Installing Tekton Pipelines

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

Before you begin

  1. You must have a Kubernetes cluster running version 1.18 or later.

If you don’t already have a cluster, you can create one for testing with kind. Install kind and create a cluster by running kind create cluster. This will create a cluster running locally, with RBAC enabled and your user granted the cluster-admin role.

  1. If you want to support high availability usecases, install a Metrics Server on your cluster.

  2. 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.
  3. Grant cluster-admin permissions to the current user.

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

Or, for the nightly release, use:

   kubectl apply --filename https://storage.googleapis.com/tekton-releases-nightly/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
  1. 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
  1. 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
   oc adm policy add-scc-to-user anyuid -z tekton-pipelines-webhook
  1. 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.

  1. 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 PipelineResource storage

PipelineResources are one of the ways that Tekton passes data between Tasks. If you intend to use PipelineResources in your Pipelines then you’ll need to configure a storage location for that data to be put so that it can be shared between Tasks in the Pipeline.

Note: Pipeline Resources are in alpha and are currently undergoing considerable redesign. Therefore this storage configuration is possibly going to change in future. Writing Tasks and Pipelines today that rely on this feature may mean you’ll need to rewrite those Tasks and Pipelines when the redesign is complete. See the explanation for the redesign in the PipelineResources doc and issue 1673 to follow along with the redesign work.

The storage options available for sharing PipelineResources between Tasks in a Pipeline are:

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

Configuring CloudEvents notifications

When configured so, Tekton can generate CloudEvents for TaskRun and PipelineRun lifecycle events. The only configuration parameter is the URL of the sink. When not set, no notification is generated.

apiVersion: v1
kind: ConfigMap
metadata:
  name: config-defaults
  namespace: tekton-pipelines
  labels:
    app.kubernetes.io/instance: default
    app.kubernetes.io/part-of: tekton-pipelines
data:
  default-cloud-events-sink: https://my-sink-url

Configuring self-signed cert for private registry

The SSL_CERT_DIR is set to /etc/ssl/certs as the default cert directory. If you are using a self-signed cert for private registry and the cert file is not under the default cert directory, configure your registry cert in the config-registry-cert ConfigMap with the key cert.

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. A list of supported fields is available here. For more information, see PodTemplate in TaskRuns or PodTemplate in PipelineRuns.
  • the default Workspace configuration can be set for any Workspaces that a Task declares but that a TaskRun does not explicitly provide
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"
  default-task-run-workspace-binding: |
    emptyDir: {}

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-affinity-assistant - set this flag to true to disable the Affinity Assistant that is used to provide Node Affinity for TaskRun pods that share workspace volume. The Affinity Assistant is incompatible with other affinity rules configured for TaskRun pods.

Note: Affinity Assistant use Inter-pod affinity and anti-affinity that require substantial amount of processing which can slow down scheduling in large clusters significantly. We do not recommend using them in clusters larger than several hundred nodes

Note: Pod anti-affinity requires nodes to be consistently labelled, in other words every node in the cluster must have an appropriate label matching topologyKey. If some or all nodes are missing the specified topologyKey label, it can lead to unintended behavior.

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

  • disable-working-directory-overwrite - set this flag to false to allow Tekton to override the working directory for the containers executing your Steps. The default value is true. For more information, see the associated issue.

  • running-in-environment-with-injected-sidecars: set this flag to "true" to allow the Tekton controller to set the tekton.dev/ready annotation at pod creation time for TaskRuns with no Sidecars specified. Enabling this option should decrease the time it takes for a TaskRun to start running. However, for clusters that use injected sidecars e.g. istio enabling this option can lead to unexpected behavior.

  • require-git-ssh-secret-known-hosts: set this flag to "true" to require that Git SSH Secrets include a known_hosts field. This ensures that a git remote server’s key is validated before data is accepted from it when authenticating over SSH. Secrets that don’t include a known_hosts will result in the TaskRun failing validation and not running.

  • enable-tekton-oci-bundles: set this flag to "true" to enable the tekton OCI bundle usage (see the tekton bundle contract). Enabling this option allows the use of bundle field in taskRef and pipelineRef for Pipeline, PipelineRun and TaskRun. By default, this option is disabled ("false"), which means it is disallowed to use the bundle field.

  • disable-creds-init - set this flag to "true" to disable Tekton’s built-in credential initialization and use Workspaces to mount credentials from Secrets instead. The default is false. For more information, see the associated issue.

  • enable-custom-tasks: set this flag to "true" to enable the use of custom tasks in pipelines.

  • enable-api-fields: set this flag to “stable” to allow only the most stable features to be used. Set it to “alpha” to allow alpha features to be used.

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.
  enable-api-fields: "alpha" # Allow alpha fields to be used in Tasks and Pipelines.

Alpha Features

Alpha features are still in development and their syntax is subject to change. To enable these, set the enable-api-fields feature flag to "alpha" in the feature-flags ConfigMap alongside your Tekton Pipelines deployment.

Features currently in “alpha” are:

Configuring High Availability

If you want to run Tekton Pipelines in a way so that webhooks are resiliant against failures and support high concurrency scenarios, you need to run a Metrics Server in your Kubernetes cluster. This is required by the Horizontal Pod Autoscalers to compute replica count.

See HA Support for Tekton Pipeline Controllers for instructions on configuring High Availability in the Tekton Pipelines Controller.

The default configuration is defined in webhook-hpa.yaml which can be customized to better fit specific usecases.

Configuring tekton pipeline controller performance

Out-of-the-box, Tekton Pipelines Controller is configured for relatively small-scale deployments but there have several options for configuring Pipelines’ performance are available. See the Performance Configuration document which describes how to change the default ThreadsPerController, QPS and Burst settings to meet your requirements.

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.


Last modified January 1, 0001