This guide is directed at Prow developers and maintainers who want to build/test individual components or deploy changes to an existing Prow cluster. getting_started_deploy.md
is a better reference for deploying a new Prow cluster.
You can build, test, and deploy Prow’s binaries, container images, and cluster resources using bazel
.
Build with:
bazel build //prow/...
Test with:
bazel test --features=race //prow/...
Individual packages and components can be built and tested like:
bazel build //prow/cmd/hook
bazel test //prow/plugins/lgtm:go_default_test
If you are making changes to a Prow plugin you can test the new behavior by sending fake webhooks to hook
with phony
.
Any modifications to Go code will require redeploying the affected binaries. Assuming your prow components have multiple replicas, this will result in no downtime.
Update your deployment (optionally build/pushing the image) to a new image with:
# export PROW_REPO_OVERRIDE=gcr.io/k8s-prow # optionally change k8s-prow to your project
push.sh # Build and push the current repo state.
bump.sh --list # Choose a recent published version
bump.sh v20181002-deadbeef # Use a specific version
Once your deployment files are updated, please update these resources on your cluster:
# Set the kubectl context you want to use
export PROW_CLUSTER_OVERRIDE=my-k8s-cluster-context # or whatever the correct value is
export BUILD_CLUSTER_OVERRIDE=my-k8s-job-cluster-context # or whatever the correct value is
# Generally just do
bazel run //config/prow/cluster:production.apply # deploy everything
# In case of an emergency hook update
bazel run //config/prow/cluster:hook.apply # just update hook
# This is equivalent to doing the following with kubectl directly:
kubectl config use-context my-k8s-cluster-context
kubectl apply -f config/prow/cluster/*.yaml
kubectl apply -f config/prow/cluster/hook_deployment.yaml
The best way to go about testing a new ProwJob depends on the job itself. If the job can be run locally that is typically the best way to initially test the job because local debugging is easier and safer than debugging in CI. See Running a ProwJob Locally below.
Actually running the job on Prow by merging the job config is the next step.
Typically, new presubmit jobs are configured to skip_report
ing to GitHub and
may not be configured to automatically run on every PR with always_run: true
.
Once the job is stable these values can be changed to make the job run everywhere
and become visible to users by posting results to GitHub (if desired). Changes
to existing jobs can be trialed on canary jobs.
ProwJobs can also be manually triggered by generating a YAML ProwJob CRD with mkpj and deploying that directly to the Prow cluster, however this pattern is generally not recommended. It requires the use of direct prod cluster access, allows ProwJobs to run in prod without passing presubmit validation, and can result in malformed ProwJobs CRDs that can jam some of Prow's core service components. See How to manually run a given job on Prow below if you need to do this.
pj-on-kind.sh is a bash script that runs ProwJobs locally as pods in a Kind cluster. The script does the following:
- Installs mkpj, mkpod, and Kind if they are not found in the path. A Kind
cluster named
mkpod
is created if one does not already exist. - Uses mkpj to generate a YAML ProwJob CRD given job name, config, and git refs (if applicable).
- Uses mkpod to generate a YAML Pod resource from the ProwJob CRD. This Pod will
be decorated with the pod utilities if needed and will exactly match what would be
applied in prod with two exceptions:
- The job logs, metadata, and artifacts will be copied to disk rather than
uploaded to GCS. By default these files are copied to
/mnt/disks/prowjob-out/<job-name>/<build-id>/
on the host machine. - Any volume mounts may be substituted for
emptyDir
orhostPath
volumes at the interactive prompt to replace dependencies that are only available in prod. NOTE! In order forhostPath
volume sources to reach the host and not just the Kind "node" container, use paths under/mnt/disks/kind-node
or set$NODE_DIR
before the mkpod cluster is created.
- The job logs, metadata, and artifacts will be copied to disk rather than
uploaded to GCS. By default these files are copied to
- Applies the Pod to the Kind cluster and starts watching it (interrupt whenever, this is for convenience). At this point the Pod will start running if configured correctly.
Once the Pod has been applied to the cluster you can wait for it to complete and output
results to the output directory, or you can interact with it using kubectl by first
running export KUBECONFIG="$(kind get kubeconfig-path --name=mkpod)"
.
Requirements: Go, Docker, and kubectl must be installed before using this script.
The ProwJob must use agent: kubernetes
(the default, runs ProwJobs as Pods).
Each Prow instance can supply a preconfigured variant of pj-on-kind.sh that properly
defaults the config file locations. Example
for prow.istio.io.
To test ProwJobs for the prow.k8s.io instance use config/pj-on-kind.sh
.
This command runs the ProwJob pull-test-infra-yamllint
locally on Kind.
./pj-on-kind.sh pull-test-infra-yamllint
You may also need to set the CONFIG_PATH
and JOB_CONFIG_PATH
environmental variables:
CONFIG_PATH=(realpath ../config/prow/config.yaml) JOB_CONFIG_PATH=(realpath ../config/jobs/kubernetes/test-infra/test-infra-presubmits.yaml) ...
This tool was written in bash so that it can be easily adjusted when debugging. In particular it should be easy to modify the main function to:
- Add additional K8s resources to the cluster before running the Pod such as secrets, configmaps, or volumes.
- Skip applying the pod.yaml to the Kind cluster to inspect it, modify it, or apply it to
a real cluster instead of the
mkpod
Kind cluster. (Same for pj.yaml)
To point kubectl
to the Kind cluster you will need to export the KUBECONFIG
Env. The command to point this to the correct config is echoed in the pj-on-kind.sh logging. It will have the form:
export KUBECONFIG='/<path to user dir>/.kube/kind-config-mkpod'
After pointing to the correct master you will be able to drop into the container using kubectl exec -it <pod name> <bash/sh/etc>
. **This pod will only last the lifecycle of the job, if you need more time to debug you might add a sleep
within the job execution.
Phaino lets you interactively mock and run the job locally on your workstation in a docker container. Detailed instructions can be found in Phaino's Readme.
Note: Test containers designed for decorated jobs (configured with decorate: true
)
may behave incorrectly or fail entirely without the environment the pod utilities
provide. Similarly jobs that mount volumes or use extra_refs
likely won't work
properly.
These jobs are best run locally as decorated pods inside a Kind cluster Using pj-on-kind.sh.
If the normal job triggering mechanisms (/test foo
comments, PR changes, PR
merges, cron schedule) are not sufficient for your testing you can use mkpj
to
manually trigger new ProwJob runs.
To manually trigger any ProwJob, run the following, specifying JOB_NAME
:
For K8S Prow, you can trigger a job by running
bazel run //config:mkpj -- --job=JOB_NAME
For your own prow instance, you can either define your own bazel rule, or just go run mkpj like:
go run k8s.io/test-infra/prow/cmd/mkpj --job=JOB_NAME --config-path=path/to/config.yaml
Alternatively, if you have jobs defined in a separate job-config
, you can
specify the config by adding the flag --job-config-path=path/to/job/config.yaml
.
This will print the ProwJob YAML to stdout. You may pipe it into kubectl
.
Depending on the job, you will need to specify more information such as PR
number.
NOTE: It is dangerous to create ProwJobs from handcrafted YAML. Please use mkpj
to generate ProwJob YAML.