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Developing

Getting started

First, you may want to Ramp up on Kubernetes and Custom Resource Definitions (CRDs) as Tekton implements several Kubernetes resource controllers configured by Tekton CRDs. Then follow these steps to start developing and contributing project code:

  1. Setting up a development environment
    1. Setup a GitHub account accessible via SSH
    2. Install tools
    3. Configure environment
    4. Setup a fork of the tektoncd/pipeline project repository
    5. Configure a container image registry
  2. Building and deploying Tekton source code from a local clone.
    1. Setup a Kubernetes cluster
    2. Configure kubectl to use your cluster
    3. Set up a docker repository 'ko' can push images to
  3. Developing and testing Tekton pipelines
    1. Learn how to iterate on code changes
    2. Managing Tekton Objects using ko in Kubernetes
    3. Accessing logs
    4. Adding new CRD types

Ramp up

Welcome to the project! 👏👏👏 You may find these resources helpful to "ramp up" on some of the technologies this project builds and runs on. This project extends Kubernetes (aka k8s) with Custom Resource Definitions (CRDs). To find out more, read:

At this point, you may find it useful to return to these Tekton Pipeline docs:


Setting up a development environment

Setup a GitHub account accessible via SSH

GitHub is used for project Source Code Management (SCM) using the SSH protocol for authentication.

  1. Create a GitHub account if you do not already have one.
  2. Setup GitHub access via SSH

Install tools

You must install these tools:

  1. git: For source control

  2. go: The language Tekton Pipelines is built in.

    Note Golang version v1.15 or higher is recommended.

  3. ko: The Tekton project uses ko to simplify the building of its container images from go source, push these images to the configured image repository and deploy these images into Kubernetes clusters.

    Note ko version v0.5.1 or higher is required for pipeline to work correctly.

  4. kubectl: For interacting with your Kubernetes cluster

    ⚠️ The user interacting with your K8s cluster must be a cluster admin to create role bindings.

    Google Cloud Platform (GCP) example:

    # Using gcloud to get your current user
    USER=$(gcloud config get-value core/account)
    # Make that user a cluster admin
    kubectl create clusterrolebinding cluster-admin-binding \
    --clusterrole=cluster-admin \
    --user="${USER}"
  5. bash v4 or higher: For scripts used to generate code and update dependencies. On MacOS the default bash is too old, you can use Homebrew to install a later version.

Configure environment

To build, deploy and run your Tekton Objects with ko, you'll need to set these environment variables:

  1. GOROOT: Set GOROOT to the location of the Go installation you want ko to use for builds.

    Note: You may need to set GOROOT if you installed Go tools to a non-default location or have multiple Go versions installed.

    If it is not set, ko infers the location by effectively using go env GOROOT.

  2. KO_DOCKER_REPO: The docker repository to which developer images should be pushed. For example:

    • Using Google Container Registry (GCR):

      # format: `gcr.io/${GCP-PROJECT-NAME}`
      export KO_DOCKER_REPO='gcr.io/my-gcloud-project-name'
    • Using Docker Desktop (Docker Hub):

      # format: 'docker.io/${DOCKER_HUB_USERNAME}'
      export KO_DOCKER_REPO='docker.io/my-dockerhub-username'
    • You can also host your own Docker Registry server and reference it:

      # format: ${localhost:port}/{}
      export KO_DOCKER_REPO=`localhost:5000/mypipelineimages`
  3. Optionally, add $HOME/go/bin to your system PATH so that any tooling installed via go get will work properly. For example:

    export PATH="${PATH}:$HOME/go/bin"

Note: It is recommended to add these environment variables to your shell's configuration files (e.g., ~/.bash_profile or ~/.bashrc).

Setup a fork

The Tekton project requires that you develop (commit) code changes to branches that belong to a fork of the tektoncd/pipeline repository in your GitHub account before submitting them as Pull Requests (PRs) to the actual project repository.

  1. Create a fork of the tektoncd/pipeline repository in your GitHub account.

  2. Create a clone of your fork on your local machine:

    git clone [email protected]:${YOUR_GITHUB_USERNAME}/pipeline.git

    Note: Tekton uses Go Modules (i.e., go mod) for package management so you may clone the repository to a location of your choosing.

  3. Configure git remote repositories

    Adding tektoncd/pipelines as the upstream and your fork as the origin remote repositories to your .git/config sets you up nicely for regularly syncing your fork and submitting pull requests.

    1. Change into the project directory

      cd pipeline
    2. Configure Tekton as the upstream repository

      git remote add upstream [email protected]:tektoncd/pipeline.git
      
      # Optional: Prevent accidental pushing of commits by changing the upstream URL to `no_push`
      git remote set-url --push upstream no_push
    3. Configure your fork as the origin repository

      git remote add origin [email protected]:${YOUR_GITHUB_USERNAME}/pipeline.git

Configure Container Registry

Depending on your chosen container registry that you set in the KO_DOCKER_REPO environment variable, you may need to additionally configure access control to allow ko to authenticate to it.

Using Docker Desktop (Docker Hub)

Docker Desktop provides seamless integration with both a local (default) image registry as well as Docker Hub remote registries. To use Docker Hub registries with ko, all you need do is to configure Docker Desktop with your Docker ID and password in its dashboard.

Using Google Container Registry (GCR)

If using GCR with ko, make sure to configure authentication for your KO_DOCKER_REPO if required. To be able to push images to gcr.io/<project>, you need to run this once:

gcloud auth configure-docker

To be able to pull images from gcr.io/<project>, please follow the instructions here to configure IAM policies for the services that will pull iamges from your GCR.

If you choose to run GKE and GCR in the same GCP project, please follow the example GKE setup and make sure to add storage-full to the --scopes args in the example to give the GKE default service account full access to your GCR. Alternatively, you can grant the GKE default service account read access to your GCR by running:

gcloud projects add-iam-policy-binding <project-number> \
--member='serviceAccount:<project-number>[email protected]' \
--role='roles/storage.objectViewer'

For more information about GCP Compute Engine default service accounts, please check here

After configuring IAM policy of your GCR, the example GKE setup in this guide now has permissions to push and pull images from your GCR. If you choose to use a different setup with fewer default permissions, or your GKE cluster that will run Tekton is in a different project than your GCR registry, you will need to provide the Tekton pipelines controller and webhook service accounts with GCR credentials. See documentation on using GCR with GKE for more information. To do this, create a secret for your docker credentials and reference this secret from the controller and webhook service accounts, as follows.

  1. Create a secret, for example:

    kubectl create secret generic ${SECRET_NAME} \
    --from-file=.dockerconfigjson=<path/to/.docker/config.json> \
    --type=kubernetes.io/dockerconfigjson
    --namespace=tekton-pipelines

    See Configuring authentication for Docker for more detailed information on creating secrets containing registry credentials.

  2. Update the tekton-pipelines-controller and tekton-pipelines-webhook service accounts to reference the newly created secret by modifying the definitions of these service accounts as shown below.

    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: tekton-pipelines-controller
      namespace: tekton-pipelines
      labels:
        app.kubernetes.io/component: controller
        app.kubernetes.io/instance: default
        app.kubernetes.io/part-of: tekton-pipelines
    imagePullSecrets:
    - name: ${SECRET_NAME}
    ---
    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: tekton-pipelines-webhook
      namespace: tekton-pipelines
      labels:
        app.kubernetes.io/component: webhook
        app.kubernetes.io/instance: default
        app.kubernetes.io/part-of: tekton-pipelines
    imagePullSecrets:
    - name: ${SECRET_NAME}

Building and deploying

Setup a Kubernetes cluster

The recommended minimum development configuration is:

  • Kubernetes version 1.22 or later
  • 4 (virtual) CPU nodes
    • 8 GB of (actual or virtualized) platform memory
  • Node autoscaling, up to 3 nodes

Using KinD

KinD is a great tool for working with Kubernetes clusters locally. It is particularly useful to quickly test code against different cluster configurations.

  1. Install required tools (note: may require a newer version of Go).

  2. Install Docker.

  3. Create cluster:

    $ kind create cluster
  4. Configure ko:

    $ export KO_DOCKER_REPO="kind.local"
    $ export KIND_CLUSTER_NAME="kind"  # only needed if you used a custom name in the previous step

optional: As a convenience, the Tekton plumbing project provides a script named 'tekton_in_kind.sh' that leverages kind to create a cluster and install Tekton Pipeline, Tekton Triggers and Tekton Dashboard components into it.

Using MiniKube

Using Docker Desktop

Using GKE

  1. Set up a GCP Project and enable the GKE API. You may find it useful to save the ID of the project in an environment variable (e.g. PROJECT_ID).
  1. Create a GKE cluster (with --cluster-version=latest but you can use any version 1.18 or later):

    export PROJECT_ID=my-gcp-project
    export CLUSTER_NAME=mycoolcluster
    
    gcloud container clusters create $CLUSTER_NAME \
     --enable-autoscaling \
     --min-nodes=1 \
     --max-nodes=3 \
     --scopes=cloud-platform \
     --no-issue-client-certificate \
     --project=$PROJECT_ID \
     --region=us-central1 \
     --machine-type=e2-standard-4 \
     --num-nodes=1 \
     --cluster-version=1.22

    Note: The recommended GCE machine type is 'e2-standard-4'.

    Note: The '--scopes' argument on the 'gcloud container cluster create' command controls what GCP resources the cluster's default service account has access to; for example, to give the default service account full access to your GCR registry, you can add 'storage-full' to the --scopes arg. See Authenticating to GCP for more details.

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

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

Developing and testing

Iterating on code changes

While iterating on code changes to the project, you may need to:

  1. Manage Tekton objects
  2. Verify installation and make sure there are no errors by accessing the logs
  3. Use various development scripts, as needed, in the 'hack' directory, For example:
    • Update your (external) dependencies with: ./hack/update-deps.sh
    • Update your type definitions with: ./hack/update-codegen.sh
    • Update your OpenAPI specs with: ./hack/update-openapigen.sh
  4. Update or add new CRD types as needed
  5. Update, add and run tests

To make changes to these CRDs, you will probably interact with:


Managing Tekton Objects using ko

The ko command is the preferred method to manage (i.e., create, modify or delete) Tekton Objects in Kubernetes from your local fork of the project. Some common operations include:

Install Pipeline

You can stand up a version of Tekton using your local clone's code to the currently configured K8s context (i.e., kubectl config current-context):

ko apply -R -f config/

Verify installation

You can verify your development installation using ko was successful by checking to see if the Tekton pipeline pods are running in Kubernetes:

kubectl get pods -n tekton-pipelines

Delete Pipeline

You can clean up everything with:

# If you should not delete the namespace of a pipeline component
ko delete -f config/

# If you also can delete the namespace of a pipeline component
ko delete -R -f config/

Note: If you use a pipeline component in the same namespace as other components such as dashboard or triggers, executing ko delete -R -f config/ deletes these other components too.

Redeploy controller

As you make changes to the code, you can redeploy your controller with:

ko apply -f config/controller.yaml

Installing into custom namespaces

When managing different development branches of code (with changed Tekton objects and controllers) in the same K8s instance, it may be helpful to install them into a custom (non-default) namespace. The ability to map a code branch to a corresponding namespace may make it easier to identify and manage the objects as a group as well as isolate log output.

To install into a different namespace you can use this script:

#!/usr/bin/env bash
set -e

# Set your target namespace here
TARGET_NAMESPACE=new-target-namespace

ko resolve -R -f config | sed -e '/kind: Namespace/!b;n;n;s/:.*/: '"${TARGET_NAMESPACE}"'/' | \
    sed "s/namespace: tekton-pipelines$/namespace: ${TARGET_NAMESPACE}/" | \
    kubectl apply -R -f-
kubectl set env deployments --all SYSTEM_NAMESPACE=${TARGET_NAMESPACE} -n ${TARGET_NAMESPACE}

This script will cause ko to:

  • Change (resolve) all namespace values in K8s configuration files within the config/ subdirectory to be updated to a name of your choosing.
  • Builds and push images with the new namespace to your container registry and
  • Update all Tekton Objects in K8s using these images

It will also update the default system namespace used for K8s deployments to the new value for all subsequent kubectl commands.


Accessing logs

To look at the controller logs, run:

kubectl -n tekton-pipelines logs $(kubectl -n tekton-pipelines get pods -l app=tekton-pipelines-controller -o name)

To look at the webhook logs, run:

kubectl -n tekton-pipelines logs $(kubectl -n tekton-pipelines get pods -l app=tekton-pipelines-webhook -o name)

To look at the logs for individual TaskRuns or PipelineRuns, see docs on accessing logs.

Adding new CRD types

If you need to add a new CRD type, you will need to add:

  1. A yaml definition in config/
  2. Add the type to the cluster roles in:
  3. Add go structs for the types in pkg/apis/pipeline/v1alpha1 e.g condition_types.go This should implement the Defaultable and Validatable interfaces as they are needed for the webhook in the next step.
  4. Register it with the webhook
  5. Add the new type to the list of known types

See the API compatibility policy.