--- +title: "TED" +template: Documentation +nav: + title: "TED" + order: 20 +--- + +# Monitoring and Alarms - TED + +The alarms related to TED are forwarded to the SNS Topic `{prefix}_{hive}_alarms` (example: `turbot_einstein_alarms`). +If you have multiple hives, you need to subscribe to each hive's SNS Topic. + +Below are the list of supported alarms for the RDS Database. + +* [CPU Utilization](ted/cpu-utilization) +* [DB Connections](ted/db-connections) +* [Free Storage Space](ted/free-storage-space) +* [Freeable Memory](ted/freeable-memory) +* [Queue Depth](ted/queue-depth) diff --git a/docs/enterprise/FAQ/monitoring-alarms/ted/queue-depth.md b/docs/enterprise/FAQ/monitoring-alarms/ted/queue-depth.md new file mode 100644 index 00000000..d42477b3 --- /dev/null +++ b/docs/enterprise/FAQ/monitoring-alarms/ted/queue-depth.md @@ -0,0 +1,50 @@ +--- +title: "Queue Depth" +template: Documentation +nav: + title: "Queue Depth" + order: 70 +--- + +# Queue Depth (Count) + +**AlarmName**: `__primary_disk_queue_depth_alarm` ( +example: `turbot_einstein_primary_disk_queue_depth_alarm`) + +**Configuration**: The number of I/O requests in the queue waiting to be serviced. These are I/O requests that have been +submitted by the application but have not been sent to the device because the device is busy servicing other I/O +requests. Time spent waiting in the queue is a component of latency and service time (not available as a metric). This +metric is reported as the average queue depth for a given time interval. Amazon RDS reports queue depth in 1-minute +intervals. Typical values for queue depth range from zero to several hundred. A higher queue-depth indicates a slower +storage performance. If you are seeing higher values of queue depth, you should review your storage and IOPS +configurations. + +**Condition**: DiskQueueDepth > 50 for 1 datapoints within 45 minutes + +**Healthy**: There is fewer number of I/O requests waiting in the queue before they can reach the disk. + +## Troubleshooting + +If the Queue depth is high and stays high, that mean insufficient IOPS to process the requests. If you are not +already using GP3 storage type which gives 12000 IOPS for storage allocation greater than 399GB, you should move to GP3 +immediately. + +If you are on GP3 or allocated 12000 IOPS already, and you still see the Queue Depth greater than 50 then check for trends in the IOPS requests. + +* Is the Queue Depth high all day or is it only during a specific hour? Like a daily job or automation that runs or + spins up lot of resources in no time and Guardrails is trying to keep up with it? + Is it a one time activity that you can co-relate to the changes made in the workspace, like an account import, or a + policy setting changed/added at top level in the hierarchy. +* If you observe that this is a one time activity then, give the system few minutes to settle down and let the retry + logic take care of the rest. If this has a pattern then see what is the automation trying to do and work with Turbot + Support to figure out how it can be optimized. If this is something that is happening all day, then navigate to + Performance Insights of the database and capture the Top SQL and share the complete query with Turbot Support to + troubleshoot further. + +### Need help? + +Please reach out to [Turbot Support](mailto:support@turbot.com) with the collected information. + +* A screenshot of the RDS instance's Configuration tab. +* A screenshot of the RDS instance's Monitoring tab showing the "Write IOPS (Count/Second)", "Read IOPS ( + Count/Second)", "Total IOPS (Count/Second)" and "Queue Depth (Count)" metrics. diff --git a/docs/enterprise/FAQ/pause-events/disable-trigger.png b/docs/enterprise/FAQ/pause-events/disable-trigger.png new file mode 100644 index 0000000000000000000000000000000000000000..4295df46f058bd08b1f50fadeda8dd8b999ec6eb GIT binary patch literal 255104 zcmeEthhI}m(=Z@KnhilgK?DrF_YMjoy|+*WDWMCYcThnQ2WQX(oMEG#Ti`ByR;SXg-Xv9R#H 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require a large number of configuration settings to determine +their desired behavior. In Turbot Guardrails, [Policies](concepts/policies) are used to +manage these settings. + +In this exercise, you will create policy settings to manage S3 Bucket tags using +the Turbot Guardrails Console UI. + +By the end of this lab, you will be able to create and view policy settings and +values in the Turbot Guardrails Console. + +## Prerequisites + +- [Install the aws, aws-iam, aws-kms and aws-s3 mods](mods/install). + +- You must have at least one S3 bucket that has been discovered in your + workspace. It is recommended that you create a test bucket for this lab. + +## View a Policy Value + +1. In the Turbot Guardrails Console, navigate to the test bucket that you created in the + [prerequisite step](set-policy#prerequisites). Our test bucket name is + _turbot-bucket-version_, which we can search for at the main Turbot Guardrails screen. + Click on the bucket once it is found. + ![](/images/docs/guardrails/search-bucket-step1.png) + ![](/images/docs/guardrails/search-bucket-step2.png) + ![](/images/docs/guardrails/search-bucket-step3.png) + +2. Click the **Policies** tab. It shows both + [Policy Settings](concepts/policies/values-settings#policy-settings) and + [Policy Values](concepts/policies/values-settings#policy-values). + ![](/images/docs/guardrails/settings-values.png) + +3. From the list of Policy Values for this bucket, click on the **Template + (Bucket > Tags > Template)** item to bring up the policy value. + ![](/images/docs/guardrails/default-policy-value.png) + +The Policy Value page shows the [Policy Hierarchy](concepts/policies/hierarchy) +on the left, and the current value in the box. + +In the example above you can see that the policy value is `[]` (in other words, +a blank array), and that this value comes from the default. + +## Create a new Policy Setting + +1. In the VALUE box, click the **CREATE SETTING** link to bring up the **Create + Policy Setting** page. +2. Note that the **Policy Type** field has already been set to + `AWS > S3 > Bucket > Tags > Template` and the **Resource** is set to your + bucket. +3. In the **Setting** field, enter some tags and values: + +```yaml +Department: "Sales" +Company: "Vandelay Industries" +Cost Center: "314159" +``` + +![](/images/docs/guardrails/tags-template.png) 4. Click **Create** to create the +setting. Note that the Policy setting is updated to show that the new setting on +the bucket is now the active setting, and the value is updated with the value +for the setting. To see the updated value, go to **Values** tab and click on the +policy value record displayed. ![](/images/docs/guardrails/values-record.png) +![](/images/docs/guardrails/values-detail.png) + +## Browse the Hierarchy + +You can create or edit policy values anywhere at or above the resource in the +policy hierarchy. In the previous example, we created a setting on the bucket, +thus it applies only to that bucket. You could instead create a policy setting +on a folder, account, or region that would apply to ALL the buckets in that +folder, account, or region. + +1. By default, items in the hierarchy that do not affect the value are hidden. + ![](/images/docs/guardrails/policy-hierarchy.png) +2. Note that you can _View_ and _Edit_ or create a _Setting_ anywhere above the + bucket in the hierarchy. + +## Set Precedence, note and expiration + +By default, the policy setting page will create an unannotated, non-expiring, +required setting. You can change these options when creating or editing a policy +setting. + +1. Click **EDIT** in the policy setting that you created earlier. +2. Add a note in the **Notes** field +3. Add expiration to `24 hours` to make this policy setting expire. + ![](/images/docs/guardrails/policy-note-expiration.png) +4. Click **Update** +5. Note that the policy setting now shows the expiration and annotation. + ![](/images/docs/guardrails/detail-note-expire.png) + +## Create a Policy Setting to Enforce Tags + +The `AWS > S3 > Bucket > Tags > Template` that you set previously defines the +set of tags that should exist, but to enforce tagging, you must also set the +`AWS > S3 > Bucket > Tags` policy. + +1. From the **Policies** tab, click the **New Policy Setting** button marked in + green. +2. Search and select `AWS > S3 > Bucket > Tags` as **Policy Type**. +3. If you were already filtered on your test bucket, it will be automatically + selected as the **Resource**. If not, select it. You may search by name, or + **Browse** for it. +4. In the **Setting** field, select `Enforce: Set Tags` + ![](/images/docs/guardrails/enforce-tag.png) +5. Click **Create**. A new policy setting will be created. Within a few seconds, + the **Tags** control will run and set the tags from your tags template to + your S3 bucket. + +## Further Reading + +- [Policy Concepts](concepts/policies) +- [Policy Hierarchy](concepts/policies/hierarchy) +- [Managing Policies](guides/managing-policies) +- [7-Minute Labs: Calculated Policies](7-minute-labs/calc-policy) diff --git a/docs/7-minute-labs/set-policy/policy-hierarchy.png b/docs/7-minute-labs/set-policy/policy-hierarchy.png new file mode 100644 index 0000000000000000000000000000000000000000..bc7e8a139bf21bf99220ed460fe2789aed1990a5 GIT binary patch literal 162422 zcmcG$WmKKLwl++G0>!1cdnuHK%fj6X6iRVlXmMY7ad&rjcXxMpcX#)XXCK-7jQ4xb ze*V0S{J2+=nPko+b0pWiLck9hF(i0AcnAmxBnfe0c?bwt2M7o#7C4yqoP4T$MF@xw zF2+JaKO}^NNPbvb7#N%CLqL3q0BLJ~m7x35ucM=_-9JK018?mh@9!Thuie(wKGNPr z(yiS?k{YkBzK(;s-t`B=rKz_aE)#I%IV^eg>^PNMDk{>%^H2GH==!uHeqJsT#ZkL~n_|qf-)4-X- zz{Q`@6P1XKhiDCpI>Z2GsAu@X5YLRmpv<(-#1WgV82#rna1UDnOF!2z`U?l75ZkW~ 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