Continuous Integration and Pipelines

In this lab you will learn about pipelines and how to configure a pipeline in OpenShift so that it will take care of the application lifecycle.

A continuous delivery (CD) pipeline is an automated expression of your process for getting software from version control right through to your users and customers. Every change to your software (committed in source control) goes through a complex process on its way to being released. This process involves building the software in a reliable and repeatable manner, as well as progressing the built software (called a "build") through multiple stages of testing and deployment.

OpenShift Pipelines is a cloud-native, continuous integration and delivery (CI/CD) solution for building pipelines using Tekton. Tekton is a flexible, Kubernetes-native, open-source CI/CD framework that enables automating deployments across multiple platforms (Kubernetes, serverless, VMs, etc) by abstracting away the underlying details.

Install OpenShift Pipelines from OperatorHub

Those using the Developer Sandbox will already have the Pipelines Operator installed, feel free to skip this section.

OpenShift provides a marketplace of installable software packaged as Kubernetes Operator called OperatorHub . You can add Kubernetes-native CI/CD to your cluster installing OpenShift Pipelines directly from OperatorHub embedded marketplace inside OpenShift.

From the left-side menu under Administrator perspective, go to Operators→ OperatorHub. In the search box, search for pipelines, then click to Red Hat OpenShift Pipelines:

From the description view, click Install to review all installation settings.

Ensure Update Channel is set to stable , and click Install to start installing the Operator.

After few seconds, the installation should be completed with success and you can verify it looking at Status column, check if the status is Succeeded.

Understanding Tekton

Tekton defines a number of Kubernetes custom resources as building blocks in order to standardize pipeline concepts and provide a terminology that is consistent across CI/CD solutions.

The custom resources needed to define a pipeline are listed below:

Task: a reusable, loosely coupled number of steps that perform a specific task (e.g. building a container image)
Pipeline: the definition of the pipeline and the Tasks that it should perform
TaskRun: the execution and result of running an instance of task
PipelineRun: the execution and result of running an instance of pipeline, which includes a number of TaskRuns

In short, in order to create a pipeline, one does the following:

Create custom or install existing reusable Tasks
Create a Pipeline and PipelineResources to define your application’s delivery pipeline
Create a PersistentVolumeClaim to provide the volume/filesystem for pipeline execution or provide a VolumeClaimTemplate which creates a PersistentVolumeClaim
Create a PipelineRun to instantiate and invoke the pipeline

For further details on pipeline concepts, refer to the Tekton documentation that provides an excellent guide for understanding various parameters and attributes available for defining pipelines.

As pipelines provide the ability to promote applications between different stages of the delivery cycle, Tekton, which is our Continuous Integration server that will execute our pipelines, will be deployed on a project with a Continuous Integration role. Pipelines executed in this project will have permissions to interact with all the projects modeling the different stages of our delivery cycle.

A Pipeline is a user-defined model of a CD pipeline. A Pipeline’s code defines your entire build process, which typically includes stages for building an application, testing it and then delivering it.

A Task and a ClusterTask contain some step to be executed. ClusterTasks are available to all user within a cluster where OpenShift Pipelines has been installed, while Tasks can be custom.

You can explore all available ClusterTasks in the cluster either from the Web Console than from CLI:

oc get clustertasks

Create Your Pipeline

Ensure you installed OpenShift Pipelines Operator before proceeding.

Let’s now create a Tekton pipeline for Nationalparks backend. In the Developer Perspective, click Pipelines in the left navigation, then click Create.

Here we can view the interactive Pipeline builder. We can add tasks to the pipeline by clicking on the Add task button. We can also add parameters to the pipeline by clicking on the created tasks. To save time here, we’ll use the YAML view to create the pipeline.

Now, depending on which language you are using, you’ll need to create the appropriate pipeline:

Java
.NET
Javascript
Python

Here, we can copy this Tekton Pipeline in the YAML text area. This pipeline will clone the source code from GitHub, build and test the application, build a container image and deploy it on OpenShift.

apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: nationalparks-pipeline
spec:
  params:
    - default: nationalparks
      name: APP_NAME
      type: string
    - default: 'https://github.com/openshift-roadshow/nationalparks.git'
      description: The application git repository url
      name: APP_GIT_URL
      type: string
    - default: master
      description: The application git repository revision
      name: APP_GIT_REVISION
      type: string
  tasks:
    - name: git-clone
      params:
        - name: url
          value: $(params.APP_GIT_URL)
        - name: revision
          value: $(params.APP_GIT_REVISION)
        - name: submodules
          value: 'true'
        - name: depth
          value: '1'
        - name: sslVerify
          value: 'true'
        - name: deleteExisting
          value: 'true'
        - name: verbose
          value: 'true'
      taskRef:
        kind: ClusterTask
        name: git-clone
      workspaces:
        - name: output
          workspace: app-source
    - name: build-and-test
      params:
        - name: MAVEN_IMAGE
          value: maven:3.8.3-openjdk-11
        - name: GOALS
          value:
            - package
        - name: PROXY_PROTOCOL
          value: http
      runAfter:
        - git-clone
      taskRef:
        kind: ClusterTask
        name: maven
      workspaces:
        - name: source
          workspace: app-source
        - name: maven-settings
          workspace: maven-settings
    - name: build-image
      params:
        - name: IMAGE
          value: image-registry.openshift-image-registry.svc:5000/$(context.pipelineRun.namespace)/$(params.APP_NAME):latest
        - name: BUILDER_IMAGE
          value: registry.redhat.io/rhel8/buildah:latest
        - name: STORAGE_DRIVER
          value: vfs
        - name: DOCKERFILE
          value: ./Dockerfile
        - name: CONTEXT
          value: .
        - name: TLSVERIFY
          value: 'true'
        - name: FORMAT
          value: oci
      runAfter:
        - build-and-test
      taskRef:
        kind: ClusterTask
        name: buildah
      workspaces:
        - name: source
          workspace: app-source
    - name: redeploy
      params:
        - name: SCRIPT
          value: oc rollout restart deployment/$(params.APP_NAME)
      runAfter:
        - build-image
      taskRef:
        kind: ClusterTask
        name: openshift-client
  workspaces:
    - name: app-source
    - name: maven-settings

Now, let’s head back to the Pipeline builder view to see it visually.

This pipeline has 4 Tasks defined:

git clone: this is a ClusterTask that will clone our source repository for nationalparks and store it to a Workspace app-source which will use the PVC created for it app-source-workspace
build-and-test: will build and test our Java application using maven ClusterTask
build-image: this is a buildah ClusterTask that will build an image using a binary file as input in OpenShift, in our case a JAR artifact generated in the previous task
redeploy: it will use an openshift-client ClusterTask to deploy the created image on OpenShift using the Deployment named nationalparks we created in the previous lab

The Pipeline is parametric, with default values already preconfigured.

It is using two Workspaces:

app-source: linked to a PersistentVolumeClaim app-source-pvc previously created. This will be used to store the artifact to be used in different Task
maven-settings: an EmptyDir volume for the maven cache, this can be extended also with a PVC to make subsequent Maven builds faster

Here, we can copy this Tekton Pipeline in the YAML text area. This pipeline will clone the source code from GitHub, build and test the application, build a container image and deploy it on OpenShift.

apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: nationalparks-pipeline
spec:
  params:
    - default: nationalparks
      name: APP_NAME
      type: string
    - default: 'https://github.com/openshift-roadshow/nationalparks-dotnet.git'
      description: The application git repository url
      name: GIT_REPO
      type: string
    - default: master
      name: GIT_REVISION
      type: string
    - default: 'image-registry.openshift-image-registry.svc:5000/$(context.pipelineRun.namespace)/$(params.APP_NAME):latest'
      name: IMAGE_NAME
      type: string
    - default: .
      name: PATH_CONTEXT
      type: string
    - default: '1'
      name: MINOR_VERSION
      type: string
  resources: []
  workspaces:
    - name: workspace
  tasks:
    - name: fetch-repository
      params:
        - name: url
          value: $(params.GIT_REPO)
        - name: revision
          value: $(params.GIT_REVISION)
        - name: subdirectory
          value: ''
        - name: deleteExisting
          value: 'true'
      taskRef:
        kind: ClusterTask
        name: git-clone
      workspaces:
        - name: output
          workspace: workspace
    - name: deploy
      params:
        - name: SCRIPT
          value: kubectl $@
        - name: ARGS
          value:
            - rollout
            - status
            - deploy/$(params.APP_NAME)
      runAfter:
        - s2i-dotnet
      taskRef:
        kind: ClusterTask
        name: openshift-client
    - name: s2i-dotnet
      runAfter:
        - fetch-repository
      taskRef:
        kind: ClusterTask
        name: s2i-dotnet
      params:
        - name: BUILDER_IMAGE
          value: registry.redhat.io/rhel8/buildah
        - name: VERSION
          value: latest
        - name: PATH_CONTEXT
          value: .
        - name: TLSVERIFY
          value: 'true'
        - name: IMAGE
          value: >-
            image-registry.openshift-image-registry.svc:5000/$(context.pipelineRun.namespace)/$(params.APP_NAME):latest
        - name: SKIP_PUSH
          value: 'false'
        - name: ENV_VARS
          value: []
      workspaces:
        - name: source
          workspace: workspace

Now, let’s head back to the Pipeline builder view to see it visually.

This pipeline has 3 Tasks defined:

fetch-repository: this is a ClusterTask that will clone our source repository for nationalparks and store it to a Workspace app-source which will use the PVC created for it app-source-workspace
build: will build and test our .NET Core C# application, generate and push a container image automatically with compiled binaries inside OpenShift Container Registry
deploy: will deploy the created image on OpenShift using the Deployment named nationalparks we created in the previous lab

The Pipeline is parametric, with default values already preconfigured.

It is using one Workspace:

app-source: this need to be linked to a PersistentVolumeClaim since will be used to store the code and the compiled binary to be used in different Tasks

Here, we can copy this Tekton Pipeline in the YAML text area. This pipeline will clone the source code from GitHub, build and test the application, build a container image and deploy it on OpenShift.

apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: nationalparks-pipeline
spec:
  params:
    - default: nationalparks
      name: APP_NAME
      type: string
    - default: 'https://github.com/openshift-roadshow/nationalparks-js.git'
      description: The application git repository url
      name: GIT_REPO
      type: string
    - default: master
      name: GIT_REVISION
      type: string
    - default: 'image-registry.openshift-image-registry.svc:5000/$(context.pipelineRun.namespace)/$(params.APP_NAME):latest'
      name: IMAGE_NAME
      type: string
    - default: .
      name: PATH_CONTEXT
      type: string
    - default: '1'
      name: MINOR_VERSION
      type: string
  tasks:
    - name: fetch-repository
      params:
        - name: url
          value: $(params.GIT_REPO)
        - name: revision
          value: $(params.GIT_REVISION)
        - name: subdirectory
          value: ''
        - name: deleteExisting
          value: 'true'
      taskRef:
        kind: ClusterTask
        name: git-clone
      workspaces:
        - name: output
          workspace: workspace
    - name: build
      params:
        - name: IMAGE
          value: $(params.IMAGE_NAME)
        - name: TLSVERIFY
          value: 'false'
        - name: PATH_CONTEXT
          value: $(params.PATH_CONTEXT)
        - name: MINOR_VERSION
          value: $(params.MINOR_VERSION)
      runAfter:
        - fetch-repository
      taskRef:
        kind: ClusterTask
        name: s2i-nodejs
      workspaces:
        - name: source
          workspace: workspace
    - name: deploy
      params:
        - name: SCRIPT
          value: kubectl $@
        - name: ARGS
          value:
            - rollout
            - status
            - deploy/$(params.APP_NAME)
      runAfter:
        - build
      taskRef:
        kind: ClusterTask
        name: openshift-client
  workspaces:
    - name: workspace

Now, let’s head back to the Pipeline builder view to see it visually.

This pipeline has 4 Tasks defined:

fetch-repository: this is a ClusterTask that will clone our source repository for nationalparks and store it to a Workspace app-source which will use the PVC created for it app-source-workspace
build: will build and test our NodeJS application, generate and push a container image automatically with compiled binaries inside OpenShift Container Registry
deploy: will deploy the created image on OpenShift using the Deployment named nationalparks we created in the previous lab

The Pipeline is parametric, with default values already preconfigured.

It is using one Workspace:

app-source: this need to be linked to a PersistentVolumeClaim since will be used to store the code and the compiled binary to be used in different Tasks

Here, we can copy this Tekton Pipeline in the YAML text area. This pipeline will clone the source code from GitHub, build and test the application, build a container image and deploy it on OpenShift.

apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: nationalparks-pipeline
spec:
  params:
    - default: nationalparks
      name: APP_NAME
      type: string
    - default: 'https://github.com/openshift-roadshow/nationalparks-py.git'
      description: The application git repository url
      name: GIT_REPO
      type: string
    - default: master
      name: GIT_REVISION
      type: string
    - default: 'image-registry.openshift-image-registry.svc:5000/$(context.pipelineRun.namespace)/$(params.APP_NAME):latest'
      name: IMAGE_NAME
      type: string
    - default: .
      name: PATH_CONTEXT
      type: string
    - default: '1'
      name: MINOR_VERSION
      type: string
  tasks:
    - name: fetch-repository
      params:
        - name: url
          value: $(params.GIT_REPO)
        - name: revision
          value: $(params.GIT_REVISION)
        - name: subdirectory
          value: ''
        - name: deleteExisting
          value: 'true'
      taskRef:
        kind: ClusterTask
        name: git-clone
      workspaces:
        - name: output
          workspace: workspace
    - name: build
      params:
        - name: IMAGE
          value: $(params.IMAGE_NAME)
        - name: TLSVERIFY
          value: 'false'
        - name: PATH_CONTEXT
          value: $(params.PATH_CONTEXT)
        - name: MINOR_VERSION
          value: $(params.MINOR_VERSION)
      runAfter:
        - fetch-repository
      taskRef:
        kind: ClusterTask
        name: s2i-python
      workspaces:
        - name: source
          workspace: workspace
    - name: deploy
      params:
        - name: SCRIPT
          value: kubectl $@
        - name: ARGS
          value:
            - rollout
            - status
            - deploy/$(params.APP_NAME)
      runAfter:
        - build
      taskRef:
        kind: ClusterTask
        name: openshift-client
  workspaces:
    - name: workspace

Now, let’s head back to the Pipeline builder view to see it visually.

This pipeline has 3 Tasks defined:

fetch-repository: this is a ClusterTask that will clone our source repository for nationalparks and store it to a Workspace app-source which will use the PVC created for it app-source-workspace
build: will build and test our Python application, generate and push a container image automatically with compiled binaries inside OpenShift Container Registry
deploy: it will deploy the created image on OpenShift using the Deployment named nationalparks we created in the previous lab

The Pipeline is parametric, with default values already preconfigured.

It is using one Workspace:

app-source: this need to be linked to a PersistentVolumeClaim since will be used to store the code and the compiled binary to be used in different Tasks

Finally, make sure to click the Create button to create the Pipeline.

Exercise: Add Storage for your Pipeline

OpenShift manages Storage with Persistent Volumes to be attached to Pods running our applications through Persistent Volume Claim requests, and it also provides the capability to manage it at ease from the Web Console. From the Administrator Perspective, go to Storage → Persistent Volume Claims.

Go to the top-right side and click Create Persistent Volume Claim button.

Inside Persistent Volume Claim name insert app-source-pvc.

In Size section, insert 1 as we are going to create 1 GiB Persistent Volume for our Pipeline, using RWO Single User access mode.

Leave all other default settings, and click Create.

The Storage Class is the type of storage available in the cluster.

Run the Pipeline

We can start now the Pipeline from the Web Console. Within the Developer Perspective go to left-side menu, click on Pipelines, then click on nationalparks-pipeline. From top-right Actions list, click on Start.

You will be prompted with parameters to add the Pipeline, showing default ones. Your appropriate values are already preconfigured depending on which language’s pipeline you chose. However, in Workspaces → select PersistentVolumeClaim from the list, and then select app-source-pvc. This is the share volume used by Pipeline Tasks in your Pipeline containing the source code and compiled artifacts. Click on Start to run your Pipeline.

You can follow the Pipeline execution at ease from Web Console. Open Developer Perspective and go to left-side menu, click on Pipeline, then click on nationalparks-pipeline. Switch to Pipeline Runs tab to watch all the steps in progress:

The click on the PipelineRun national-parks-deploy-run-:

Then click on the Task running to check logs:

Verify PipelineRun has been completed with success: