feat: open-source module

.github/workflows/ci.yaml

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+name: CI Pipeline
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - "main"
+    paths-ignore:
+      - ".github/**"
+      - "*.md"
+      - "docs/**"
+      - "!README.md"
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  CI:
+    env:
+      TF_VAR_credentials: ${{ secrets.GOOGLE_CREDENTIALS }}
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+
+      - uses: hashicorp/setup-terraform@v3
+        with:
+          terraform_version: "1.9.6"
+
+      - name: Check is doc is update to date
+        run: |
+          make doc
+          if ! git diff --exit-code; then
+              echo "Documentation not up to date. Please run \"make doc\" and commit changes!" >&2
+              exit 1
+          fi
+
+      - uses: terraform-linters/setup-tflint@v4
+        name: Setup TFLint
+
+      - name: Init TFLint
+        run: tflint --init
+        env:
+          # https://github.com/terraform-linters/tflint/blob/master/docs/user-guide/plugins.md#avoiding-rate-limiting
+          GITHUB_TOKEN: ${{ github.token }}
+
+      - run: terraform init
+
+      - run: make check

.github/workflows/pull-requests.yaml

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+name: Pull Request Pipeline
+
+on:
+  workflow_dispatch:
+  pull_request:
+    branches:
+      - "main"
+    paths-ignore:
+      - ".github/**"
+      - "*.md"
+      - "docs/**"
+      - "!README.md"
+
+jobs:
+  CI:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+
+      - uses: hashicorp/setup-terraform@v3
+        with:
+          terraform_version: "1.9.3"
+
+      - name: Check is doc is update to date
+        run: |
+          make doc
+          if ! git diff --exit-code; then
+              echo "Documentation not up to date. Please run \"make doc\" and commit changes!" >&2
+              exit 1
+          fi
+
+      - uses: terraform-linters/setup-tflint@v4
+        name: Setup TFLint
+
+      - name: Init TFLint
+        run: tflint --init
+        env:
+          # https://github.com/terraform-linters/tflint/blob/master/docs/user-guide/plugins.md#avoiding-rate-limiting
+          GITHUB_TOKEN: ${{ github.token }}
+
+      - run: terraform init
+
+      - run: make check-no-tests

.gitignore

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+**/.terraform/
+*.secrets.auto.tfvars
+secrets.auto.tfvars
+.idea/
+backend.tfvars
+.terraform.lock.hcl
+credentials.json

.terraform-docs.yml

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+formatter: "markdown" # this is required
+
+version: ""
+
+header-from: main.tf
+footer-from: ""
+
+recursive:
+  enabled: false
+  path: modules
+
+sections:
+  hide: []
+  show: []
+
+content: |-
+  # Nebuly Platform (GCP)
+
+  Terraform module for provisioning Nebuly Platform resources on GCP.
+
+  Available on [Terraform Registry](https://registry.terraform.io/modules/nebuly-ai/nebuly-platform/gcp/latest).
+
+  ## Prerequisites
+
+  ### Nebuly Credentials
+
+  Before using this Terraform module, ensure that you have your Nebuly credentials ready. 
+  These credentials are necessary to activate your installation and should be provided as input via the `nebuly_credentials` input.
+
+  ### Required GCP APIs
+
+  Before using this Terraform module, ensure that the following GCP APIs are enabled in your Google Cloud project:
+
+  - [sqladmin.googleapis.com](https://cloud.google.com/sql/docs/mysql/admin-api)
+  - [servicenetworking.googleapis.com](https://cloud.google.com/service-infrastructure/docs/service-networking/getting-started)
+  - [cloudresourcemanager.googleapis.com](https://cloud.google.com/resource-manager/reference/rest)
+  - [container.googleapis.com](https://cloud.google.com/kubernetes-engine/docs/reference/rest)
+  - [secretmanager.googleapis.com](https://cloud.google.com/secret-manager/docs/reference/rest)
+
+  You can enable the APIs using either the GCP Console or the gcloud CLI, as explained in the [GCP Documentation](https://cloud.google.com/endpoints/docs/openapi/enable-api#gcloud).
+
+  ### Required GCP Quotas
+
+  Ensure that your GCP project has the necessary quotas for the following resources over the regions you plan to deploy Nebuly:
+
+  - **Name**: GPUs (all regions) 
+    
+    **Min Value**: 2
+  - **Name**: NVIDIA L4 GPUs 
+    
+    **Min Value**: 1
+  - **Name**: NVIDIA T4 GPUs 
+    
+    **Min Value**: 1
+
+  For more information on how to check and increase quotas, refer to the [GCP Documentation](https://cloud.google.com/docs/quotas/view-manage).
+    
+
+  ## Quickstart
+
+  To get started with Nebuly installation on GCP, you can follow the steps below. 
+
+  These instructions will guide you through the installation using Nebuly's default standard configuration with the Nebuly Helm Chart.
+
+  For specific configurations or assistance, reach out to the Nebuly Slack channel or email [[email protected]](mailto:[email protected]).
+
+  ### 1. Terraform setup
+
+  Import Nebuly into your Terraform root module, provide the necessary variables, and apply the changes.
+
+  For configuration examples, you can refer to the [Examples](#examples). 
+
+  Once the Terraform changes are applied, proceed with the next steps to deploy Nebuly on the provisioned Google Kubernetes Engine (GKE) cluster.
+
+  ### 2. Connect to the GKE Cluster 
+
+  For connecting to the created GKE cluster, you can follow the steps below. For more information, 
+  refer to the [GKE Documentation](https://cloud.google.com/kubernetes-engine/docs/how-to/cluster-access-for-kubectl).
+
+  * Install the [GCloud CLI](https://cloud.google.com/sdk/docs/install-sdk).
+
+  * Install [kubectl](https://kubernetes.io/docs/reference/kubectl/):
+  ```shell
+  gcloud components install kubectl
+  ```
+
+  * Install the Install the gke-gcloud-auth-plugin:
+  ```shell
+  gcloud components install gke-gcloud-auth-plugin
+  ```
+
+  * Fetch the command for retrieving the credentials from the module outputs:
+
+  ```shell
+  terraform output gke_cluster_get_credentials
+  ```
+
+  * Run the command you got from the previous step
+
+  ### 3. Create image pull secret
+
+  The auto-generated Helm values use the name defined in the k8s_image_pull_secret_name input variable for the Image Pull Secret. If you prefer a custom name, update either the Terraform variable or your Helm values accordingly.
+  Create a Kubernetes [Image Pull Secret](https://kubernetes.io/docs/tasks/configure-pod-container/pull-image-private-registry/) for 
+  authenticating with your Docker registry and pulling the Nebuly Docker images.
+
+  ### 4. Bootstrap GKE cluster
+
+  Retrieve the auto-generated values from the Terraform outputs and save them to a file named `values-bootstrap.yaml`:
+
+  ```shell
+  terraform output helm_values_bootstrap
+  ```
+
+  Install the bootstrap Helm chart to set up all the dependencies required for installing the Nebuly Platform Helm chart on GKE.
+
+  Refer to the [chart documentation](https://github.com/nebuly-ai/helm-charts/tree/main/bootstrap-gcp) for all the configuration details.
+
+  ```shell
+  helm install oci://ghcr.io/nebuly-ai/helm-charts/bootstrap-gcp \
+    --namespace nebuly-bootstrap \
+    --generate-name \
+    --create-namespace \
+    -f values-bootstrap.yaml
+  ```
+
+
+  ### 5. Create Secret Provider Class
+  Create a Secret Provider Class to allow GKE to fetch credentials from the provisioned Key Vault.
+
+  * Get the Secret Provider Class YAML definition from the Terraform module outputs:
+    ```shell
+    terraform output secret_provider_class
+    ```
+
+  * Copy the output of the command into a file named secret-provider-class.yaml.
+
+  * Run the following commands to install Nebuly in the Kubernetes namespace nebuly:
+
+    ```shell
+    kubectl create ns nebuly
+    kubectl apply --server-side -f secret-provider-class.yaml
+    ```
+
+
+  ### 6. Install nebuly-platform chart
+
+  Retrieve the auto-generated values from the Terraform outputs and save them to a file named `values.yaml`:
+
+  ```shell
+  terraform output helm_values
+  ```
+
+  Install the Nebuly Platform Helm chart. 
+  Refer to the [chart documentation](https://github.com/nebuly-ai/helm-charts/tree/main/nebuly-platform) for detailed configuration options.
+
+  ```shell
+  helm install oci://ghcr.io/nebuly-ai/helm-charts/nebuly-platform \
+    --namespace nebuly \
+    -f values.yaml \
+    --timeout 16m \
+    <your-release-name> 
+  ```
+
+  > ℹ️  During the initial installation of the chart, all required Nebuly LLMs are uploaded to your model registry. 
+  > This process can take approximately 5 minutes. If the helm install command appears to be stuck, don't worry: it's simply waiting for the upload to finish.
+
+  ### 7. Access Nebuly
+
+  Retrieve the external Load Balancer IP address to access the Nebuly Platform:
+
+  ```shell
+  kubectl get svc -n nebuly-bootstrap -o jsonpath='{range .items[?(@.status.loadBalancer.ingress)]}{.status.loadBalancer.ingress[0].ip}{"\n"}{end}'
+  ```
+
+  You can then register a DNS A record pointing to the Load Balancer IP address to access Nebuly via the custom domain you provided 
+  in the input variable `platform_domain`.
+
+
+  ## Examples
+
+  You can find examples of code that uses this Terraform module in the [examples](./examples) directory.
+
+  {{ .Header }}
+
+
+  {{ .Providers }}
+
+
+  {{ .Outputs }}
+
+
+  {{ .Inputs }}
+
+  ## Resources
+
+  {{ range .Module.Resources }}
+  - {{ .GetMode }}.{{ .Spec }} ({{ .Position.Filename }}#{{ .Position.Line }})
+  {{- end }}
+
+output:
+  file: ""
+  mode: inject
+  template: |-
+    <!-- BEGIN_TF_DOCS -->
+    {{ .Content }}
+    <!-- END_TF_DOCS -->
+
+output-values:
+  enabled: false
+  from: ""
+
+sort:
+  enabled: true
+  by: name
+
+settings:
+  anchor: true
+  color: true
+  default: true
+  description: false
+  escape: true
+  hide-empty: false
+  html: true
+  indent: 2
+  lockfile: false
+  read-comments: true
+  required: true
+  sensitive: true
+  type: true