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Installing Tekton Pipelines

This guide explains how to install Tekton Pipelines. It covers the following topics:

Before you begin

  1. Choose the version of Tekton Pipelines you want to install. You have the following options:

    • Official - install this unless you have a specific reason to go for a different release.
    • Nightly - may contain bugs, install at your own risk. Nightlies live at gcr.io/tekton-nightly.
    • [HEAD] - this is the bleeding edge. It contains unreleased code that may result in unpredictable behavior. To get started, see the development guide instead of this page.

  2. If you don't have an existing Kubernetes cluster, set one up, version 1.15 or later:

    #Example command for creating a cluster on GKE
gcloud container clusters create $CLUSTER_NAME \
  --zone=$CLUSTER_ZONE --cluster-version=1.15.11-gke.5

  3. Grant cluster-admin permissions to the current user:

    kubectl create clusterrolebinding cluster-admin-binding \
--clusterrole=cluster-admin \
--user=$(gcloud config get-value core/account)

    See Role-based access control for more information.

Installing Tekton Pipelines on Kubernetes

To install Tekton Pipelines on a Kubernetes cluster:

  1. Run the following command to install Tekton Pipelines and its dependencies:

    kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/latest/release.yaml

    You can install a specific release using previous/$VERSION_NUMBER. For example:

     kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/previous/v0.2.0/release.yaml

    If your container runtime does not support image-reference:tag@digest (for example, like cri-o used in OpenShift 4.x), use release.notags.yaml instead:

    kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/latest/release.notags.yaml

  2. Monitor the installation using the following command until all components show a Running status:

    kubectl get pods --namespace tekton-pipelines --watch

    Note: Hit CTRL+C to stop monitoring.

Congratulations! You have successfully installed Tekton Pipelines on your Kubernetes cluster. Next, see the following topics:

Installing Tekton Pipelines on OpenShift

To install Tekton Pipelines on OpenShift, you must first apply the anyuid security context constraint to the tekton-pipelines-controller service account. This is required to run the webhook Pod. See Security Context Constraints for more information.

  1. Log on as a user with cluster-admin privileges. The following example uses the default system:admin user:

    # For MiniShift: oc login -u admin:admin
oc login -u system:admin

  2. Set up the namespace (project) and configure the service account:

    oc new-project tekton-pipelines
oc adm policy add-scc-to-user anyuid -z tekton-pipelines-controller

  3. Install Tekton Pipelines:

    oc apply --filename https://storage.googleapis.com/tekton-releases/pipeline/latest/release.notags.yaml

    See the OpenShift CLI documentation for more information on the oc command.

  4. Monitor the installation using the following command until all components show a Running status:

    oc get pods --namespace tekton-pipelines --watch

    Note: Hit CTRL + C to stop monitoring.

Congratulations! You have successfully installed Tekton Pipelines on your OpenShift environment. Next, see the following topics:

If you want to run OpenShift 4.x on your laptop (or desktop), you should take a look at Red Hat CodeReady Containers.

Configuring artifact storage

Tasks in Tekton Pipelines need to ingest inputs from and store outputs to one or more common locations. You can use one of the following solutions to set up resource storage for Tekton Pipelines:

Note: Inputs and output locations for Tasks are defined via PipelineResources.

Either option provides the same functionality to Tekton Pipelines. Choose the option that best suits your business needs. For example:

  • In some environments, creating a persistent volume could be slower than transferring files to/from a cloud storage bucket.
  • If the cluster is running in multiple zones, accessing a persistent volume could be unreliable.

Note: To customize the names of the ConfigMaps for artifact persistence (e.g. to avoid collisions with other services), rename the ConfigMap and update the env value defined controller.yaml.

Configuring a persistent volume

To configure a persistent volume, use a ConfigMap with the name config-artifact-pvc and the following attributes:

  • size: the size of the volume. Default is 5GiB.
  • storageClassName: the storage class of the volume. The possible values depend on the cluster configuration and the underlying infrastructure provider. Default is the default storage class.

Configuring a cloud storage bucket

To configure either an S3 bucket or a GCS bucket, use a ConfigMap with the name config-artifact-bucket and the following attributes:

  • location - the address of the bucket, for example gs://mybucket or s3://mybucket.
  • bucket.service.account.secret.name - the name of the secret containing the credentials for the service account with access to the bucket.
  • bucket.service.account.secret.key - the key in the secret with the required service account JSON file.
  • bucket.service.account.field.name - the name of the environment variable to use when specifying the secret path. Defaults to GOOGLE_APPLICATION_CREDENTIALS. Set to BOTO_CONFIG if using S3 instead of GCS.

Important: Configure your bucket's retention policy to delete all files after your Tasks finish running.

Note: You can only use an S3 bucket located in the us-east-1 region. This is a limitation of gsutil running a boto configuration behind the scenes to access the S3 bucket.

Example configuration for an S3 bucket

Below is an example configuration that uses an S3 bucket:

apiVersion: v1
kind: Secret
metadata:
  name: tekton-storage
  namespace: tekton-pipelines
type: kubernetes.io/opaque
stringData:
  boto-config: |
    [Credentials]
    aws_access_key_id = AWS_ACCESS_KEY_ID
    aws_secret_access_key = AWS_SECRET_ACCESS_KEY
    [s3]
    host = s3.us-east-1.amazonaws.com
    [Boto]
    https_validate_certificates = True
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: config-artifact-bucket
  namespace: tekton-pipelines
data:
  location: s3://mybucket
  bucket.service.account.secret.name: tekton-storage
  bucket.service.account.secret.key: boto-config
  bucket.service.account.field.name: BOTO_CONFIG

Example configuration for a GCS bucket

Below is an example configuration that uses a GCS bucket:

apiVersion: v1
kind: Secret
metadata:
  name: tekton-storage
  namespace: tekton-pipelines
type: kubernetes.io/opaque
stringData:
  gcs-config: |
    {
      "type": "service_account",
      "project_id": "gproject",
      "private_key_id": "some-key-id",
      "private_key": "-----BEGIN PRIVATE KEY-----\nME[...]dF=\n-----END PRIVATE KEY-----\n",
      "client_email": "tekton-storage@gproject.iam.gserviceaccount.com",
      "client_id": "1234567890",
      "auth_uri": "https://accounts.google.com/o/oauth2/auth",
      "token_uri": "https://oauth2.googleapis.com/token",
      "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
      "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/tekton-storage%40gproject.iam.gserviceaccount.com"
    }
---
apiVersion: v1
kind: ConfigMap
metadata:
  name: config-artifact-bucket
  namespace: tekton-pipelines
data:
  location: gs://mybucket
  bucket.service.account.secret.name: tekton-storage
  bucket.service.account.secret.key: gcs-config
  bucket.service.account.field.name: GOOGLE_APPLICATION_CREDENTIALS

Customizing basic execution parameters

You can specify your own values that replace the default service account (ServiceAccount), timeout (Timeout), and Pod template (PodTemplate) values used by Tekton Pipelines in TaskRun and PipelineRun definitions. To do so, modify the ConfigMap config-defaults with your desired values.

The example below customizes the following:

  • the default service account from default to tekton.
  • the default timeout from 60 minutes to 20 minutes.
  • the default app.kubernetes.io/managed-by label is applied to all Pods created to execute TaskRuns.
  • the default Pod template to include a node selector to select the node where the Pod will be scheduled by default. For more information, see PodTemplate in TaskRuns or PodTemplate in PipelineRuns.
apiVersion: v1
kind: ConfigMap
metadata:
  name: config-defaults
data:
  default-service-account: "tekton"
  default-timeout-minutes: "20"
  default-pod-template: |
    nodeSelector:
      kops.k8s.io/instancegroup: build-instance-group
  default-managed-by-label-value: "my-tekton-installation"

Note: The _example key in the provided config-defaults.yaml file lists the keys you can customize along with their default values.

Customizing the Pipelines Controller behavior

To customize the behavior of the Pipelines Controller, modify the ConfigMap feature-flags as follows:

  • disable-home-env-overwrite - set this flag to true to prevent Tekton from overriding the $HOME environment variable for the containers executing your Steps. The default is false. For more information, see the associated issue.

  • disable-working-directory-overwrite - set this flag to true to prevent Tekton from overriding the working directory for the containers executing your Steps. The default value is false, which causes Tekton to override the working directory for each Step that does not have its working directory explicitly set with /workspace. For more information, see the associated issue.

For example:

apiVersion: v1
kind: ConfigMap
metadata:
  name: feature-flags
data:
  disable-home-env-overwrite: "true" # Tekton will not override the $HOME variable for individual Steps.
  disable-working-directory-overwrite: "true" # Tekton will not override the working directory for individual Steps.

Creating a custom release of Tekton Pipelines

You can create a custom release of Tekton Pipelines by following and customizing the steps in Creating an official release. For example, you might want to customize the container images built and used by Tekton Pipelines.

Next steps

To get started with Tekton Pipelines, see the Tekton Pipelines Tutorial and take a look at our examples.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License.