In Phase 2 of the App Mod journey, the customer would like to enhance their modernized application to include new requirements to tracking visitors activity and introduce API management to secure and manage their APIs.
Click to read more about the story behind this lab
In Phase 1:
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The application is modernized into microservices and runs on OpenShift and inherits all its benefits.
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Adoption of GitOps practices decreases Lead Time for Change, Mean Time to Recover and Change Failure Rate while increasing Deployment Frequency
Fast forward 6 months!
Taking advantage of this new momentum, the business comes up with new requirements for the e-commerce retail application. In Phase 2, the customer would like to enhance their modernized application to include new requirements and features.
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Track how visitors engage with their website, derive intelligence out of user activity stream
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Process and analyze this user activity stream to showcase Featured Products based on products with the most customer interest leading a more personalised experience.
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Introduce a multi-channel approach to build a mobile app as a new channel of access - mobile development is most likely to be outsourced
There are however a number of challenges with the new requirements:
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Adding new channels remains difficult, with a high risk of tight coupling to the existing services, which would slow down development productivity and time to market.
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The existing services need to be managed and secured to allow access for external partners and development teams. Governance remains a challenge.
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Adoption of new technologies such as event streaming requires time and new skills, which are not readily available inside the company.
In order to cope with these challenges, the development team decides for a new approach.
Adoption of Apache Kafka as a streaming platform to ingest and process user activity event streams.
API First approach: API contract is formalized in a OpenAPI spec document before dev commences. API design phase is done collaboratively with all stakeholders. The first version of the OpenAPI spec document is pushed and managed in a service registry, which acts a the system of truth. Mocks are created for the API.
Parallel Development streams with API first approach enables parallel development streams. - UI development teams and other API consumers start their development against the mocked - Backend development teams can implement the APIs using modern cloud-native frameworks and test the implementation against the OpenAPI spec to ensure that the implementation does not break the contract.
Manage and Secure the APIs Use an API management platform to expose the APIs in a secure and managed manner for access by the mobile app and other 3rd party applications.
Managed cloud services preferred for easy and rapid adoption of new middleware components like the API Management platform and Apache Kafka. This allows the teams to focus on the business requirements, without the need to invest in skills and infrastructure to deploy and maintain these components.
The primary goal of the workshop is to guide the user through
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Adding Event Streaming capabilities to an application to allow tracking user activity
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Adding API management capabilities to an application to manage and secure the APIs for access by external teams
To learn how to demonstrate the API first approach and enabling parallel development, refer to Solution Pattern: Enhancing Applications with Application Services
In this step you provision a Streams for Apache Kafka instance which will be used for the activity tracking events.
The instructions use the Red Hat Hybrid Cloud Console at console.redhat.com. Instructions for the rhoas CLI can be found in the appendix.
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Navigate to console.redhat.com and log in with your Red Hat account credentials.
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On the console.redhat.com landing page, select Application and Data Services from the menu on the left.
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On the Application Services landing page, select Streams for Apache Kafka → Kafka Instances.
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On the Kafka Instances overview page, click the Create Kafka instance button. Enter
globexas the name of the instance and select the relevant Cloud region for your Kafka instance and click Create instance. This starts the provisioning process for your Kafka instance.NoteThis will create a evaluation Kafka instance, which will remain available for 48 hrs. The Kafka instance comes with some limitations, which are listed in the Create instance window. The eval Kafka instance consists of a single broker, while production Kafka brokers have a minimum of 3 brokers.
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The new Kafka instance is listed in the instances table. After a couple of minutes, your instance should be marked as ready.
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When the instance Status is Ready, you can start using the Kafka instance. You can use the options icon (three vertical dots) to view, connect to, or delete the instance as needed.
Normally, when using Streams for Apache Kafka, the next steps would be to create a service account and set up the Access Control List for that service account. However, when using Service Binding to connect applications to the Kafka instance, a service account is created as part of the binding. Once the service account is created, you will need to setup the required permissions for that service account. An alternative is to set up wildcard permissions (valid for all service accounts), but this is generally considered less secure.
Register for a RHOAM sandbox by clicking on the red button in the Developer Sandbox use case activities page
You will be asked to confirm the registration through an email sent to your inbox. Once you launch the sandbox, follow these steps to setup a RHOAM sandbox tenant:
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From the Projects dropdown on the top of the page, set the project namespace as <username>-dev from the projects that have been already created for you.
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Click on Search from the left navigation
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Click on Resources to search for
APIManagementTenantand select it.
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Select Create APIManagementTenant button
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You will be taken to the YAML configuration of this resource. Click the Create button at the bottom of the YAML displayed.
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You will be taken to the Details page of this resource. Click on the YAML tab to view the changes to the YAML configuration.
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Watch for changes to the YAML of the APIManagementTenant resource, and wait for the status to be displayed at the bottom of the YAML to become
status.provisioningStatus: 3scale account ready
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The API Management Tenant account is now provisioned and is ready for use. This may take a couple of minutes.
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To access OpenShift API Management, navigate to the Launcher pane on the right side, select
API Management
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Choose to Authenticate through <> Red Hat Single Sign-On, and login using the identity provider that applies to you, e.g DevSandbox.
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You will be able to view the Dashboard
This completes the environment prerequistes setup. In the next section, you will use these Cloud Services to enhance your applications.
To support the business requirement of capturing and processing user activity on the Globex Coolstuff application, two new services have been developed:
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Activity Tracking service: This service exposes a REST endpoint. User activities on the Coolstuff website (such as opening a product page, liking a product etc..) generates an activity payload which is sent to the Activity tracking REST endpoint. The service transforms this payload into a Kafka message which is sent to a topic on the Kafka broker.
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Recommendation Engine: This service consumes and processes the events produced by the Activity Tracking service. The service uses the Kafka Streams library to continuously determine the top featured products (the products which generate the most activities). The service also exposes a REST endpoint to expose the list of featured products.
Both services are developed using Quarkus and the Quarkus extensions for reactive messaging and Kafka Streams. The development of the services is outside the scope of this workshop, but you are encouraged to examine the source code of the applications on GitHub: Activity Tracking Service and Recommendation Engine
In this part of the workshop you will connect the Activity Tracking and Recommendation Engine applications to the OpenShift Streams for Apache Kafka instance using Service Binding.
The setup and the configuration of the Streams for Apache Kafka instance as well as the service binding can also be done using the Red Hat OpenShift Application Services (rhoas) CLI. Instructions for completing the workshop using the rhoas CLI can be found in the appendix at the end of the instructions.
Click to learn more about Service Binding
Service Binding allows you to communicate connection details and secrets to an application to allow it to bind to a service. In this context, a service can be anything: a Kafka instance, a NoSQL database, etc. By using Service Binding, we no longer need to configure connection details (host, port), authentication mechanisms (SASL, OAuth) and credentials (username/password, client id/client secret) in an application. Instead, Service Binding injects these variables into your application container (as files or environment variables) for your application to consume. The Quarkus Kubernetes Service Binding extension enables Quarkus applications to automatically pickup these variables, injected as files, from the container’s filesystem, removing the need to specify any configuration settings in the application resources (e.g configuration files) themselves.
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In a browser window, navigate to the console of the lab OpenShift cluster. Open the Developer perspective in the globex-userXX namespace.
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In the Developer perspective, open the Topology view. Expect to see something like this (rearrange the topology as you see fit):
The deployed topology consists of:
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globex-ui: The Globex Coolstuff web application (Node.js/Angular). -
catalog-app: The Globex Coolstuff catalog service, consisting of the catalog database and the Spring Boot catalog microservice. -
inventory-app: The Globex Coolstuff inventory service, consisting of the inventory database and the Quarkus inventory microservice. -
activity-tracking: The Activity Tracking service. Notice that the deployment of the service is scaled to zero. The service will be scaled up once the connection to the Kafka broker is set up. -
recommendation-engine: The Recommendation Engine service. Notice that the deployment of the service is scaled to zero. The service will be scaled up once the connection to the Kafka broker is set up. -
activity-tracking-simulator: A Quarkus service that simulates user activity events and sends them to the Activity Tracking service.
-
-
Find the route to the Globex UI application and open the URL in your browser. Expect to see the home page of the Globex Coolstuff web application:
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Click on Cool Stuff Store in the top menu to see a paginated list of products:
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The Featured pane on the home page is empty at the moment. Also the product list page has an empty bar above the product list. These elements will be populated once the recommendation engine is up and running.
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In the Kafka Instances page of the web console, click the name of the Kafka instance (
globex) that you want to add a topic to. -
Select the Topics tab, click Create topic, and follow the guided steps to define the topic details. Click Next to complete each step and click Finish to complete the setup.
-
Topic name: Enter
globex.tracking. -
Partitions: Keep the default value at
1. -
Message retention: Keep default values. [ Retention time:
A weekand Retention Size:Unlimited. ] -
Replicas: Keep default values
NoteThe Activity Tracking service, which has been already deployed for you, sends activity events to this topic named
globex.tracking. Additional topics are required by the recommendation engine, but these topics are created dynamically when the application starts up.Click to learn more about these parameters
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Partitions are distinct lists of messages within a topic and enable parts of a topic to be distributed over multiple brokers in the cluster. A topic can contain one or more partitions, enabling producer and consumer loads to be scaled.
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Message retention time is the amount of time that messages are retained in a topic before they are deleted or compacted, depending on the cleanup policy. Retention size is the maximum total size of all log segments in a partition before they are deleted or compacted. For this workshop you can keep the default values.
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Replicas are copies of partitions in a topic. Partition replicas are distributed over multiple brokers in the cluster to ensure topic availability if a broker fails. When a follower replica is in sync with a partition leader, the follower replica can become the new partition leader if needed. ***For this release of Streams for Apache Kafka, the replicas are preconfigured. As the eval Kafka instance consists of only one broker, the number of partition replicas for the topic is set to
1, as well as the minimum number of follower replicas that must be in sync with a partition leader. For a production Kafka broker on Streams for Apache Kafka these values will be3and2respectively.
-
-
-
After you complete the topic setup, the new Kafka topic is listed in the topics table. You can now start producing and consuming messages to and from this topic using services that you connect to this instance.
Binding applications to services using Service Binding requires the Service Binding operator to be installed on the OpenShift cluster. To bind more specifically to a OpenShift Streams for Apache Kafka instance, the Red Hat OpenShift Application Services (RHOAS) operator is required. Both operators have been installed on your OpenShift cluster.
In this part of the workshop you connect your OpenShift instance to the Streams for Kafka instance you created previously. This can be done from the Developer perspective on the OpenShift console, or using the rhoas CLI. Instructions for the CLI can be found in the appendix.
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In a browser window, navigate to the console of your OpenShift cluster. Open the Developer perspective in the globex namespace.
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In the Developer perspective, navigate to the +Add view. Locate the Developer Catalog card with the Managed Services entry
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Click the Managed Services link. This opens the Managed Services page, which has a card for Red Hat OpenShift Application Services.
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In order to discover the managed services you are entitled to, you need to unlock the functionality with a token obtained from console.redhat.com. Please make sure you are logged in with the RHN ID you had used to create the Kafka instance
Open a new browser tab and navigate to console.redhat.com/openshift/token. Click on Load token in the Connect with offline token box. Copy the generated API token. -
Go back to the browser tab with the OpenShift console, and click the Red Hat OpenShift Application Services card. Paste the API token value in the API Token field. Click Connect.
This may take a minute or so. You are redirected back to the Managed Services page, which shows now a card for Red Hat OpenShift Streams for Apache Kafka.
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Click the Red Hat OpenShift Streams for Apache Kafka card, and click Connect. This opens a page which shows the Kafka instances that you can connect to. Select the entry
globexand click Next
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You are redirected to the Topology View of the Developer perspective, which shows now an entry for the managed Kafka instance.
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The entry is backed by a
KafkaConnectioncustom resource created by the OpenShift Application Services operator. To see the details of the KafkaConnection resource, click on the resource in the Topology view, and in the Details window, select Edit KafkaConnection to see the YAML structure of the custom resource.
Notice that the YAML structure contains the bootstrap URL to the Kafka broker, as well as a reference to a secret containing the data of a service account, namedrh-cloud-services-service-account.
As part of connecting to the managed Kafka instance, a service account is created. This is the service account that will be used by the Activity Tracking and Recommendation Engine services to actually connect to the managed Kafka instance. To make this work, the service account needs permissions, in particular the service account needs to be able to consume from topics, produce to topics and create new topics.
Setting permissions in the Access Control List of a Streams for Apache Kafka can be done in the console.redhat.com console, or using the rhoas CLI. Instructions for the CLI can be found in the appendix.
-
Navigate to the Application and Data Services page of the console.redhat.com console.
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On the Service Accounts page, check that a service account was created by the OpenShift Application Services operator. Look for a service account with a name like
rhoas-operator-xxx. -
Navigate to the Streams for Apache Kafka → Kafka instances page and open the page for your Kafka instance.
-
Click the Access tab to view the current ACL for this instance.
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Click Manage access, use the Account drop-down menu to select the service account that was created by the OpenShift Application Services operator, and click Next.
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Under Assign Permissions, use the drop-down menus to set the permissions shown in the following table for this service account.
Select the Consume from a topic and Produce to a topic from the Task-based permission possibilities. Set the topic and consumer group names toisand*.
Click Save.
The ACL list for the service account should look like:
You can now bind the Activity Tracking Service and Recommendation Engine to the OpenShift Streams for Apache instance. Through Service Binding the connection details are injected into the application pods. Service Binding to a managed Kafka instance can be done on the Topology view of OpenShift console, or through the rhoas CLI. The instructions for the rhoas CLI can be found in the appendix.
-
Navigate to the Topology view of the OpenShift console in the globex namespace.
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Hover over the activity-tracking deployment, and grab the arrow that appears. Drag the arrow to the KafkaConnection icon. When reaching the KafkaConnection icon, a text box
Create Service Bindingappears. Release the arrow. Click Create in the Create Service Binding pop-up window. The Activity Tracking deployment and the KafkaConnection icon are now connected with a solid black arrow.
-
Click on the activity-tracking deployment to open the details window, and click on the deployment name to open the full details of the Deployment. Notice that the service binding occurs by injecting a secret into the pod:
-
Scale the activity-tracking deployment to 1 replica.
-
Check the logs of the activity-tracking pod, and notice that the pod successfully connects to the Kafka broker instance.
exec java -Dquarkus.http.host=0.0.0.0 -Djava.util.logging.manager=org.jboss.logmanager.LogManager -XX:+ExitOnOutOfMemoryError -cp . -jar /deployments/quarkus-run.jar __ ____ __ _____ ___ __ ____ ______ --/ __ \/ / / / _ | / _ \/ //_/ / / / __/ -/ /_/ / /_/ / __ |/ , _/ ,< / /_/ /\ \ --\___\_\____/_/ |_/_/|_/_/|_|\____/___/ 2022-05-23 15:26:40,829 INFO [org.apa.kaf.com.sec.aut.AbstractLogin] (main) Successfully logged in. 2022-05-23 15:26:41,061 INFO [io.sma.rea.mes.kafka] (main) SRMSG18258: Kafka producer kafka-producer-tracking-event, connected to Kafka brokers 'globex-ca-m-q-mtp---qgalcrg.bf2.kafka.rhcloud.com:443', is configured to write records to 'globex.tracking' 2022-05-23 15:26:41,363 INFO [io.quarkus] (main) activity-tracking-service 1.0.0-SNAPSHOT on JVM (powered by Quarkus 2.7.4.Final) started in 2.427s. Listening on: http://0.0.0.0:8080 2022-05-23 15:26:41,364 INFO [io.quarkus] (main) Profile prod activated. 2022-05-23 15:26:41,364 INFO [io.quarkus] (main) Installed features: [cdi, kafka-client, resteasy-reactive, smallrye-context-propagation, smallrye-health, smallrye-reactive-messaging, smallrye-reactive-messaging-kafka, vertx]
-
Repeat the same procedure for the recommendation-engine deployment. Once the service binding created, scale the deployment to 1 pod.
-
Once the recommendation-engine is up and running, check in the console.redhat.com console that a number of new topics have been created:
Those are the topics created by the Kafka Streams topology in the Recommendation Engine to calculate the top featured products based on activity events.
Now that the Activity Tracking and Recommendation Engine apps are up and running, we can test the generation of activity events and the calculation of the top featured products.
The deployment topology for the workshop includes an activity simulator service which will generate a number of activity events randomly distributed over a list of products. These activity events are sent to the Activity Tracking service and transformed into Kafka messages in the globex.tracking topic. These messages are consumed by the Recommendation Engine app to calculate the top featured products.
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In the OpenShift console, locate the route for the activity-tracking-simulator deployment.
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Open a browser tab pointing to the application, and navigate to the
q/swagger-uipath in the browser (e.g.https://<url>.opentlc.com>/q/swagger-ui). This opens a Swagger UI page which allows you to use the REST API of the application. The REST application has only one operation,POST /simulate.
-
Generate a number activities. Set
countto any value between 100 and 1000. -
OpenShift Streams for Apache Kafka has a message viewer functionality that allows you to inspect the contents of messages in a topic.
Navigate to console.redhat.com, select your Kafka instance and in the instance window select the Topics tab. Click on theglobex.trackingtopic, and select the messages tab. Notice the activity event messages, with a JSON payload:
-
The featured product list calculated by the Recommendation Engine is produced to the
globex.recommendation-product-score-aggregated-changelogtopic. The list is recalculated roughly every 10 seconds as long as activity events are produced. Every calculation produces a message to the changelog topic. The last message in the topic represents the latest top featured list.
-
In a browser window, navigate to the home page of the Globex Coolstuff web application. Notice that the home page now shows a list of featured products.
Also, the product page now shows a banner with the featured products.
Congratulations! You reached the end of this part of the workshop, in which you added event streaming capabilities to the Globex Coolstuff application, using the OpenShift Streams for Apache Kafka managed cloud service, and Service Binding to connect your apps to the Kafka instance.
In this part of the workshop you will use the RHOAM sandbox environment that you have already setup in the prerequisites section to manage and secure the pre-deployed Catalog service.
A product is a customer-facing API that packages one or more backends. You will create an API Product manually with the following instructions
-
In a browser window navigate to the Red Hat OpenShift API Management console.
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In the Dashboard, under the APIs section, click Create Product in the Products card.
-
Provide the following details:
-
Name:
globex-product-catalog -
System name:
globex-product -
Description:
Optional field containing more details about the product.
-
-
Click Create Product.
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A Product
globex-product-catalogis created and you are taken to the Product Overview page
-
In the Dashboard, . Under the APIs section, click Create Backend in the Backends card
-
Provide the following details and Click Create Backend
-
Name:
globex-catalog. -
System name:
globex-catalog. -
Description:
Optional field containing more details about the backend. -
Private endpoint: Base URL of the Product Catalog API.
NoteInstructions on how to access the Private Endpoint of the Product Catalog API:
-
Access the Developer Perspective Topology of the OpenShift environment where the Globex application has been deployed
-
Click on the catalog-service icon and you will see the deployment details popup on the right hand side
-
Copy the Location as present at the bottom of this under Routes. This would look something like this
https://catalog-globex-userXX.apps.cluster-pppk8.pppk8.sandbox45.opentlc.com:443
-
-
-
Navigate to the Product
globex-product-catalogoverview page, and navigate to Integration > Backend -
Click on Add Backend, choose
globex-catalogfrom the dropdown, and click on Add to Product button
-
Go to the Dashboard
-
Under the API section, click on
globex-product-catalogunder the Product -
In Applications > Application Plans menu on the left hand side, click on Create Application Plan
-
Provide the following details:
-
Name:
globex-app-plan -
System name:
globex-app-plan
-
-
Click Create Application Plan.
An application is always associated with an application plan. Applications are stored within developer accounts.
-
Navigate to Audience > Accounts > Listing.
-
Click Create to create a new Developer account.
-
Provide the following details:
-
Username:
globex-dev -
Email: enter an email address
-
Password: enter a password
-
Organization/Group Name:
Globex
-
-
Click Create
-
Go to the Application tab of this account through the navigation on the top of the page.
-
Click Create Application.
-
You will view the New Application page
-
Choose the following details:
-
Product:
globex-product-catalog -
Application plan:
globex-app-plan -
Name:
globex-application -
Description: a suitable description
-
-
Click Create Application.
-
You can see your new application in Dashboard > Audience > Accounts > Applications > Listing
-
Navigate to the Product > globex-product-catalog > Integration > Configuration
-
Under APIcast Configuration, click Promote to Staging APIcast to promote the new APIcast configuration to staging,
-
To test requests to your API product, copy the command provided in Example curl for testing and access it from a browser.
-
Include the path
services/productsin the URL so that it looks something like thishttps://globex-product-jaya-devnation2-apicast-staging.apps.rhoam-ds-prod.xe9u.p1.openshiftapps.com/services/products?user_key=282d71626bc661abdd2ce204d1fc2285 -
After you run the command, you should get a JSON response containing results from the Catalog API.
-
In real life, the mobile app would be using the staging and production API endpoints securely to access the APIs.
-
Click on the Analytics > Traffic link on the left hand side. You will see the
Hitsdetails
-
This chart shows a summary of traffic statistics for the application.
-
➡️ 8. Summary
If you prefer to use the rhoas CLI to provision and configure the OpenShift Streams for Apache Kafka instance, and to bind your applications to the Kafka instance using Service Binding, you can follow the following instructions:
-
Install the
rhoasCLI-
Obtain the latest release of the
rhoasCLI archive for your operating system from the Red Hat OpenShift Application Services CLI releases page on GitHub. -
Install the package (or extract the archive), and add the
rhoasexecutable to your path. -
Check the version of the CLI
$ rhoas version
rhoas version 0.42.2
-
-
Login into Red Hat Application Services
$ rhoas login
This initiates a browser based login. Log in using your Red Hat Account credentials.
-
Provision an evaluation Kafka instance:
-
Provision the instance:
$ rhoas kafka create --name globex --region us-east-1
{ "cloud_provider": "aws", "created_at": "2022-05-23T17:20:03.700415552Z", "href": "/api/kafkas_mgmt/v1/kafkas/ca5s4gjtq6jlcbnumh5g", "id": "ca5s4gjtq6jlcbnumh5g", "instance_type": "developer", "kafka_storage_size": "10Gi", "kind": "Kafka", "multi_az": false, "name": "globex", "owner": "rh-bu-cloudservices-tmm", "reauthentication_enabled": true, "region": "us-east-1", "status": "accepted", "updated_at": "2022-05-23T17:20:03.700415552Z" } -
To check the status of the kafka instance:
$ rhoas status
Service Context Name: default Context File Location: /home/bernard/.config/rhoas/contexts.json Kafka ----------------------------------------------------------------------------- ID: ca5s4gjtq6jlcbnumh5g Name: globex Status: ready Bootstrap URL: globex-ca-s-gjtq-jlcbnumh-g.bf2.kafka.rhcloud.com:443
-
-
Create a Kafka topic:
-
Create the topic:
$ rhoas kafka topic create --name globex.tracking --partitions 1
-
Verify the topics:
$ rhoas kafka topic list
NAME PARTITIONS RETENTION TIME (MS) RETENTION SIZE (BYTES) ----------------- ------------ --------------------- ------------------------ globex.tracking 1 604800000 -1 (Unlimited)
-
-
Connect Streams for Apache Kafka instance.
-
Before starting, make sure that you are connected to your OpenShift cluster using the
ocCLI. -
To connect your Kafka instance to your project, execute the following command in the terminal:
$ rhoas cluster connect -n globex
-
You are asked to select the type of service you want to connect. Select kafka and press
enter.? Select type of service [Use arrows to move, type to filter] > kafka service-registry -
The CLI will prints the Connection Details and asks you to confirm. Type
yand pressenterto continue.? Select type of service kafka This command will link your cluster with Cloud Services by creating custom resources and secrets. In case of problems please execute "rhoas cluster status" to check if your cluster is properly configured Connection Details: Service Type: kafka Service Name: globex Kubernetes Namespace: globex Service Account Secret: rh-cloud-services-service-account ? Do you want to continue? (y/N) -
You will be asked to provide a token, which can be retrieved from console.redhat.com/openshift/token. Navigate to this URL, copy the token to your clipboard, and copy it into your terminal. Press
enterto continue.You should see output similar to this:
✔️ Token Secret "rh-cloud-services-accesstoken" created successfully ✔️ Service Account Secret "rh-cloud-services-service-account" created successfully Client ID: srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d Make a copy of the client ID to store in a safe place. Credentials won't appear again after closing the terminal. You will need to assign permissions to service account in order to use it. You need to separately grant service account access to Kafka by issuing following command $ rhoas kafka acl grant-access --producer --consumer --service-account srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d --topic all --group all ✔️ kafka resource "globex" has been created Waiting for status from kafka resource. Created kafka can be already injected to your application. To bind you need to have Service Binding Operator installed: https://github.com/redhat-developer/service-binding-operator You can bind kafka to your application by executing "rhoas cluster bind" or directly in the OpenShift Console topology view. ✔️ Connection to service successful.NoteThe same command can also be run in a non-interactive way:
$ rhoas cluster connect -n globex --service-type kafka --service-name globex --token eyJhbGciOiJ...GDC-cTHCwgmxT-nzM -y
-
To verify that the connection has been successfully created, execute the following oc command:
$ oc get KafkaConnection -n globex
This should return a KafkaConnection with the name of your Kafka instance.
NAME AGE globex 3m42s
-
-
Assign permissions to the service account created by the OpenShift Application Services operator:
$ rhoas kafka acl grant-access --producer --consumer --service-account srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d --topic all --group all -y
The following ACL rules will be created: PRINCIPAL (7) PERMISSION OPERATION DESCRIPTION ------------------------------------------------ ------------ ----------- ------------------------- srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d allow describe topic is "*" srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d allow read topic is "*" srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d allow read group is "*" srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d allow write topic is "*" srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d allow create topic is "*" srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d allow write transactional-id is "*" srvc-acct-553dd8d3-e461-411d-a76c-7769bbb5c45d allow describe transactional-id is "*" ✔️ ACLs successfully created in the Kafka instance "globex" -
Bind an application to a Streams for Apache Kafka instance.
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Execute the following command:
$ rhoas cluster bind -n globex -
You are asked to select the application you want to connect to. Select activity-tracking and press
enter. (When repeating for the second application, select recommendation-engine)Looking for Deployment resources. Use --deployment-config flag to look for deployment configs ? Please select application you want to connect with [Use arrows to move, type to filter] > activity-tracking activity-tracking-simulator catalog-database catalog-service globex-ui inventory-database inventory-service recommendation-engine -
You are asked to select the type of service you want to connect. Select kafka and press
enter.Looking for Deployment resources. Use --deployment-config flag to look for deployment configs ? Please select application you want to connect with activity-tracking ? Select type of service [Use arrows to move, type to filter] > kafka service-registry -
The CLI asks you to confirm. Type
yand pressenterto continue.Looking for Deployment resources. Use --deployment-config flag to look for deployment configs ? Please select application you want to connect with activity-tracking ? Select type of service kafka Binding "globex" with "activity-tracking" app ? Do you want to continue? (y/N)The CLI produces the following output:
Using ServiceBinding Operator to perform binding ✔️ Binding globex with activity-tracking app succeededNoteThe command can also be run in a non-interactive way:
$ rhoas cluster bind -n globex --app-name activity-tracking --service-type kafka --service-name globex -y $ rhoas cluster bind -n globex --app-name recommendation-engine --service-type kafka --service-name globex -y
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➡️ 8. Summary