Pipelines

OpenShift Container Platform 4.6

Configuring and using Pipelines in OpenShift Container Platform

Red Hat OpenShift Documentation Team

Abstract

This document provides instructions for configuring and using pipelines in OpenShift Container Platform.

Chapter 1. Understanding OpenShift Pipelines

Important

OpenShift Pipelines is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.

For more information about the support scope of Red Hat Technology Preview features, see https://access.redhat.com/support/offerings/techpreview/.

Red Hat OpenShift Pipelines is a cloud-native, continuous integration and continuous delivery (CI/CD) solution based on Kubernetes resources. It uses Tekton building blocks to automate deployments across multiple platforms by abstracting away the underlying implementation details. Tekton introduces a number of standard Custom Resource Definitions (CRDs) for defining CI/CD pipelines that are portable across Kubernetes distributions.

1.1. Key features

  • Red Hat OpenShift Pipelines is a serverless CI/CD system that runs Pipelines with all the required dependencies in isolated containers.
  • Red Hat OpenShift Pipelines are designed for decentralized teams that work on microservice-based architecture.
  • Red Hat OpenShift Pipelines use standard CI/CD pipeline definitions that are easy to extend and integrate with the existing Kubernetes tools, enabling you to scale on-demand.
  • You can use Red Hat OpenShift Pipelines to build images with Kubernetes tools such as Source-to-Image (S2I), Buildah, Buildpacks, and Kaniko that are portable across any Kubernetes platform.
  • You can use the OpenShift Container Platform Developer Console to create Tekton resources, view logs of Pipeline runs, and manage pipelines in your OpenShift Container Platform namespaces.

1.2. Red Hat OpenShift Pipelines concepts

Red Hat OpenShift Pipelines provide a set of standard Custom Resource Definitions (CRDs) that act as the building blocks from which you can assemble a CI/CD pipeline for your application.

Task
A Task is the smallest configurable unit in a Pipeline. It is essentially a function of inputs and outputs that form the Pipeline build. It can run individually or as a part of a Pipeline. A Pipeline includes one or more Tasks, where each Task consists of one or more Steps. Steps are a series of commands that are sequentially executed by the Task.
Pipeline
A Pipeline consists of a series of Tasks that are executed to construct complex workflows that automate the build, deployment, and delivery of applications. It is a collection of PipelineResources, parameters, and one or more Tasks. A Pipeline interacts with the outside world by using PipelineResources, which are added to Tasks as inputs and outputs.
PipelineRun
A PipelineRun is the running instance of a Pipeline. A PipelineRun initiates a Pipeline and manages the creation of a TaskRun for each Task being executed in the Pipeline.
TaskRun
A TaskRun is automatically created by a PipelineRun for each Task in a Pipeline. It is the result of running an instance of a Task in a Pipeline. It can also be manually created if a Task runs outside of a Pipeline.
Workspace
A Workspace is a storage volume that a Task requires at runtime to receive input or provide output. A Task or Pipeline declares the Workspace, and a TaskRun or PipelineRun provides the actual location of the storage volume, which mounts on the declared Workspace. This makes the Task flexible, reusable, and allows the Workspaces to be shared across multiple Tasks.
Trigger
A Trigger captures an external event, such as a Git pull request and processes the event payload to extract key pieces of information. This extracted information is then mapped to a set of predefined parameters, which trigger a series of tasks that may involve creation and deployment of Kubernetes resources. You can use Triggers along with Pipelines to create full-fledged CI/CD systems where the execution is defined entirely through Kubernetes resources.
Condition
A Condition refers to a validation or check, which is executed before a Task is run in your Pipeline. Conditions are like if statements which perform logical tests, with a return value of True or False. A Task is executed if all Conditions return True, but if any of the Conditions fail, the Task and all subsequent Tasks are skipped. You can use Conditions in your Pipeline to create complex workflows covering multiple scenarios.

1.3. Detailed OpenShift Pipeline Concepts

This guide provides a detailed view of the various Pipeline concepts.

1.3.1. Tasks

Tasks are the building blocks of a Pipeline and consist of sequentially executed Steps. Tasks are reusable and can be used in multiple Pipelines.

Steps are a series of commands that achieve a specific goal, such as building an image. Every Task runs as a pod and each Step runs in its own container within the same pod. Because Steps run within the same pod, they have access to the same volumes for caching files, ConfigMaps, and Secrets.

The following example shows the apply-manifests Task.

apiVersion: tekton.dev/v1beta1 1
kind: Task 2
metadata:
  name: apply-manifests 3
spec: 4
  params:
  - default: k8s
    description: The directory in source that contains yaml manifests
    name: manifest_dir
    type: string
  steps:
  - args:
    - |-
      echo Applying manifests in $(inputs.params.manifest_dir) directory
      oc apply -f $(inputs.params.manifest_dir)
      echo -----------------------------------
    command:
    - /bin/bash
    - -c
    image: quay.io/openshift/origin-cli:latest
    name: apply
    workingDir: /workspace/source
  workspaces:
  - name: source
1
Task API version v1beta1.
2
Specifies the type of Kubernetes object. In this example, Task.
3
Unique name of this Task.
4
Lists the parameters and Steps in the Task and the workspace used by the Task.

This Task starts the pod and runs a container inside that pod using the maven:3.6.0-jdk-8-slim image to run the specified commands. It receives an input directory called workspace-git that contains the source code of the application.

The Task only declares the placeholder for the Git repository, it does not specify which Git repository to use. This allows Tasks to be reusable for multiple Pipelines and purposes.

1.3.2. TaskRun

A TaskRun instantiates a Task for execution with specific inputs, outputs, and execution parameters on a cluster. It can be invoked on its own or as part of a PipelineRun.

A Task consists of one or more Steps that execute container images, and each container image performs a specific piece of build work. A TaskRun executes the Steps in a Task in the specified order, until all Steps execute successfully or a failure occurs.

The following example shows a TaskRun that runs the apply-manifests Task with the relevant input parameters:

apiVersion: tekton.dev/v1beta1 1
kind: TaskRun 2
metadata:
  name: apply-manifests-taskrun 3
spec: 4
  serviceAccountName: pipeline
  taskRef: 5
    kind: Task
    name: apply-manifests
  workspaces: 6
  - name: source
    persistentVolumeClaim:
      claimName: source-pvc
1
TaskRun API version v1beta1.
2
Specifies the type of Kubernetes object. In this example, TaskRun.
3
Unique name to identify this TaskRun.
4
Definition of the TaskRun. For this TaskRun, the Task and the required workspace are specified.
5
Name of the Task reference used for this TaskRun. This TaskRun executes the apply-manifests Task.
6
Workspace used by the TaskRun.

1.3.3. Pipelines

A Pipeline is a collection of Task resources arranged in a specific order of execution. You can define a CI/CD workflow for your application using pipelines containing one or more tasks.

A Pipeline resource definition consists of a number of fields or attributes, which together enable the pipeline to accomplish a specific goal. Each Pipeline resource definition must contain at least one Task resource, which ingests specific inputs and produces specific outputs. The pipeline definition can also optionally include Conditions, Workspaces, Parameters, or Resources depending on the application requirements.

The following example shows the build-and-deploy pipeline, which builds an application image from a Git repository using the buildah ClusterTask resource:

apiVersion: tekton.dev/v1beta1 1
kind: Pipeline 2
metadata:
  name: build-and-deploy 3
spec: 4
  workspaces: 5
  - name: shared-workspace
  params: 6
  - 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: "release-tech-preview-3"
  - name: IMAGE
    type: string
    description: image to be build from the code
  tasks: 7
  - 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 8
    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 9
    taskRef:
      name: apply-manifests
    workspaces:
    - name: source
      workspace: shared-workspace
    runAfter: 10
    - 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
1
Pipeline API version v1beta1.
2
Specifies the type of Kubernetes object. In this example, Pipeline.
3
Unique name of this Pipeline.
4
Specifies the definition and structure of the Pipeline.
5
Workspaces used across all the Tasks in the Pipeline.
6
Parameters used across all the Tasks in the Pipeline.
7
Specifies the list of Tasks used in the Pipeline.
8
Task build-image, which uses the buildah ClusterTask to build application images from a given Git repository.
9
Task apply-manifests, which uses a user-defined Task with the same name.
10
Specifies the sequence in which Tasks are run in a Pipeline. In this example, the apply-manifests Task is run only after the build-image Task is completed.

1.3.4. PipelineRun

A PipelineRun instantiates a Pipeline for execution with specific inputs, outputs, and execution parameters on a cluster. A corresponding TaskRun is created for each Task automatically in the PipelineRun.

All the Tasks in the Pipeline are executed in the defined sequence until all Tasks are successful or a Task fails. The status field tracks and stores the progress of each TaskRun in the PipelineRun for monitoring and auditing purpose.

The following example shows a PipelineRun to run the build-and-deploy Pipeline with relevant resources and parameters:

apiVersion: tekton.dev/v1beta1 1
kind: PipelineRun 2
metadata:
  name: build-deploy-api-pipelinerun 3
spec:
  pipelineRef:
    name: build-and-deploy 4
  params: 5
  - name: deployment-name
    value: vote-api
  - name: git-url
    value: http://github.com/openshift-pipelines/vote-api.git
  - name: IMAGE
    value: image-registry.openshift-image-registry.svc:5000/pipelines-tutorial/vote-api
  workspaces: 6
  - name: shared-workspace
    volumeClaimTemplate:
      spec:
        accessModes:
          - ReadWriteOnce
        resources:
          requests:
            storage: 500Mi
1
PipelineRun API version v1beta1.
2
Specifies the type of Kubernetes object. In this example, PipelineRun.
3
Unique name to identify this PipelineRun.
4
Name of the Pipeline to be run. In this example, build-and-deploy.
5
Specifies the list of parameters required to run the Pipeline.
6
Workspace used by the PipelineRun.

1.3.5. Workspaces

Note

It is recommended that you use Workspaces instead of PipelineResources in OpenShift Pipelines, as PipelineResources are difficult to debug, limited in scope, and make Tasks less reusable.

Workspaces declare shared storage volumes that a Task in a Pipeline needs at runtime. Instead of specifying the actual location of the volumes, Workspaces enable you to declare the filesystem or parts of the filesystem that would be required at runtime. You must provide the specific location details of the volume that is mounted into that Workspace in a TaskRun or a PipelineRun. This separation of volume declaration from runtime storage volumes makes the Tasks reusable, flexible, and independent of the user environment.

With Workspaces, you can:

  • Store Task inputs and outputs
  • Share data among Tasks
  • Use it as a mount point for credentials held in Secrets
  • Use it as a mount point for configurations held in ConfigMaps
  • Use it as a mount point for common tools shared by an organization
  • Create a cache of build artifacts that speed up jobs

You can specify Workspaces in the TaskRun or PipelineRun using:

  • A read-only ConfigMaps or Secret
  • An existing PersistentVolumeClaim shared with other Tasks
  • A PersistentVolumeClaim from a provided VolumeClaimTemplate
  • An emptyDir that is discarded when the TaskRun completes

The following example shows a code snippet of the build-and-deploy Pipeline, which declares a shared-workspace Workspace for the build-image and apply-manifests Tasks as defined in the Pipeline.

apiVersion: tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: build-and-deploy
spec:
  workspaces: 1
  - name: shared-workspace
  params:
...
  tasks: 2
  - name: build-image
   taskRef:
     name: buildah
     kind: ClusterTask
   params:
   - name: TLSVERIFY
     value: "false"
   - name: IMAGE
     value: $(params.IMAGE)
   workspaces: 3
   - name: source 4
     workspace: shared-workspace 5
   runAfter:
   - fetch-repository
 - name: apply-manifests
   taskRef:
     name: apply-manifests
   workspaces: 6
   - name: source
     workspace: shared-workspace
   runAfter:
    - build-image
...
1
List of Workspaces shared between the Tasks defined in the Pipeline. A Pipeline can define as many Workspaces as required. In this example, only one Workspace named shared-workspace is declared.
2
Definition of Tasks used in the Pipeline. This snippet defines two Tasks, build-image and apply-manifests, which share a common Workspace.
3
List of Workspaces used in the build-image Task. A Task definition can include as many Workspaces as it requires. However, it is recommended that a Task uses at most one writable Workspace.
4
Name that uniquely identifies the Workspace used in the Task. This Task uses one Workspace named source.
5
Name of the Pipeline Workspace used by the Task. Note that the Workspace source in turn uses the Pipeline Workspace named shared-workspace.
6
List of Workspaces used in the apply-manifests Task. Note that this Task shares the source Workspace with the build-image Task.

Workspaces help tasks share data, and allow you to specify one or more volumes that each task in the pipeline requires during execution. You can create a persistent volume claim or provide a volume claim template that creates a persistent volume claim for you.

The following code snippet of the build-deploy-api-pipelinerun PipelineRun uses a volume claim template to create a persistent volume claim for defining the storage volume for the shared-workspace Workspace used in the build-and-deploy Pipeline.

apiVersion: tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: build-deploy-api-pipelinerun
spec:
  pipelineRef:
    name: build-and-deploy
  params:
...

  workspaces: 1
  - name: shared-workspace 2
    volumeClaimTemplate: 3
      spec:
        accessModes:
          - ReadWriteOnce
        resources:
          requests:
            storage: 500Mi
1
Specifies the list of Pipeline Workspaces for which volume binding will be provided in the PipelineRun.
2
The name of the Workspace in the Pipeline for which the volume is being provided.
3
Specifies a volume claim template that creates a persistent volume claim to define the storage volume for the workspace.

1.3.6. Triggers

Use Triggers in conjunction with pipelines to create a full-fledged CI/CD system where Kubernetes resources define the entire CI/CD execution. Triggers capture the external events and process them to extract key pieces of information. Mapping this event data to a set of predefined parameters triggers a series of tasks that can then create and deploy Kubernetes resources and instantiate the pipeline.

For example, you define a CI/CD workflow using Red Hat OpenShift Pipelines for your application. The pipeline must start for any new changes to take effect in the application repository. Triggers automate this process by capturing and processing any change event and by triggering a pipeline run that deploys the new image with the latest changes.

Triggers consist of the following main resources that work together to form a reusable, decoupled, and self-sustaining CI/CD system:

  • The TriggerBinding resource validates events, extracts the fields from an event payload, and stores them as parameters.
  • The TriggerTemplate resource acts as a standard for the way resources must be created. It specifies the way parameterized data from the TriggerBinding resource should be used. A trigger template receives input from the trigger binding, and then performs a series of actions that results in creation of new pipeline resources, and initiation of a new pipeline run.
  • The EventListener resource provides an endpoint, or an event sink, that listens for incoming HTTP-based events with a JSON payload. It extracts event parameters from each TriggerBinding resource, and then processes this data to create Kubernetes resources as specified by the corresponding TriggerTemplate resource. The EventListener resource also performs lightweight event processing or basic filtering on the payload using event interceptors, which identify the type of payload and optionally modify it. Currently, pipeline triggers support four types of interceptors: Webhook Interceptors, GitHub Interceptors, GitLab Interceptors, and Common Expression Language (CEL) Interceptors.
  • The Trigger resource connects the TriggerBinding and TriggerTemplate resources, and this Trigger resource is referenced in the EventListener specification.

The following example shows a code snippet of the TriggerBinding resource, which extracts the Git repository information from the received event payload:

apiVersion: triggers.tekton.dev/v1alpha1 1
kind: TriggerBinding 2
metadata:
  name: vote-app 3
spec:
  params: 4
  - name: git-repo-url
    value: $(body.repository.url)
  - name: git-repo-name
    value: $(body.repository.name)
  - name: git-revision
    value: $(body.head_commit.id)
1
The API version of the TriggerBinding resource. In this example, v1alpha1.
2
Specifies the type of Kubernetes object. In this example, TriggerBinding.
3
Unique name to identify the TriggerBinding resource.
4
List of parameters which will be extracted from the received event payload and passed to the TriggerTemplate resource. In this example, the Git repository URL, name, and revision are extracted from the body of the event payload.

The following example shows a code snippet of a TriggerTemplate resource, which creates a pipeline run using the Git repository information received from the TriggerBinding resource you just created:

apiVersion: triggers.tekton.dev/v1alpha1 1
kind: TriggerTemplate 2
metadata:
  name: vote-app 3
spec:
  params: 4
  - 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: 5
  - 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
        volumeClaimTemplate:
         spec:
          accessModes:
           - ReadWriteOnce
          resources:
            requests:
              storage: 500Mi
1
The API version of the TriggerTemplate resource. In this example, v1alpha1.
2
Specifies the type of Kubernetes object. In this example, TriggerTemplate.
3
Unique name to identify the TriggerTemplate resource.
4
Parameters supplied by the TriggerBinding or EventListerner resources.
5
List of templates that specify the way resources must be created using the parameters received through the TriggerBinding or EventListener resources.

The following example shows a code snippet of a Trigger resource, named vote-trigger that connects the TriggerBinding and TriggerTemplate resources.

apiVersion: triggers.tekton.dev/v1alpha1 1
kind: Trigger 2
metadata:
  name: vote-trigger 3
spec:
  serviceAccountName: pipeline 4
  bindings:
    - ref: vote-app 5
  template: 6
     name: vote-app
1
The API version of the Trigger resource. In this example, v1alpha1.
2
Specifies the type of Kubernetes object. In this example, Trigger.
3
Unique name to identify the Trigger resource.
4
Service account name to be used.
5
Name of the TriggerBinding resource to be connected to the TriggerTemplate resource.
6
Name of the TriggerTemplate resource to be connected to the TriggerBinding resource.

The following example shows an EventListener resource, which references the Trigger resource named vote-trigger.

apiVersion: triggers.tekton.dev/v1alpha1 1
kind: EventListener 2
metadata:
  name: vote-app 3
spec:
  serviceAccountName: pipeline 4
  triggers:
    - triggerRef: vote-trigger 5
1
The API version of the EventListener resource. In this example, v1alpha1.
2
Specifies the type of Kubernetes object. In this example, EventListener.
3
Unique name to identify the EventListener resource.
4
Service account name to be used.
5
Name of the Trigger resource referenced by the EventListener resource.

1.4. Additional resources

Chapter 2. Installing OpenShift Pipelines

This guide walks cluster administrators through the process of installing the Red Hat OpenShift Pipelines Operator to an OpenShift Container Platform cluster.

Note

The Red Hat OpenShift Pipelines Operator is supported for installation in a restricted network environment. For more information, see Using Operator Lifecycle Manager on restricted networks.

Prerequisites

  • You have access to an OpenShift Container Platform cluster using an account with cluster-admin permissions.
  • You have installed oc CLI.
  • You have installed OpenShift Pipelines (tkn) CLI on your local system.

2.1. Installing the Red Hat OpenShift Pipelines Operator in web console

You can install Red Hat OpenShift Pipelines using the Operator listed in the OpenShift Container Platform OperatorHub. When you install the Red Hat OpenShift Pipelines Operator, the Custom Resources (CRs) required for the Pipelines configuration are automatically installed along with the Operator.

Procedure

  1. In the Administrator perspective of the web console, navigate to OperatorsOperatorHub.
  2. Use the Filter by keyword box to search for Red Hat OpenShift Pipelines Operator in the catalog. Click the OpenShift Pipelines Operator tile.

    Note

    Ensure that you do not select the Community version of the OpenShift Pipelines Operator.

  3. Read the brief description about the Operator on the Red Hat OpenShift Pipelines Operator page. Click Install.
  4. On the Install Operator page:

    1. Select All namespaces on the cluster (default) for the Installation Mode. This mode installs the Operator in the default openshift-operators namespace, which enables the Operator to watch and be made available to all namespaces in the cluster.
    2. Select Automatic for the Approval Strategy. This ensures that the future upgrades to the Operator are handled automatically by the Operator Lifecycle Manager (OLM). If you select the Manual approval strategy, OLM creates an update request. As a cluster administrator, you must then manually approve the OLM update request to update the Operator to the new version.
    3. Select an Update Channel.

      • The ocp-<4.x> channel enables installation of the latest stable release of the Red Hat OpenShift Pipelines Operator.
      • The preview channel enables installation of the latest preview version of the Red Hat OpenShift Pipelines Operator, which may contain features that are not yet available from the 4.x update channel.
  5. Click Install. You will see the Operator listed on the Installed Operators page.

    Note

    The Operator is installed automatically into the openshift-operators namespace.

  6. Verify that the Status is set to Succeeded Up to date to confirm successful installation of Red Hat OpenShift Pipelines Operator.

2.2. Installing the OpenShift Pipelines Operator using the CLI

You can install Red Hat OpenShift Pipelines Operator from the OperatorHub using the CLI.

Procedure

  1. Create a Subscription object YAML file to subscribe a namespace to the Red Hat OpenShift Pipelines Operator, for example, sub.yaml:

    Example Subscription

    apiVersion: operators.coreos.com/v1alpha1
    kind: Subscription
    metadata:
      name: openshift-pipelines-operator
      namespace: openshift-operators
    spec:
      channel:  <channel name> 1
      name: openshift-pipelines-operator-rh 2
      source: redhat-operators 3
      sourceNamespace: openshift-marketplace 4

    1
    Specify the channel name from where you want to subscribe the Operator
    2
    Name of the Operator to subscribe to.
    3
    Name of the CatalogSource that provides the Operator.
    4
    Namespace of the CatalogSource. Use openshift-marketplace for the default OperatorHub CatalogSources.
  2. Create the Subscription object:

    $ oc apply -f sub.yaml

    The Red Hat OpenShift Pipelines Operator is now installed in the default target namespace openshift-operators.

Additional Resources

Chapter 3. Uninstalling OpenShift Pipelines

Uninstalling the Red Hat OpenShift Pipelines Operator is a two-step process:

  1. Delete the Custom Resources (CRs) that were added by default when you installed the Red Hat OpenShift Pipelines Operator.
  2. Uninstall the Red Hat OpenShift Pipelines Operator.

Uninstalling only the Operator will not remove the Red Hat OpenShift Pipelines components created by default when the Operator is installed.

3.1. Deleting the Red Hat OpenShift Pipelines components and Custom Resources

Delete the Custom Resources (CRs) created by default during installation of the Red Hat OpenShift Pipelines Operator.

Procedure

  1. In the Administrator perspective of the web console, navigate to AdministrationCustom Resource Definition.
  2. Type config.operator.tekton.dev in the Filter by name box to search for the Red Hat OpenShift Pipelines Operator CRs.
  3. Click CRD Config to see the Custom Resource Definition Details page.
  4. Click the Actions drop-down menu and select Delete Custom Resource Definition.

    Note

    Deleting the CRs will delete the Red Hat OpenShift Pipelines components, and all the Tasks and Pipelines on the cluster will be lost.

  5. Click Delete to confirm the deletion of the CRs.

3.2. Uninstalling the Red Hat OpenShift Pipelines Operator

Procedure

  1. From the OperatorsOperatorHub page, use the Filter by keyword box to search for Red Hat OpenShift Pipelines Operator.
  2. Click the OpenShift Pipelines Operator tile. The Operator tile indicates it is installed.
  3. In the OpenShift Pipelines Operator descriptor page, click Uninstall.

Additional Resources

Chapter 4. Creating CI/CD solutions for applications using OpenShift Pipelines

With Red Hat OpenShift Pipelines, you can create a customized CI/CD solution to build, test, and deploy your application.

To create a full-fledged, self-serving CI/CD pipeline for an application, you must perform the following tasks:

  • Create custom tasks, or install existing reusable tasks.
  • Create and define the delivery pipeline for your application.
  • Provide a storage volume or filesystem that is attached to a workspace for the pipeline execution using one of the following approaches:

    • Specify a volume claim template that creates a persistent volume claim
    • Specify a persistent volume claim
  • Create a PipelineRun object to instantiate and invoke the pipeline.
  • Add triggers to capture events in the source repository.

This section uses the pipelines-tutorial example to demonstrate the preceding tasks. The example uses a simple application which consists of:

  • A front-end interface, vote-ui, with the source code in the ui-repo Git repository.
  • A back-end interface, vote-api, with the source code in the api-repo Git repository.
  • The apply-manifests and update-deployment tasks in the pipelines-tutorial Git repository.

4.1. Prerequisites

  • You have access to an OpenShift Container Platform cluster.
  • You have installed OpenShift Pipelines using the Red Hat OpenShift Pipelines Operator listed in the OpenShift OperatorHub. Once installed, it is applicable to the entire cluster.
  • You have installed OpenShift Pipelines CLI.
  • You have forked the front-end ui-repo and back-end api-repo Git repositories using your GitHub ID, and have Administrator access to these repositories.
  • Optional: You have cloned the pipelines-tutorial Git repository.

4.2. Creating a project and checking your Pipeline ServiceAccount

Procedure

  1. Log in to your OpenShift Container Platform cluster:

    $ oc login -u <login> -p <password> https://openshift.example.com:6443
  2. Create a project for the sample application. For this example workflow, create the pipelines-tutorial project:

    $ oc new-project pipelines-tutorial
    Note

    If you create a project with a different name, be sure to update the resource URLs used in the example with your project name.

  3. View the pipeline ServiceAccount:

    Red Hat OpenShift Pipelines Operator adds and configures a ServiceAccount named pipeline that has sufficient permissions to build and push an image. This ServiceAccount is used by PipelineRun.

    $ oc get serviceaccount pipeline

4.3. Creating Pipeline Tasks

Procedure

  1. Install the apply-manifests and update-deployment Task resources from the pipelines-tutorial repository, which contains a list of reusable tasks for pipelines:

    $ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/release-tech-preview-3/01_pipeline/01_apply_manifest_task.yaml
    $ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/release-tech-preview-3/01_pipeline/02_update_deployment_task.yaml
  2. Use the tkn task list command to list the tasks you created:

    $ tkn task list

    The output verifies that the apply-manifests and update-deployment Task resources were created:

    NAME                DESCRIPTION   AGE
    apply-manifests                   1 minute ago
    update-deployment                 48 seconds ago
  3. Use the tkn clustertasks list command to list the Operator-installed additional ClusterTask resources, for example --buildah and s2i-python-3:

    Note

    You must use a privileged pod container to run the buildah ClusterTask resource because it requires a privileged security context. To learn more about security context constraints (SCC) for pods, see the Additional resources section.

    $ tkn clustertasks list

    The output lists the Operator-installed ClusterTask resources:

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

4.4. Assembling a Pipeline

A Pipeline represents a CI/CD flow and is defined by the Tasks to be executed. It is designed to be generic and reusable in multiple applications and environments.

A Pipeline specifies how the Tasks interact with each other and their order of execution using the from and runAfter parameters. It uses the workspaces field to specify one or more volumes that each Task in the Pipeline requires during execution.

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

The Pipeline performs the following tasks for the back-end application vote-api and front-end application vote-ui:

  • Clones the source code of the application from the Git repository by referring to the git-url and git-revision parameters.
  • Builds the container image using the buildah ClusterTask.
  • Pushes the image to the internal image registry by referring to the image parameter.
  • Deploys the new image on OpenShift Container Platform by using the apply-manifests and update-deployment Tasks.

Procedure

  1. Copy the contents of the following sample Pipeline YAML file and save it:

    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: "release-tech-preview-3"
      - 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

    The Pipeline definition abstracts away the specifics of the Git source repository and image registries. These details are added as params when a Pipeline is triggered and executed.

  2. Create the Pipeline:

    $ oc create -f <pipeline-yaml-file-name.yaml>

    Alternatively, you can also execute the YAML file directly from the Git repository:

    $ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/release-tech-preview-3/01_pipeline/04_pipeline.yaml
  3. Use the tkn pipeline list command to verify that the Pipeline is added to the application:

    $ tkn pipeline list

    The output verifies that the build-and-deploy Pipeline was created:

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

4.5. Running a Pipeline

A PipelineRun resource starts a pipeline and ties it to the Git and image resources that should be used for the specific invocation. It automatically creates and starts the TaskRun resources for each task in the pipeline.

Procedure

  1. Start the pipeline for the back-end application:

    $ tkn pipeline start build-and-deploy \
        -w name=shared-workspace,volumeClaimTemplateFile=https://raw.githubusercontent.com/openshift/pipelines-tutorial/release-tech-preview-3/01_pipeline/03_persistent_volume_claim.yaml \
        -p deployment-name=vote-api \
        -p git-url=http://github.com/openshift-pipelines/vote-api.git \
        -p IMAGE=image-registry.openshift-image-registry.svc:5000/pipelines-tutorial/vote-api \

    The previous command uses a volume claim template, which creates a persistent volume claim for the pipeline execution.

  2. To track the progress of the pipeline run, enter the following command::

    $ tkn pipelinerun logs <pipelinerun_id> -f

    The <pipelinerun_id> in the above command is the ID for the PipelineRun that was returned in the output of the previous command.

  3. Start the Pipeline for the front-end application:

    $ tkn pipeline start build-and-deploy \
        -w name=shared-workspace,volumeClaimTemplateFile=https://raw.githubusercontent.com/openshift/pipelines-tutorial/release-tech-preview-3/01_pipeline/03_persistent_volume_claim.yaml \
        -p deployment-name=vote-ui \
        -p git-url=http://github.com/openshift-pipelines/vote-ui.git \
        -p IMAGE=image-registry.openshift-image-registry.svc:5000/pipelines-tutorial/vote-ui \
  4. To track the progress of the pipeline run, enter the following command:

    $ tkn pipelinerun logs <pipelinerun_id> -f

    The <pipelinerun_id> in the above command is the ID for the PipelineRun that was returned in the output of the previous command.

  5. After a few minutes, use tkn pipelinerun list command to verify that the Pipeline ran successfully by listing all the PipelineRuns:

    $ tkn pipelinerun list

    The output lists the PipelineRuns:

     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
  6. Get the application route:

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

    Note the output of the previous command. You can access the application using this route.

  7. To rerun the last pipeline run, using the pipeline resources and service account of the previous pipeline, run:

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

4.6. Adding Triggers to a Pipeline

Triggers enable pipelines to respond to external GitHub events, such as push events and pull requests. After you assemble and start a Pipeline for the application, add the TriggerBinding, TriggerTemplate, Trigger, and EventListener resources to capture the GitHub events.

Procedure

  1. Copy the content of the following sample TriggerBinding YAML file and save it:

    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)
  2. Create the TriggerBinding resource:

    $ oc create -f <triggerbinding-yaml-file-name.yaml>

    Alternatively, you can create the TriggerBinding resource directly from the pipelines-tutorial Git repository:

    $ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/release-tech-preview-3/03_triggers/01_binding.yaml
  3. Copy the content of the following sample TriggerTemplate YAML file and save it:

    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: release-tech-preview-3
      - 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
            volumeClaimTemplate:
              spec:
                accessModes:
                  - ReadWriteOnce
                resources:
                  requests:
                    storage: 500Mi

    The template specifies a volume claim template to create a persistent volume claim for defining the storage volume for the workspace. Therefore, you do not need to create a persistent volume claim to provide data storage.

  4. Create the TriggerTemplate resource:

    $ oc create -f <triggertemplate-yaml-file-name.yaml>

    Alternatively, you can create the TriggerTemplate resource directly from the pipelines-tutorial Git repository:

    $ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/release-tech-preview-3/03_triggers/02_template.yaml
  5. Copy the contents of the following sample Trigger YAML file and save it:

    apiVersion: triggers.tekton.dev/v1alpha1
    kind: Trigger
    metadata:
      name: vote-trigger
    spec:
      serviceAccountName: pipeline
      bindings:
        - ref: vote-app
      template:
         name: vote-app
  6. Create the Trigger resource:

    $ oc create -f <trigger-yaml-file-name.yaml>

    Alternatively, you can create the Trigger resource directly from the pipelines-tutorial Git repository:

    $ oc create -f https://github.com/openshift/pipelines-tutorial/blob/release-tech-preview-3/03_triggers/03_trigger.yaml
  7. Copy the contents of the following sample EventListener YAML file and save it:

    apiVersion: triggers.tekton.dev/v1alpha1
    kind: EventListener
    metadata:
      name: vote-app
    spec:
      serviceAccountName: pipeline
      triggers:
        - triggerRef: vote-trigger
  8. Create the EventListener resource:

    $ oc create -f <eventlistener-yaml-file-name.yaml>

    Alternatively, you can create the EvenListener resource directly from the pipelines-tutorial Git repository:

    $ oc create -f https://raw.githubusercontent.com/openshift/pipelines-tutorial/release-tech-preview-3/03_triggers/04_event_listener.yaml
  9. Expose the EventListener service as an OpenShift Container Platform route to make it publicly accessible:

    $ oc expose svc el-vote-app

4.7. Creating Webhooks

Webhooks are HTTP POST messages that are received by the EventListeners whenever a configured event occurs in your repository. The event payload is then mapped to TriggerBindings, and processed by TriggerTemplates. The TriggerTemplates eventually start one or more PipelineRuns, leading to the creation and deployment of Kubernetes resources.

In this section, you will configure a Webhook URL on your forked Git repositories vote-ui and vote-api. This URL points to the publicly accessible EventListener service route.

Note

Adding Webhooks requires administrative privileges to the repository. If you do not have administrative access to your repository, contact your system administrator for adding Webhooks.

Procedure

  1. Get the Webhook URL:

    $ echo "URL: $(oc  get route el-vote-app --template='http://{{.spec.host}}')"

    Note the URL obtained in the output.

  2. Configure Webhooks manually on the front-end repository:

    1. Open the front-end Git repository vote-ui in your browser.
    2. Click SettingsWebhooksAdd Webhook
    3. On the Webhooks/Add Webhook page:

      1. Enter the Webhook URL from step 1 in Payload URL field
      2. Select application/json for the Content type
      3. Specify the secret in the Secret field
      4. Ensure that the Just the push event is selected
      5. Select Active
      6. Click Add Webhook
  3. Repeat step 2 for the back-end repository vote-api.

4.8. Triggering a pipeline run

Whenever a push event occurs in the Git repository, the configured Webhook sends an event payload to the publicly exposed EventListener service route. The EventListener service of the application processes the payload, and passes it to the relevant TriggerBinding and TriggerTemplate resource pairs. The TriggerBinding resource extracts the parameters and the TriggerTemplate resource uses these parameters and specifies the way the resources must be created. This may rebuild and redeploy the application.

In this section, you push an empty commit to the front-end vote-ui repository, which then triggers the pipeline run.

Procedure

  1. From the terminal, clone your forked Git repository vote-ui:

    $ git clone git@github.com:<your GitHub ID>/vote-ui.git -b release-tech-preview-3
  2. Push an empty commit:

    $ git commit -m "empty-commit" --allow-empty && git push origin release-tech-preview-3
  3. Check if the pipeline run was triggered:

    $ tkn pipelinerun list

    Notice that a new pipeline run was initiated.

4.9. Additional resources

Chapter 5. Working with Red Hat OpenShift Pipelines using the Developer perspective

You can use the Developer perspective of the OpenShift Container Platform web console to create CI/CD Pipelines for your software delivery process.

In the Developer perspective:

  • Use the AddPipelinePipeline Builder option to create customized Pipelines for your application.
  • Use the AddFrom Git option to create Pipelines using operator-installed Pipeline templates and resources while creating an application on OpenShift Container Platform.

After you create the Pipelines for your application, you can view and visually interact with the deployed Pipelines in the Pipelines view. You can also use the Topology view to interact with the Pipelines created using the From Git option. You need to apply custom labels to a Pipeline created using the Pipeline Builder to see it in the Topology view.

Prerequisites

  • You have access to an OpenShift Container Platform cluster and have switched to the Developer perspective in the web console.
  • You have the OpenShift Pipelines Operator installed in your cluster.
  • You are a cluster administrator or a user with create and edit permissions.
  • You have created a project.

5.1. Constructing Pipelines using the Pipeline Builder

In the Developer perspective of the console, you can use the AddPipelinePipeline Builder option to:

  • Construct a Pipeline flow using existing Tasks and ClusterTasks. When you install the OpenShift Pipelines Operator, it adds reusable Pipeline ClusterTasks to your cluster.
  • Specify the type of resources required for the Pipeline Run, and if required, add additional parameters to the Pipeline.
  • Reference these Pipeline resources in each of the Tasks in the Pipeline as input and output resources.
  • The parameters for a Task are prepopulated based on the specifications of the Task. If required, reference any additional parameters added to the Pipeline in the Task.

Procedure

  1. In the Add view of the Developer perspective, click the Pipeline tile to see the Pipeline Builder page.
  2. Enter a unique name for the Pipeline.
  3. Select a Task from the Select task list to add a Task to the Pipeline. This example uses the s2i-nodejs Task.

    1. To add sequential Tasks to the Pipeline, click the plus icon to the right or left of the Task, and from the Select task list, select the Task you want to add to the Pipeline. For this example, use the plus icon to the right of the s2i-nodejs Task to add an openshift-client Task.
    2. To add a parallel Task to the existing Task, click the plus icon displayed below the Task, and from the Select Task list, select the parallel Task you want to add to the Pipeline.

      Figure 5.1. Pipeline Builder

      op pipeline builder
  4. Click Add Resources to specify the name and type of resources that the Pipeline Run will use. These resources are then used by the Tasks in the Pipeline as inputs and outputs. For this example:

    1. Add an input resource. In the Name field, enter Source, and from the Resource Type drop-down list, select Git.
    2. Add an output resource. In the Name field, enter Img, and from the Resource Type drop-down list, select Image.
  5. The Parameters for a Task are prepopulated based on the specifications of the Task. If required, use the Add Parameters link to add additional parameters.
  6. A Missing Resources warning is displayed on a Task if the resources for the Task are not specified. Click the s2i-nodejs Task to see the side panel with details for the Task.

    Figure 5.2. Tasks details in Pipelines Builder

    op pipeline builder task details
  7. In the Task side panel, specify the resources and parameters for it:

    1. In the Input ResourcesSource section, the Select Resources drop-down list displays the resources that you added to the Pipeline. For this example, select Source.
    2. In the Output ResourcesImage section, click the Select Resources list, and select Img.
    3. If required, in the Parameters section, add more parameters to the default ones, by using the $(params.<param-name>) syntax.
  8. Similarly, add an input resource for the openshift-client Task.
  9. Click Create to create the Pipeline. You are redirected to the Pipeline Details page that displays the details of the created Pipeline. You can now use the Action button to start the Pipeline.

Optionally, you can also use the Edit YAML link, on the upper right of the Pipeline Builder page, to directly modify a Pipeline YAML file in the console. You can also use the operator-installed, reusable snippets and samples to create detailed Pipelines.

5.2. Creating applications with OpenShift Pipelines

To create Pipelines along with applications, use the From Git option in the Add view of the Developer perspective. For more information, see Creating applications using the Developer perspective.

5.3. Interacting with Pipelines using the Developer perspective

The Pipelines view in the Developer perspective lists all the Pipelines in a project along with details, such as the namespace in which the Pipeline was created, the last PipelineRun, the status of the Tasks in the PipelineRun, the status of the PipelineRun, and the time taken for the run.

Procedure

  1. In the Pipelines view of the Developer perspective, select a project from the Project drop-down list to see the Pipelines in that project.

    Figure 5.3. Pipelines view in the Developer perspective

    op pipeline list
  2. Click the required Pipeline to see the Pipeline Details page. This page provides a visual representation of all the serial and parallel Tasks in the Pipeline. The Tasks are also listed at the lower right of the page. You can click the listed Tasks to view Task details.
  3. Optionally, in the Pipeline Details page:

    • Click the YAML tab to edit the YAML file for the Pipeline.
    • Click the Pipeline Runs tab to see the completed, running, or failed runs for the Pipeline. You can use the Options menu kebab to stop a running Pipeline, to rerun a Pipeline using the same parameters and resources as that of the previous Pipeline execution, or to delete a PipelineRun.
    • Click the Parameters tab to see the parameters defined in the Pipeline. You can also add or edit additional parameters as required.
    • Click the Resources tab to see the resources defined in the Pipeline. You can also add or edit additional resources as required.

5.4. Starting Pipelines

After you create a Pipeline, you need to start it to execute the included Tasks in the defined sequence. You can start a Pipeline Run from the Pipelines view, Pipeline Details page, or the Topology view.

Procedure

To start a Pipeline using the Pipelines view:

  1. In the Pipelines view of the Developer perspective, click the Options kebab menu adjoining a Pipeline, and select Start.
  2. The Start Pipeline dialog box displays the Git Resources and the Image Resources based on the Pipeline definition.

    Note

    For Pipelines created using the From Git option, the Start Pipeline dialog box also displays an APP_NAME field in the Parameters section, and all the fields in the dialog box are prepopulated by the Pipeline templates.

    1. If you have resources in your namespace, the Git Resources and the Image Resources fields are prepopulated with those resources. If required, use the drop-downs to select or create the required resources and customize the Pipeline Run instance.
  3. Optional: Modify the Advanced Options to add credentials to authenticate the specified private Git server or Docker registry.

    1. Under Advanced Options, click Show Credentials Options and select Add Secret.
    2. In the Create Source Secret section, specify the following:

      1. A unique Secret Name for the secret.
      2. In the Designated provider to be authenticated section, specify the provider to be authenticated in the Access to field, and the base Server URL.
      3. Select the Authentication Type and provide the credentials:

        • For the Authentication Type Image Registry Crendentials, specify the Registry Server Address that you want to authenticate, and provide your credentials in the Username, Password, and Email fields.

          Select Add Credentials if you want to specify an additional Registry Server Address.

        • For the Authentication Type Basic Authentication, specify the values for the UserName and Password or Token fields.
        • For the Authentication Type SSH Keys, specify the value for the SSH Private Key field.
      4. Select the check mark to add the secret.

    You can add multiple secrets based upon the number of resources in your Pipeline.

  4. Click Start to start the PipelineRun.
  5. The Pipeline Run Details page displays the Pipeline being executed. After the Pipeline starts, the Tasks and Steps within each Task are executed. You can:

    • Hover over the Tasks to see the time taken for the execution of each Step.
    • Click on a Task to see logs for each of the Steps in the Task.
    • Click the Logs tab to see the logs according to the execution sequence of the Tasks and use the Download button to download the logs to a text file.

      Figure 5.4. Pipeline run

      op pipeline run
  6. For Pipelines created using the From Git option, you can use the Topology view to interact with Pipelines after you start them:

    Note

    To see Pipelines created using the Pipeline Builder in the Topology view, customize the Pipeline labels to link the Pipeline with the application workload.

    1. On the left navigation panel, click Topology, and click on the application to see the Pipeline Runs listed in the side panel.
    2. In the Pipeline Runs section, click Start Last Run to start a new Pipeline Run with the same parameters and resources as the previous ones. This option is disabled if a Pipeline Run has not been initiated.

      Figure 5.5. Pipelines on the Topology view

      op pipeline topology
    3. In the Topology page, hover to the left of the application to see the status of the Pipeline Run for the application.

5.5. Editing Pipelines

You can edit the Pipelines in your cluster using the Developer perspective of the web console:

Procedure

  1. In the Pipelines view of the Developer perspective, select the Pipeline you want to edit to see the details of the Pipeline. In the Pipeline Details page, click Actions and select Edit Pipeline.
  2. In the Pipeline Builder page:

    • You can add additional Tasks, parameters, or resources to the Pipeline.
    • You can click the Task you want to modify to see the Task details in the side panel and modify the required Task details, such as the display name, parameters and resources.
    • Alternatively, to delete the Task, click the Task, and in the side panel, click Actions and select Remove Task.
  3. Click Save to save the modified Pipeline.

5.6. Deleting Pipelines

You can delete the Pipelines in your cluster using the Developer perspective of the web console.

Procedure

  1. In the Pipelines view of the Developer perspective, click the Options kebab menu adjoining a Pipeline, and select Delete Pipeline.
  2. In the Delete Pipeline confirmation prompt, click Delete to confirm the deletion.

Chapter 6. Red Hat OpenShift Pipelines release notes

Red Hat OpenShift Pipelines is a cloud-native CI/CD experience based on the Tekton project which provides:

  • Standard Kubernetes-native pipeline definitions (CRDs).
  • Serverless pipelines with no CI server management overhead.
  • Extensibility to build images using any Kubernetes tool, such as S2I, Buildah, JIB, and Kaniko.
  • Portability across any Kubernetes distribution.
  • Powerful CLI for interacting with pipelines.
  • Integrated user experience with the Developer perspective of the OpenShift Container Platform web console.

For an overview of Red Hat OpenShift Pipelines, see Understanding OpenShift Pipelines.

6.1. Getting support

If you experience difficulty with a procedure described in this documentation, visit the Red Hat Customer Portal to learn more about Red Hat Technology Preview features support scope.

For questions and feedback, you can send an email to the product team at pipelines-interest@redhat.com.

6.2. Release notes for Red Hat OpenShift Pipelines Technology Preview 1.2

6.2.1. New features

Red Hat OpenShift Pipelines Technology Preview (TP) 1.2 is now available on OpenShift Container Platform 4.6. Red Hat OpenShift Pipelines TP 1.2 is updated to support:

  • Tekton Pipelines 0.16.3
  • Tekton tkn CLI 0.13.1
  • Tekton Triggers 0.8.1
  • ClusterTasks based on Tekton Catalog 0.16

In addition to the fixes and stability improvements, here is a highlight of what’s new in OpenShift Pipelines 1.2.

6.2.1.1. Pipelines

  • This release of Red Hat OpenShift Pipelines adds support for a disconnected installation.
  • You can now use the when field, instead of conditions, to run a task only when certain criteria are met. The key components of WhenExpressions are Input, Operator, and Values. If all the WhenExpressions evaluate to True, then the task is run. If any of the WhenExpressions evaluate to False, the task is skipped.
  • Step statuses are now updated if a task run is canceled or times out.
  • Support for Git Large File Storage (LFS) is now available to build the base image used by git-init.
  • You can now use the taskSpec field to specify metadata, such as labels and annotations, when a task is embedded in a pipeline.
  • Cloud events are now supported by pipeline runs. Retries with backoff are now enabled for cloud events sent by the cloud event pipeline resource.
  • You can now set a default Workspace configuration for any workspace that a Task resource declares, but that a TaskRun resource does not explicitly provide.
  • Support is available for namespace variable interpolation for the PipelineRun namespace and TaskRun namespace.
  • Validation for TaskRun objects is now added to check that not more than one persistent volume claim workspace is used when a TaskRun resource is associated with an Affinity Assistant. If more than one persistent volume claim workspace is used, the task run fails with a TaskRunValidationFailed condition. Note that by default, the Affinity Assistant is disabled in Red Hat OpenShift Pipelines, so you will need to enable the assistant to use it.

6.2.1.2. Pipelines CLI

  • The tkn task describe, tkn taskrun describe, tkn clustertask describe, tkn pipeline describe, and tkn pipelinerun describe commands now:

    • Automatically select the Task, TaskRun, ClusterTask, Pipeline and PipelineRun resource, respectively, if only one of them is present.
    • Display the results of the Task, TaskRun, ClusterTask, Pipeline and PipelineRun resource in their outputs, respectively.
    • Display workspaces declared in the Task, TaskRun, ClusterTask, Pipeline and PipelineRun resource in their outputs, respectively.
  • You can now use the --prefix-name option with the tkn clustertask start command to specify a prefix for the name of a task run.
  • Interactive mode support has now been provided to the tkn clustertask start command.
  • You can now specify PodTemplate properties supported by pipelines using local or remote file definitions for TaskRun and PipelineRun objects.
  • You can now use the --use-params-defaults option with the tkn clustertask start command to use the default values set in the ClusterTask configuration and create the task run.
  • The --use-param-defaults flag for the tkn pipeline start command now prompts the interactive mode if the default values have not been specified for some of the parameters.

6.2.1.3. Triggers

  • The Common Expression Language (CEL) function named parseYAML has been added to parse a YAML string into a map of strings.
  • Error messages for parsing CEL expressions have been improved to make them more granular while evaluating expressions and when parsing the hook body for creating the evaluation environment.
  • Support is now available for marshaling boolean values and maps if they are used as the values of expressions in a CEL overlay mechanism.
  • The following fields have been added to the EventListener object:

    • The replicas field enables the event listener to run more than one pod by specifying the number of replicas in the YAML file.
    • The NodeSelector field enables the EventListener object to schedule the event listener pod to a specific node.
  • Webhook interceptors can now parse the EventListener-Request-URL header to extract parameters from the original request URL being handled by the event listener.
  • Annotations from the event listener can now be propagated to the deployment, services, and other pods. Note that custom annotations on services or deployment are overwritten, and hence, must be added to the event listener annotations so that they are propagated.
  • Proper validation for replicas in the EventListener specification is now available for cases when a user specifies the spec.replicas values as negative or zero.
  • You can now specify the TriggerCRD object inside the EventListener spec as a reference using the TriggerRef field to create the TriggerCRD object separately and then bind it inside the EventListener spec.
  • Validation and defaults for the TriggerCRD object are now available.

6.2.2. Deprecated features

  • $(params) are now deprecated and replaced by $(tt.params) to avoid confusion between the resourcetemplate and triggertemplate parameters.
  • The ServiceAccount reference of the optional EventListenerTrigger-based authentication level has changed from an object reference to a ServiceAccountName string. This ensures that the ServiceAccount reference is in the same namespace as the EventListenerTrigger object.
  • The Conditions custom resource definition (CRD) is now deprecated; use the WhenExpressions CRD instead.
  • The PipelineRun.Spec.ServiceAccountNames object is being deprecated and replaced by the PipelineRun.Spec.TaskRunSpec[].ServiceAccountName object.

6.2.3. Known issues

  • This release of Red Hat OpenShift Pipelines adds support for a disconnected installation. However, some images used by the cluster tasks must be mirrored for them to work in disconnected clusters.
  • Pipelines in the openshift namespace are not deleted after you uninstall the Red Hat OpenShift Pipelines Operator. Use the oc delete pipelines -n openshift --all command to delete the pipelines.
  • Uninstalling the Red Hat OpenShift Pipelines Operator does not remove the event listeners.

    As a workaround, to remove the EventListener and Pod CRDs:

    1. Edit the EventListener object with the foregroundDeletion finalizers:

      oc patch el/<eventlistener_name> -p '{"metadata":{"finalizers":["foregroundDeletion"]}}' --type=merge

      For example:

      oc patch el/github-listener-interceptor -p '{"metadata":{"finalizers":["foregroundDeletion"]}}' --type=merge
    2. Delete the EventListener CRD:

      oc patch crd/eventlisteners.triggers.tekton.dev -p '{"metadata":{"finalizers":[]}}' --type=merge

6.2.4. Fixed issues

  • A simple syntax validation to check the CEL filter, overlays in the Webhook validator, and the expressions in the interceptor has now been added.
  • Triggers no longer overwrite annotations set on the underlying deployment and service objects.
  • Previously, an event listener would stop accepting events. This fix adds an idle timeout of 120 seconds for the EventListener sink to resolve this issue.
  • Previously, canceling a pipeline run with a Failed(Canceled) state gave a success message. This has been fixed to display an error instead.
  • The tkn eventlistener list command now provides the status of the listed event listeners, thus enabling you to easily identify the available ones.
  • Consistent error messages are now displayed for the triggers list and triggers describe commands when triggers are not installed or when a resource cannot be found.
  • Previously, a large number of idle connections would build up during cloud event delivery. The DisableKeepAlives: true parameter was added to the cloudeventclient config to fix this issue. Thus, a new connection is set up for every cloud event.
  • Previously, the creds-init code would write empty files to the disk even if credentials of a given type were not provided. This fix modifies the creds-init code to write files for only those credentials that have actually been mounted from correctly annotated secrets.

6.3. Release notes for Red Hat OpenShift Pipelines Technology Preview 1.1

6.3.1. New features

Red Hat OpenShift Pipelines Technology Preview (TP) 1.1 is now available on OpenShift Container Platform 4.6. Red Hat OpenShift Pipelines TP 1.1 is updated to support:

  • Tekton Pipelines 0.14.3
  • Tekton tkn CLI 0.11.0
  • Tekton Triggers 0.6.1
  • ClusterTasks based on Tekton Catalog 0.14

In addition to the fixes and stability improvements, here is a highlight of what’s new in OpenShift Pipelines 1.1.

6.3.1.1. Pipelines

  • Workspaces can now be used instead of PipelineResources. It is recommended that you use Workspaces in OpenShift Pipelines, as PipelineResources are difficult to debug, limited in scope, and make Tasks less reusable. For more details on Workspaces, see Understanding OpenShift Pipelines.
  • Workspace support for VolumeClaimTemplates has been added:

    • The VolumeClaimTemplate for a PipelineRun and TaskRun can now be added as a volume source for Workspaces. The tekton-controller then creates a PersistentVolumeClaim (PVC) using the template that is seen as a PVC for all TaskRuns in the Pipeline. Thus you do not need to define the PVC configuration every time it binds a workspace that spans multiple tasks.
    • Support to find the name of the PersistentVolumeClaim when a VolumeClaimTemplate is used as a volume source is now available using variable substitution.
  • Support for improving audits:

    • The PipelineRun.Status field now contains the status of every TaskRun in the Pipeline and the Pipeline specification used to instantiate a PipelineRun to monitor the progress of the PipelineRun.
    • Pipeline results have been added to the pipeline specification and PipelineRun status.
    • The TaskRun.Status field now contains the exact Task specification used to instantiate the TaskRun.
  • Support to apply the default parameter to Conditions.
  • A TaskRun created by referencing a ClusterTask now adds the tekton.dev/clusterTask label instead of the tekton.dev/task label.
  • The kubeconfigwriter now adds the ClientKeyData and the ClientCertificateData configurations in the Resource structure to enable replacement of the pipeline resource type cluster with the kubeconfig-creator Task.
  • The names of the feature-flags and the config-defaults ConfigMaps are now customizable.
  • Support for HostNetwork in the PodTemplate used by TaskRun is now available.
  • An Affinity Assistant is now available to support node affinity in TaskRuns that share workspace volume. By default, this is disabled on OpenShift Pipelines.
  • The PodTemplate has been updated to specify imagePullSecrets to identify secrets that the container runtime should use to authorize container image pulls when starting a pod.
  • Support for emitting warning events from the TaskRun controller if the controller fails to update the TaskRun.
  • Standard or recommended k8s labels have been added to all resources to identify resources belonging to an application or component.
  • The Entrypoint process is now notified for signals and these signals are then propagated using a dedicated PID Group of the Entrypoint process.
  • The PodTemplate can now be set on a Task level at runtime using TaskRunSpecs.
  • Support for emitting Kubernetes events:

    • The controller now emits events for additional TaskRun lifecycle events - taskrun started and taskrun running.
    • The PipelineRun controller now emits an event every time a Pipeline starts.
  • In addition to the default Kubernetes events, support for CloudEvents for TaskRuns is now available. The controller can be configured to send any TaskRun events, such as create, started, and failed, as cloud events.
  • Support for using the $context.<task|taskRun|pipeline|pipelineRun>.name variable to reference the appropriate name when in PipelineRuns and TaskRuns.
  • Validation for PipelineRun parameters is now available to ensure that all the parameters required by the Pipeline are provided by the PipelineRun. This also allows PipelineRuns to provide extra parameters in addition to the required parameters.
  • You can now specify Tasks within a Pipeline that will always execute before the pipeline exits, either after finishing all tasks successfully or after a Task in the Pipeline failed, using the finally field in the Pipeline YAML file.
  • The git-clone ClusterTask is now available.

6.3.1.2. Pipelines CLI

  • Support for embedded Trigger binding is now available to the tkn evenlistener describe command.
  • Support to recommend subcommands and make suggestions if an incorrect subcommand is used.
  • The tkn task describe command now auto selects the task if only one task is present in the Pipeline.
  • You can now start a Task using default parameter values by specifying the --use-param-defaults flag in the tkn task start command.
  • You can now specify a volumeClaimTemplate for PipelineRuns or TaskRuns using the --workspace option with the tkn pipeline start or tkn task start commands.
  • The tkn pipelinerun logs command now displays logs for the final tasks listed in the finally section.
  • Interactive mode support has now been provided to the tkn task start command and the describe subcommand for the following tkn resources: pipeline, pipelinerun, task, taskrun, clustertask, and pipelineresource.
  • The tkn version command now displays the version of the Triggers installed in the cluster.
  • The tkn pipeline describe command now displays parameter values and timeouts specified for Tasks used in the Pipeline.
  • Support added for the --last option for the tkn pipelinerun describe and the tkn taskrun describe commands to describe the most recent PipelineRun or TaskRun, respectively.
  • The tkn pipeline describe command now displays the conditions applicable to the Tasks in the Pipeline.
  • You can now use the --no-headers and --all-namespaces flags with the tkn resource list command.

6.3.1.3. Triggers

  • The following Common Expression Language (CEL) functions are now available:

    • parseURL to parse and extract portions of a URL
    • parseJSON to parse JSON value types embedded in a string in the payload field of the deployment webhook
  • A new interceptor for webhooks from Bitbucket has been added.
  • EventListeners now display the Address URL and the Available status as additional fields when listed with the kubectl get command.
  • TriggerTemplate params now use the $(tt.params.<paramName>) syntax instead of $(params.<paramName>) to reduce the confusion between TriggerTemplate and ResourceTemplates params.
  • You can now add tolerations in the EventListener CRD to ensure that EventListeners are deployed with the same configuration even if all nodes are tainted due to security or management issues.
  • You can now add a Readiness Probe for EventListener Deployment at URL/live.
  • Support for embedding TriggerBinding specifications in EventListener Triggers.
  • Trigger resources are now annotated with the recommended app.kubernetes.io labels.

6.3.2. Deprecated features

The following items are deprecated in this release:

  • The --namespace or -n flags for all cluster-wide commands, including the clustertask and clustertriggerbinding commands, are deprecated. It will be removed in a future release.
  • The name field in triggers.bindings within an EventListener has been deprecated in favor of the ref field and will be removed in a future release.
  • Variable interpolation in TriggerTemplates using $(params) has been deprecated in favor of using $(tt.params) to reduce confusion with the Pipeline variable interpolation syntax. The $(params.<paramName>) syntax will be removed in a future release.
  • The tekton.dev/task label is deprecated on ClusterTasks.
  • The TaskRun.Status.ResourceResults.ResourceRef field is deprecated and will be removed.
  • The tkn pipeline create, tkn task create, and tkn resource create -f subcommands have been removed.
  • Namespace validation has been removed from tkn commands.
  • The default timeout of 1h and the -t flag for the tkn ct start command have been removed.
  • The s2i ClusterTask has been deprecated.

6.3.3. Known issues

  • Conditions do not support Workspaces.
  • The --workspace option and the interactive mode is not supported for the tkn clustertask start command.
  • Support of backward compatibility for $(params.<paramName>) forces you to use TriggerTemplates with pipeline specific params as the Triggers webhook is unable to differentiate Trigger params from pipelines params.
  • Pipeline metrics report incorrect values when you run a promQL query for tekton_taskrun_count and tekton_taskrun_duration_seconds_count.
  • PipelineRuns and TaskRuns continue to be in the Running and Running(Pending) states respectively even when a non existing PVC name is given to a Workspace.

6.3.4. Fixed issues

  • Previously, the tkn task delete <name> --trs command would delete both the Task and ClusterTask if the name of the Task and ClusterTask were the same. With this fix, the command deletes only the TaskRuns that are created by the Task <name>.
  • Previously the tkn pr delete -p <name> --keep 2 command would disregard the -p flag when used with the --keep flag and would delete all the PipelineRuns except the latest two. With this fix, the command deletes only the PipelineRuns that are created by the Pipeline <name>, except for the latest two.
  • The tkn triggertemplate describe output now displays ResourceTemplates in a table format instead of YAML format.
  • Previously the buildah ClusterTask failed when a new user was added to a container. With this fix, the issue has been resolved.

6.4. Release notes for Red Hat OpenShift Pipelines Technology Preview 1.0

6.4.1. New features

Red Hat OpenShift Pipelines Technology Preview (TP) 1.0 is now available on OpenShift Container Platform 4.6. Red Hat OpenShift Pipelines TP 1.0 is updated to support:

  • Tekton Pipelines 0.11.3
  • Tekton tkn CLI 0.9.0
  • Tekton Triggers 0.4.0
  • ClusterTasks based on Tekton Catalog 0.11

In addition to the fixes and stability improvements, here is a highlight of what’s new in OpenShift Pipelines 1.0.

6.4.1.1. Pipelines

  • Support for v1beta1 API Version.
  • Support for an improved LimitRange. Previously, LimitRange was specified exclusively for the TaskRun and the PipelineRun. Now there is no need to explicitly specify the LimitRange. The minimum LimitRange across the namespace is used.
  • Support for sharing data between Tasks using TaskResults and TaskParams.
  • Pipelines can now be configured to not overwrite the HOME environment variable and workingDir of Steps.
  • Similar to Task Steps, sidecars now support script mode.
  • You can now specify a different scheduler name in TaskRun podTemplate.
  • Support for variable substitution using Star Array Notation.
  • Tekton Controller can now be configured to monitor an individual namespace.
  • A new description field is now added to the specification of Pipeline, Task, ClusterTask, Resource, and Condition.
  • Addition of proxy parameters to Git PipelineResources.

6.4.1.2. Pipelines CLI

  • The describe subcommand is now added for the following tkn resources: eventlistener, condition, triggertemplate, clustertask, and triggerbinding.
  • Support added for v1beta1 to the following commands along with backward comptibility for v1alpha1: clustertask, task, pipeline, pipelinerun, and taskrun.
  • The following commands can now list output from all namespaces using the --all-namespaces flag option:

    • tkn task list
    • tkn pipeline list
    • tkn taskrun list
    • tkn pipelinerun list

      The output of these commands is also enhanced to display information without headers using the --no-headers flag option.

  • You can now start a Pipeline using default parameter values by specifying --use-param-defaults flag in the tkn pipelines start command.
  • Support for Workspace is now added to tkn pipeline start and tkn task start commands.
  • A new clustertriggerbinding command is now added with the following subcommands: describe, delete, and list.
  • You can now directly start a pipeline run using a local or remote yaml file.
  • The describe subcommand now displays an enhanced and detailed output. With the addition of new fields, such as description, timeout, param description, and sidecar status, the command output now provides more detailed information about a specific tkn resource.
  • The tkn task log command now displays logs directly if only one task is present in the namespace.

6.4.1.3. Triggers

  • Triggers can now create both v1alpha1 and v1beta1 Pipeline resources.
  • Support for new Common Expression Language (CEL) interceptor function - compareSecret. This function securely compares strings to secrets in CEL expressions.
  • Support for authentication and authorization at the EventListener Trigger level.

6.4.2. Deprecated features

The following items are deprecated in this release:

  • The environment variable $HOME, and variable workingDir in the Steps specification are deprecated and might be changed in a future release. Currently in a Step container, HOME and workingDir are overwritten to /tekton/home and /workspace respectively.

    In a later release, these two fields will not be modified, and will be set to values defined in the container image and Task YAML. For this release, use flags disable-home-env-overwrite and disable-working-directory-overwrite to disable overwriting of the HOME and workingDir variables.

  • The following commands are deprecated and might be removed in the future release:

    • tkn pipeline create
    • tkn task create
  • The -f flag with the tkn resource create command is now deprecated. It might be removed in the future release.
  • The -t flag and the --timeout flag (with seconds format) for the tkn clustertask create command are now deprecated. Only duration timeout format is now supported, for example 1h30s. These deprecated flags might be removed in the future release.

6.4.3. Known issues

  • If you are upgrading from an older version of Red Hat OpenShift Pipelines, you must delete your existing deployments before upgrading to Red Hat OpenShift Pipelines version 1.0. To delete an existing deployment, you must first delete Custom Resources and then uninstall the Red Hat OpenShift Pipelines Operator. For more details, see the uninstalling Red Hat OpenShift Pipelines section.
  • Submitting the same v1alpha1 Tasks more than once results in an error. Use oc replace instead of oc apply when re-submitting a v1alpha1 Task.
  • The buildah ClusterTask does not work when a new user is added to a container.

    When the Operator is installed, the --storage-driver flag for the buildah ClusterTask is not specified, therefore the flag is set to its default value. In some cases, this causes the storage driver to be set incorrectly. When a new user is added, the incorrect storage-driver results in the failure of the buildah ClusterTask with the following error:

    useradd: /etc/passwd.8: lock file already used
    useradd: cannot lock /etc/passwd; try again later.

    As a workaround, manually set the --storage-driver flag value to overlay in the buildah-task.yaml file:

    1. Login to your cluster as a cluster-admin:

      $ oc login -u <login> -p <password> https://openshift.example.com:6443
    2. Use the oc edit command to edit buildah ClusterTask:

      $ oc edit clustertask buildah

      The current version of the buildah clustertask YAML file opens in the editor set by your EDITOR environment variable.

    3. Under the steps field, locate the following command field:

       command: ['buildah', 'bud', '--format=$(params.FORMAT)', '--tls-verify=$(params.TLSVERIFY)', '--layers', '-f', '$(params.DOCKERFILE)', '-t', '$(resources.outputs.image.url)', '$(params.CONTEXT)']
    4. Replace the command field with the following:

       command: ['buildah', '--storage-driver=overlay', 'bud', '--format=$(params.FORMAT)', '--tls-verify=$(params.TLSVERIFY)', '--no-cache', '-f', '$(params.DOCKERFILE)', '-t', '$(params.IMAGE)', '$(params.CONTEXT)']
    5. Save the file and exit.

    Alternatively, you can also modify the buildah ClusterTask YAML file directly on the web console by navigating to PipelinesCluster Tasksbuildah. Select Edit Cluster Task from the Actions menu and replace the command field as shown in the previous procedure.

6.4.4. Fixed issues

  • Previously, the DeploymentConfig Task triggered a new deployment build even when an image build was already in progress. This caused the deployment of the Pipeline to fail. With this fix, the deploy task command is now replaced with the oc rollout status command which waits for the in-progress deployment to finish.
  • Support for APP_NAME parameter is now added in Pipeline templates.
  • Previously, the Pipeline template for Java S2I failed to look up the image in the registry. With this fix, the image is looked up using the existing image PipelineResources instead of the user provided IMAGE_NAME parameter.
  • All the OpenShift Pipelines images are now based on the Red Hat Universal Base Images (UBI).
  • Previously, when the Pipeline was installed in a namespace other than tekton-pipelines, the tkn version command displayed the Pipeline version as unknown. With this fix, the tkn version command now displays the correct Pipeline version in any namespace.
  • The -c flag is no longer supported for the tkn version command.
  • Non-admin users can now list the ClusterTriggerBindings.
  • The EventListener CompareSecret function is now fixed for the CEL Interceptor.
  • The list, describe, and start subcommands for task and clustertask now correctly display the output in case a Task and ClusterTask have the same name.
  • Previously, the OpenShift Pipelines Operator modified the privileged security context constraints (SCCs), which caused an error during cluster upgrade. This error is now fixed.
  • In the tekton-pipelines namespace, the timeouts of all TaskRuns and PipelineRuns are now set to the value of default-timeout-minutes field using the ConfigMap.
  • Previously, the Pipelines section in the web console was not displayed for non-admin users. This issue is now resolved.

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