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OpenShift Pipelines Tutorial

Welcome to the OpenShift Pipelines tutorial!

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.

OpenShift Pipelines features:

  • Standard CI/CD pipeline definition based on Tekton
  • Build images with Kubernetes tools such as S2I, Buildah, Buildpacks, Kaniko, etc
  • Deploy applications to multiple platforms such as Kubernetes, serverless and VMs
  • Easy to extend and integrate with existing tools
  • Scale pipelines on-demand
  • Portable across any Kubernetes platform
  • Designed for microservices and decentralized teams
  • Integrated with the OpenShift Developer Console

This tutorial walks you through pipeline concepts and how to create and run a simple pipeline for building and deploying a containerized app on OpenShift, and in this tutorial, we will use Triggers to handle a real GitHub webhook request to kickoff a PipelineRun.

In this tutorial you will:

Prerequisites

You need an OpenShift 4 cluster in order to complete this tutorial. If you don't have an existing cluster, go to Openlabs and register free with IBM Cloud in order to get an OpenShift cluster up and running - select Lab6 to get access to Openshift console, and a command shell.

Lab 6: Bring Your Own Application

You will also use the Tekton CLI (tkn) through out this tutorial. The Openlabs environment command shell already has tkn installed. If you need Tekton elsewhere, download the Tekton CLI by following instructions available on the CLI GitHub repository.

To be able to trigger a pipeline build directly from an application change/commit, you will need a GitHub account, and clones of the sample application components vote-ui and vote-api

vote-app

Concepts

Tekton defines a number of Kubernetes custom resources (CRDs) as building blocks in order to standardize pipeline concepts and provide a terminology that is consistent across CI/CD solutions. These custom resources are an extension of the Kubernetes API that let users create and interact with these objects using kubectl and other Kubernetes tools.

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

Tekton Architecture

To create a pipeline:

  • 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
  • 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.

The Tekton API enables functionality to be separated from configuration (e.g. Pipelines vs PipelineRuns) such that steps can be reusable.

Triggers extends the Tekton architecture with the following CRDs:

  • TriggerTemplate - Templates resources to be created (e.g. Create PipelineResources and PipelineRun that uses them)
  • TriggerBinding - Validates events and extracts payload fields
  • EventListener - Connects TriggerBindings and TriggerTemplates into an addressable endpoint (the event sink). It uses the extracted event parameters from each TriggerBinding (and any supplied static parameters) to create the resources specified in the corresponding TriggerTemplate. It also optionally allows an external service to pre-process the event payload via the interceptor field.
  • ClusterTriggerBinding - A cluster-scoped TriggerBinding

Using tektoncd/triggers in conjunction with tektoncd/pipeline enables you to easily create full-fledged CI/CD systems where the execution is defined entirely through Kubernetes resources.

You can learn more about triggers by checking out the docs

In the following sections, you will go through each of the above steps to define and invoke a pipeline.

Install OpenShift Pipelines

OpenShift Pipelines is provided as an add-on on top of OpenShift that can be installed via an operator available in the OpenShift OperatorHub.

  • Follow these instructions in order to install OpenShift Pipelines on OpenShift via the OperatorHub.

OpenShift OperatorHub

$ oc get pipeline --all-namespaces

should produce output similar to:

NAMESPACE   NAME                         AGE
openshift   buildah                      105s
openshift   buildah-deployment           105s
openshift   buildah-deployment-pr        105s
openshift   buildah-knative              105s
openshift   buildah-knative-pr           105s
openshift   buildah-pr                   105s
openshift   s2i-dotnet-3                 106s
openshift   s2i-dotnet-3-deployment      106s
openshift   s2i-dotnet-3-deployment-pr   105s
openshift   s2i-dotnet-3-knative         106s
openshift   s2i-dotnet-3-knative-pr      105s
openshift   s2i-dotnet-3-pr              105s
openshift   s2i-go                       107s
...

Deploy Sample Application

Create a project for the sample voting application that you will be using in this tutorial:

$ oc new-project pipelines-tutorial

OpenShift Pipelines automatically adds and configures a ServiceAccount named pipeline that has sufficient permissions to build and push an image. This service account will be used later in the tutorial.

Run the following command to see the pipeline service account:

$ oc get serviceaccount pipeline

You will use the simple application during this tutorial, which has a frontend vote-ui and backend vote-api

Using your Github account, create clones of these repositories at github.com, to allow you to control the trigger-based build and deploy

You can also deploy the same applications by applying the artifacts available in k8s directory of the respective repo.

If you deploy the application directly, you should be able to see the deployment in the OpenShift Web Console by switching over to the Developer perspective of the OpenShift Web Console. Change from Administrator to Developer from the drop down as shown below:

Developer Perspective

Make sure you are on the pipelines-tutorial project by selecting it from the Project dropdown menu. Either search for pipelines-tutorial in the search bar or scroll down until you find pipelines-tutorial and click on the name of your project.

Projects

Install Tasks

Tasks consist of a number of steps that are executed sequentially. Tasks are executed/run by creating TaskRuns. A TaskRun will schedule a Pod. Each step is executed in a separate container within the same pod. They can also have inputs and outputs in order to interact with other tasks in the pipeline.

Here is an example of a Maven task for building a Maven-based Java application:

apiVersion: tekton.dev/v1beta1
kind: Task
metadata:
  name: maven-build
spec:
  workspaces:
   -name: filedrop
  steps:
  - name: build
    image: maven:3.6.0-jdk-8-slim
    command:
    - /usr/bin/mvn
    args:
    - install

When a task starts running, it starts a pod and runs each step sequentially in a separate container on the same pod. This task happens to have a single step, but tasks can have multiple steps, and, since they run within the same pod, they have access to the same volumes in order to cache files, access configmaps, secrets, etc. You can specify volume using workspace. It is recommended that Tasks uses at most one writeable Workspace. Workspace can be secret, pvc, config or emptyDir.

Note that only the requirement for a git repository is declared on the task and not a specific git repository to be used. That allows tasks to be reusable for multiple pipelines and purposes. You can find more examples of reusable tasks in the Tekton Catalog and OpenShift Catalog repositories.

Install the apply-manifests and update-deployment tasks from the repository using oc or kubectl, which you will need for creating a pipeline in the next section:

$ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/master/01_pipeline/01_apply_manifest_task.yaml
$ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/master/01_pipeline/02_update_deployment_task.yaml

You can take a look at the tasks you created using the Tekton CLI:

$ tkn task ls

resulting in output similar to:

NAME                AGE
apply-manifests     10 seconds ago
update-deployment   4 seconds ago

We will be using buildah clusterTasks, which gets installed along with the Pipeline Operator. The Operator installs a few ClusterTask which you can see.

$ tkn clustertasks ls

resulting in output similar to:

NAME                       DESCRIPTION   AGE
buildah                                  1 day ago
buildah-v0-14-3                          1 day ago
git-clone                                1 day ago
s2i-php                                  1 day ago
tkn                                      1 day ago

Create Pipeline

A pipeline defines a number of tasks that should be executed and how they interact with each other via their inputs and outputs.

In this tutorial, you will create a pipeline that takes the source code of the application from GitHub and then builds and deploys it on OpenShift.

Pipeline Diagram

Here is the YAML file that represents the above pipeline:

apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: build-and-deploy
spec:
  workspaces:
  - name: shared-workspace
  params:
  - name: deployment-name
    type: string
    description: name of the deployment to be patched
  - name: git-url
    type: string
    description: url of the git repo for the code of deployment
  - name: git-revision
    type: string
    description: revision to be used from repo of the code for deployment
    default: "master"
  - name: IMAGE
    type: string
    description: image to be build from the code
  tasks:
  - name: fetch-repository
    taskRef:
      name: git-clone
      kind: ClusterTask
    workspaces:
    - name: output
      workspace: shared-workspace
    params:
    - name: url
      value: $(params.git-url)
    - name: subdirectory
      value: ""
    - name: deleteExisting
      value: "true"
    - name: revision
      value: $(params.git-revision)
  - name: build-image
    taskRef:
      name: buildah
      kind: ClusterTask
    params:
    - name: TLSVERIFY
      value: "false"
    - name: IMAGE
      value: $(params.IMAGE)
    workspaces:
    - name: source
      workspace: shared-workspace
    runAfter:
    - fetch-repository
  - name: apply-manifests
    taskRef:
      name: apply-manifests
    workspaces:
    - name: source
      workspace: shared-workspace
    runAfter:
    - build-image
  - name: update-deployment
    taskRef:
      name: update-deployment
    workspaces:
    - name: source
      workspace: shared-workspace
    params:
    - name: deployment
      value: $(params.deployment-name)
    - name: IMAGE
      value: $(params.IMAGE)
    runAfter:
    - apply-manifests

Once you deploy the pipelines, you should be able to visualize pipeline flow in the OpenShift Web Console by switching over to the Developer perspective of the OpenShift Web Console. Select pipeline tab, select project as pipelines-tutorial and click on pipeline build-and-deploy

Pipeline-view

This pipeline helps you to build and deploy backend/frontend code, by configuring the appropriate resources to pipeline.

Pipeline Steps:

  1. Clones the source code of the application from a git repository by referring (git-url and git-revision param)
  2. Builds the container image of application using the buildah clustertask that uses Buildah to build the image
  3. The application image is pushed to an image registry by refering (image param)
  4. The new application image is deployed on OpenShift using the apply-manifests and update-deployment tasks.

You might have noticed that in the pipeline, there are no references to the specific git repository or the image registry it will be pushed to; that's because pipelines in Tekton are designed to be generic and re-usable across environments and stages through the application's lifecycle. Pipelines abstract away the specifics of the git source repository and image to be produced as PipelineResources or Params. When triggering a pipeline, you can provide different git repositories and image registries to be used during pipeline execution.

Be patient! You will do that in a little bit in the next section.

The execution order of task is determined by dependencies that are defined between the tasks via inputs and outputs as well as explicit orders that are defined via runAfter.

The workspaces field allow you to specify one or more volumes that each Task in the Pipeline requires during execution. You specify one or more Workspaces in the workspaces field.

Create the pipeline by running the following:

$ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/master/01_pipeline/04_pipeline.yaml

Alternatively, in the OpenShift Web Console, you can click on the + at the top right of the screen while you are in the pipelines-tutorial project:

OpenShift Console - Import Yaml

Upon creating the pipeline via the web console, you will be taken to a Pipeline Details page that gives an overview of the pipeline you created.

OpenShift Console - Pipeline Details

Check the list of pipelines you have created using the CLI:

$ tkn pipeline ls

resulting in output similar to:

NAME               AGE            LAST RUN   STARTED   DURATION   STATUS
build-and-deploy   1 minute ago   ---        ---       ---        ---

Trigger Pipeline

Now that the pipeline is created, you can trigger it to execute the tasks specified in the pipeline.

Note :-

If you are not into the pipelines-tutorial namespace, and using another namespace for the tutorial steps, please make sure you update the frontend and backend image resource to the correct url with your namespace name like so :

image-registry.openshift-image-registry.svc:5000/<namespace-name>/vote-api:latest

You need to create the PersistentVolumeClaim which can be used for Pipeline execution:

$ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/master/01_pipeline/03_persistent_volume_claim.yaml

A PipelineRun is how you can start a pipeline and tie it to the persistentVolumeClaim and params that should be used for this specific invocation.

Let's start a pipeline to build and deploy backend application using tkn; copy, edit and run the following command:

$ tkn pipeline start build-and-deploy \
    -w name=shared-workspace,claimName=source-pvc \
    -p deployment-name=vote-api \
    -p git-url=https://github.com/<!your-github-account!>/BSOK-vote-api.git \
    -p IMAGE=image-registry.openshift-image-registry.svc:5000/pipelines-tutorial/vote-api

resulting in output similar to:

Pipelinerun started: build-and-deploy-run-z2rz8

In order to track the pipelinerun progress run:
tkn pipelinerun logs build-and-deploy-run-z2rz8 -f -n pipelines-tutorial

Similarly, start a pipeline to build and deploy frontend application; again - copy, edit and run the following command:

$ tkn pipeline start build-and-deploy \
    -w name=shared-workspace,claimName=source-pvc \
    -p deployment-name=vote-ui \
    -p git-url=http://github.com/<!your-github-account!>/BSOK-vote-ui.git \
    -p IMAGE=image-registry.openshift-image-registry.svc:5000/pipelines-tutorial/vote-ui

resulting in output similar to:

Pipelinerun started: build-and-deploy-run-xy7rw

In order to track the pipelinerun progress run:
tkn pipelinerun logs build-and-deploy-run-xy7rw -f -n pipelines-tutorial

As soon as you start the build-and-deploy pipeline, a pipelinerun will be instantiated and pods will be created to execute the tasks that are defined in the pipeline.

$ tkn pipeline list

resulting in output similar to:

NAME               AGE             LAST RUN                     STARTED          DURATION   STATUS
build-and-deploy   6 minutes ago   build-and-deploy-run-xy7rw   36 seconds ago   ---        Running

Above we have started build-and-deploy pipeline, with relevant pipeline resources to deploy backend/frontend application using single pipeline

$ tkn pipelinerun ls

resulting in output similar to:

NAME                         STARTED         DURATION     STATUS
build-and-deploy-run-xy7rw   36 seconds ago   ---          Running
build-and-deploy-run-z2rz8   40 seconds ago   ---          Running

You can optionally check out the logs of the pipelinerun as it runs using the tkn pipeline logs command which interactively allows you to pick the pipelinerun of your interest and inspect the logs (note: allow this command to run until the pipeline completes, as terminating can disrupt the pipeline):

$ tkn pipeline logs -f

resulting in output similar to:

? Select pipelinerun:  [Use arrows to move, type to filter]
> build-and-deploy-run-xy7rw started 36 seconds ago
  build-and-deploy-run-z2rz8 started 40 seconds ago

After a few minutes, the pipeline should finish successfully.

$ tkn pipelinerun list

resulting in output similar to:

NAME                         STARTED      DURATION     STATUS
build-and-deploy-run-xy7rw   1 hour ago   2 minutes    Succeeded
build-and-deploy-run-z2rz8   1 hour ago   19 minutes   Succeeded

Looking back at the project, you should see that the images are successfully built and deployed.

Application Deployed

You can get the route of the application by executing the following command and access the application

$ oc get route vote-ui --template='http://{{.spec.host}}'

If you want to re-run the pipeline again, you can use the following short-hand command to rerun the last pipelinerun again that uses the same workspaces, params and service account used in the previous pipeline run:

$ tkn pipeline start build-and-deploy --last

Whenever there is any change to your repository we need to start pipeline explicity to see new changes to take effect

Triggers

Triggers, in conjunction with pipelines, enable us to hook our Pipelines to respond to external github events (push events, pull requests etc).

Prerequisites

NOTE: Running a cluster locally crc won't work, as you will need the Openshift webhook-url to be accessible to your github repositories.

Adding Triggers to our Application:

Now let’s add a TriggerTemplate, TriggerBinding, and an EventListener to our project.

Trigger Template

A TriggerTemplate is a resource which have parameters that can be substituted anywhere within the resources of template.

The definition of our TriggerTemplate is given in 03-triggers/02-template.yaml.

apiVersion: triggers.tekton.dev/v1alpha1
kind: TriggerTemplate
metadata:
  name: vote-app
spec:
  params:
  - name: git-repo-url
    description: The git repository url
  - name: git-revision
    description: The git revision
    default: master
  - name: git-repo-name
    description: The name of the deployment to be created / patched

  resourcetemplates:
  - apiVersion: tekton.dev/v1beta1
    kind: PipelineRun
    metadata:
      name: build-deploy-$(tt.params.git-repo-name)-$(uid)
    spec:
      serviceAccountName: pipeline
      pipelineRef:
        name: build-and-deploy
      params:
      - name: deployment-name
        value: $(tt.params.git-repo-name)
      - name: git-url
        value: $(tt.params.git-repo-url)
      - name: git-revision
        value: $(tt.params.git-revision)
      - name: IMAGE
        value: image-registry.openshift-image-registry.svc:5000/pipelines-tutorial/$(tt.params.git-repo-name)
      workspaces:
      - name: shared-workspace
        persistentvolumeclaim:
          claimName: source-pvc
  • Run following command to apply Triggertemplate.
$ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/master/03_triggers/02_template.yaml

Trigger Binding

TriggerBindings is a map enable you to capture fields from an event and store them as parameters, and replace them in triggerTemplate whenever an event occurs.

The definition of our TriggerBinding is given in 03-triggers/01_binding.yaml.

apiVersion: triggers.tekton.dev/v1alpha1
kind: TriggerBinding
metadata:
  name: vote-app
spec:
  params:
  - name: git-repo-url
    value: $(body.repository.url)
  - name: git-repo-name
    value: $(body.repository.name)
  - name: git-revision
    value: $(body.head_commit.id)

The exact paths (keys) of parameter we need can be found by examining the event payload (eg: GitHub events).

Run following command to apply Triggertemplate.

$ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/master/03_triggers/01_binding.yaml

Event Listener

This component sets up a Service and listens for events. It also connects a TriggerTemplate to a TriggerBinding, into an addressable endpoint (the event sink)

The definition for our EventListener can be found in 03-triggers/03_event_listener.yaml.

apiVersion: triggers.tekton.dev/v1alpha1
kind: EventListener
metadata:
  name: vote-app
spec:
  serviceAccountName: pipeline
  triggers:
  - bindings:
    - name: vote-app
    template:
      name: vote-app
  • Run following command to create Triggertemplate.
$ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/master/03_triggers/04_event_listener.yaml

Note: EventListener will setup a Service. We need to expose that Service as an OpenShift Route to make it publicly accessible.

  • Run below command to expose eventlistener service as a route
$ oc expose svc el-vote-app

Configuring GitHub WebHooks

Now we need to configure webhook-url on the cloned backend and frontend source code repositories with the Route we exposed previously.

  • Run below command to get webhook-url
$ echo "URL: $(oc  get route el-vote-app --template='http://{{.spec.host}}')"

resulting in output similar to:

URL: http://el-vote-app-pipelines-tutorial.dte-ocp44-new-bfay8r-915b3b336cabec458a7c7ec2aa7c625f-0000.us-east.containers.appdomain.cloud

Reminder:

Fork or clone the backend and frontend source code repositories so that you have sufficient privileges to configure GitHub webhooks.

Configure webhook manually

Open both your cloned/forkedGitHub repositories and perform the following steps:

  1. Go to Settings > Webhook
  2. click on Add Webhook
  3. Add the above URL to payload URL
  4. Select Content type as application/json
  5. Add secret eg: 1234567
  6. Click on Add Webhook

Add webhook

Now we should see a webhook configured on your forked source code repositories (on our GitHub Repo, go to Settings>Webhooks).

Webhook-final

Great!, We have configured webhooks

Trigger pipeline Run

When we perform any push event on the backend the following should happen.

  1. The configured webhook in vote-api GitHub repository should push the event payload to our route (exposed EventListener Service).

  2. The Event-Listener will pass the event to the TriggerBinding and TriggerTemplate pair.

  3. TriggerBinding will extract parameters needed for rendering the TriggerTemplate. Successful rendering of TriggerTemplate should create 2 PipelineResources (source-repo-vote-api and image-source-vote-api) and a PipelineRun (build-deploy-vote-api)

We can test this by pushing a commit to your cloned/forked vote-api repository from GitHub web ui or from terminal.

Let’s push an empty commit to vote-api repository.

$ git commit -m "empty-commit" --allow-empty && git push origin master

resulting in output similar to:

...
Writing objects: 100% (1/1), 190 bytes | 190.00 KiB/s, done.
Total 1 (delta 0), reused 0 (delta 0)
To github.com:<!your-github-account!>/vote-api.git
   72c14bb..97d3115  master -> master

Watch OpenShift WebConsole Developer perspective and a PipelineRun will be automatically created.

pipeline-run-api

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