This guide explains how to install Tekton Pipelines. It covers the following topics:
- Before you begin
- Installing Tekton Pipelines on Kubernetes
- Installing Tekton Pipelines on OpenShift
- Configuring artifact storage
- Customizing basic execution parameters
- Creating a custom release of Tekton Pipelines
- Next steps
-
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.
-
If you don't have an existing Kubernetes cluster, set one up, version 1.16 or later:
#Example command for creating a cluster on GKE gcloud container clusters create $CLUSTER_NAME \ --zone=$CLUSTER_ZONE --cluster-version=1.16.9-gke.6
-
Grant
cluster-admin
permissions to the current user:kubectl create clusterrolebinding cluster-admin-binding \ --clusterrole=cluster-admin \ --user=$(gcloud config get-value core/account)
See Role-based access control for more information.
To install Tekton Pipelines on a Kubernetes cluster:
-
Run the following command to install Tekton Pipelines and its dependencies:
kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/latest/release.yaml
You can install a specific release using
previous/$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, likecri-o
used in OpenShift 4.x), userelease.notags.yaml
instead:kubectl apply --filename https://storage.googleapis.com/tekton-releases/pipeline/latest/release.notags.yaml
-
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:
- Configuring artifact storage to set up artifact storage for Tekton Pipelines.
- Customizing basic execution parameters if you need to customize your service account, timeout, or Pod template values.
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.
-
Log on as a user with
cluster-admin
privileges. The following example uses the defaultsystem:admin
user:# For MiniShift: oc login -u admin:admin oc login -u system:admin
-
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
-
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. -
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:
- Configuring artifact storage to set up artifact storage for Tekton Pipelines.
- Customizing basic execution parameters if you need to customize your service account, timeout, or Pod template values.
If you want to run OpenShift 4.x on your laptop (or desktop), you should take a look at Red Hat CodeReady Containers.
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.
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.
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 examplegs://mybucket
ors3://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 toGOOGLE_APPLICATION_CREDENTIALS
. Set toBOTO_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.
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
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": "[email protected]",
"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
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
generared.
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
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
totekton
. - the default timeout from 60 minutes to 20 minutes.
- the default
app.kubernetes.io/managed-by
label is applied to all Pods created to executeTaskRuns
. - 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
inTaskRuns
orPodTemplate
inPipelineRuns
.
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.
To customize the behavior of the Pipelines Controller, modify the ConfigMap feature-flags
as follows:
-
disable-affinity-assistant
- set this flag totrue
to disable the Affinity Assistant that is used to provide Node Affinity forTaskRun
pods that share workspace volume. The Affinity Assistant is incompatible with other affinity rules configured forTaskRun
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 specifiedtopologyKey
label, it can lead to unintended behavior. -
disable-home-env-overwrite
- set this flag totrue
to prevent Tekton from overriding the$HOME
environment variable for the containers executing yourSteps
. The default isfalse
. For more information, see the associated issue. -
disable-working-directory-overwrite
- set this flag totrue
to prevent Tekton from overriding the working directory for the containers executing yourSteps
. The default value isfalse
, which causes Tekton to override the working directory for eachStep
that does not have its working directory explicitly set with/workspace
. 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 thetekton.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.
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.
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.
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.