Skip to content

Latest commit

 

History

History
315 lines (234 loc) · 11.6 KB

DEVELOPMENT.md

File metadata and controls

315 lines (234 loc) · 11.6 KB
Raw

Developing

Getting started

  1. Ramp up on kubernetes and CRDs
  2. Create a GitHub account
  3. Setup GitHub access via SSH
  4. Create and checkout a repo fork
  5. Set up your shell environment
  6. Install requirements
  7. Set up a Kubernetes cluster
  8. Configure kubectl to use your cluster
  9. Set up a docker repository you can push to

Then you can iterate (including running the controllers with ko).

Ramp up

Welcome to the project!! You may find these resources helpful to ramp up on some of the technology this project is built on. This project extends Kubernetes (aka k8s) with Custom Resource Definitions (CRDs). To find out more:

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

Checkout your fork

The Go tools require that you clone the repository to the src/github.com/tektoncd/pipeline directory in your GOPATH.

To check out this repository:

  1. Create your own fork of this repo
  2. Clone it to your machine:
mkdir -p ${GOPATH}/src/github.com/tektoncd
cd ${GOPATH}/src/github.com/tektoncd
git clone [email protected]:${YOUR_GITHUB_USERNAME}/pipeline.git
cd pipeline
git remote add upstream [email protected]:tektoncd/pipeline.git
git remote set-url --push upstream no_push

Adding the upstream remote sets you up nicely for regularly syncing your fork.

Requirements

You must install these tools:

  1. go: The language Tekton Pipelines is built in
  2. git: For source control
  3. ko: For development. ko version v0.5.1 or higher is required for pipeline to work correctly.
  4. kubectl: For interacting with your kube cluster

Your [$GOPATH] setting is critical for ko apply to function properly: a successful run will typically involve building pushing images instead of only configuring Kubernetes resources.

Kubernetes cluster

The recommended configuration is:

  • Kubernetes version 1.16 or later
  • 4 vCPU nodes (n1-standard-4)
  • Node autoscaling, up to 3 nodes
  • API scopes for cloud-platform

To setup a cluster using MiniKube:

  • Follow instructions for your platform to Install Minikube and start a session as follows:
minikube start eval $(minikube docker-env)

To setup a cluster with Docker Desktop:

Docker Desktop versions come integrated with an edge version of Kubernetes that has been proven to work for both developing and running Pipelines. To find out what Kubernetes a specific version of Docker Desktop includes, please refer to the release notes for your platform here: https://docs.docker.com/.

To enable the Kubernetes that comes with Docker Desktop:

  1. From the Docker Desktop dropdown menu, open the preferences... interface.

  2. Under the Resources tab ensure that in the ADVANCED menuitem you have at allocated at least 4 CPUs, 8.0 GiB Memory, and 1.0 GiB Swap.

  3. Under the Kubernetes tab, check the Enable Kubernetes box.

    • Note: the Kubernetes version Docker Desktop will use is displayed at the top of the window.

  4. Click the Apply and Restart button to save the preferences.

  5. Switch the proper kubectl config context:

    kubectl config get-contexts # You should see docker-for-desktop in the previous command output
kubectl config use-context docker-for-desktop
    • Note: Docker Desktop menu provides a Kubernetes menuitem that allows you to select between contexts which is equivalent to the kubectl command.

To setup a cluster with GKE:

  1. Install required tools and setup GCP project (You may find it useful to save the ID of the project in an environment variable (e.g. PROJECT_ID).

  2. Create a GKE cluster (with --cluster-version=latest but you can use any version 1.16 or later):

    export PROJECT_ID=my-gcp-project
export CLUSTER_NAME=mycoolcluster

gcloud container clusters create $CLUSTER_NAME \
 --enable-autoscaling \
 --min-nodes=1 \
 --max-nodes=3 \
 --scopes=cloud-platform \
 --enable-basic-auth \
 --no-issue-client-certificate \
 --project=$PROJECT_ID \
 --region=us-central1 \
 --machine-type=n1-standard-4 \
 --image-type=cos \
 --num-nodes=1 \
 --cluster-version=1.16

    Note that the --scopes argument to gcloud container cluster create 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 your --scopes arg.

  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)

Environment Setup

To run your controllers with ko you'll need to set these environment variables (we recommend adding them to your .bashrc):

  1. GOPATH: If you don't have one, simply pick a directory and add export GOPATH=...
  2. $GOPATH/bin on PATH: This is so that tooling installed via go get will work properly.
  3. KO_DOCKER_REPO: The docker repository to which developer images should be pushed (e.g. gcr.io/[gcloud-project]). You can also run a local registry and set KO_DOCKER_REPO to reference the registry (e.g. at localhost:5000/mypipelineimages).

.bashrc example:

export GOPATH="$HOME/go"
export PATH="${PATH}:${GOPATH}/bin"
export KO_DOCKER_REPO='gcr.io/my-gcloud-project-name'

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

The user you are using to interact with your k8s cluster must be a cluster admin to create role bindings:

# 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}"

Install in custom namespace

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

Iterating

While iterating on the project, you may need to:

  1. Install/Run everything
  2. Verify it's working by looking at the logs
  3. Update your (external) dependencies with: ./hack/update-deps.sh.
  4. Update your type definitions with: ./hack/update-codegen.sh.
  5. Add new CRD types
  6. Add and run tests

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

Install Pipeline

You can stand up a version of this controller on-cluster (to your kubectl config current-context):

ko apply -f config/

Redeploy controller

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

ko apply -f config/controller.yaml

Tear it down

You can clean up everything with:

ko delete -f config/

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 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.