• Prerequisites
• Set up your environment
• Create and connect to a cluster
• Install and configure the Kubernetes Operator
• Verify your configuration

Tutorial: Configure GitLab Runner to use the Google Kubernetes Engine

This tutorial describes how to configure GitLab Runner to use the Google Kubernetes Engine (GKE) to run jobs.

In this tutorial, you configure GitLab Runner to run jobs in the following GKE cluster modes:

• Autopilot
• Standard

To configure GitLab Runner to use the GKE:

1. Set up your environment.
2. Create and connect to a cluster.
3. Install and configure the Kubernetes Operator.
4. Optional. Verify that the configuration was successful.

Prerequisites

Before you can configure GitLab Runner to use the GKE you must:

• Have a project where you have the Maintainer or Owner role. If you don’t have a project, you can create it.
• Obtain the project runner registration token.
• Install GitLab Runner.

Set up your environment

Install the tools to configure and use GitLab Runner in the GKE.

1. Install and configure Google Cloud CLI. You use Google Cloud CLI to connect to the cluster.
2. Install and configure kubectl. You use kubectl to communicate with the remote cluster from your local environment.

Create and connect to a cluster

This step describes how to create a cluster and connect to it. After you connect to the cluster, you use kubectl to interact with it and, for autopilot clusters, to add configurations that specify which jobs to run.

1. In the Google Cloud Platform, create an autopilot or standard cluster.

2. Install the kubectl authentication plugin:

   gcloud components install gke-gcloud-auth-plugin
   

3. Connect to the cluster:

   gcloud container clusters get-credentials CLUSTER_NAME --zone=CLUSTER_LOCATION
   

4. View the cluster configuration:

   kubectl config view
   

5. Verify that you are connected to the cluster:

   kubectl config current-context
   

Install and configure the Kubernetes Operator

Now that you have a cluster, you’re ready to install and configure the Kubernetes Operator.

1. Install the prerequisites:

   kubectl apply -f https://github.com/jetstack/cert-manager/releases/download/v1.7.1/cert-manager.yaml
   

2. Install the Operator Lifecycle Manager (OLM), a tool that manages the Kubernetes Operators that run on the cluster:

   curl --silent --location "https://github.com/operator-framework/operator-lifecycle-manager/releases/download/v0.24.0/install.sh" \
    | bash -s v0.24.0
   

3. Install the Kubernetes Operator Catalog:

   kubectl create -f https://raw.githubusercontent.com/operator-framework/operator-lifecycle-manager/master/deploy/upstream/quickstart/crds.yaml
   kubectl create -f https://raw.githubusercontent.com/operator-framework/operator-lifecycle-manager/master/deploy/upstream/quickstart/olm.yaml
   

4. Install the Kubernetes Operator:

   kubectl create -f https://operatorhub.io/install/gitlab-runner-operator.yaml
   

5. Create a secret that contains the runner-registration-token from your GitLab project:

    cat > gitlab-runner-secret.yml << EOF
    apiVersion: v1
    kind: Secret
    metadata:
      name: gitlab-runner-secret
    type: Opaque
    stringData:
   runner-registration-token: YOUR_RUNNER_REGISTRATION_TOKEN
   EOF
   

6. Apply the secret:

   kubectl apply -f gitlab-runner-secret.yml
   

7. For autopilot clusters, you must create a YAML file with additional configuration details. Autopilot clusters use this file to instruct the GKE about what resources the Pod needs so it can run the jobs. You don’t need to create this file for standard clusters. Here is an example configuration:

   cat > config.yml << EOF
   apiVersion: v1
   kind: configMaps
   metadata:
     name: config.toml
   config: |
   [[runners]]
     [runners.kubernetes]
       image = "alpine"
       cpu_limit = "1"
       memory_limit = "128Mi"
       service_cpu_limit = "1"
       service_memory_limit = "128Mi"
       helper_cpu_limit = "500m"
       helper_memory_limit = "100Mi"
   

8. Apply the config.yml:

   kubectl apply -f config.yml
   

9. Create the custom resource definition file and include the following information:

   cat > gitlab-runner.yml << EOF
      apiVersion: apps.gitlab.com/v1beta2
         kind: Runner
         metadata:
         name: gitlab-runner
      spec:
         gitlabUrl: https://gitlab.example.com
         buildImage: alpine
         config: "config.toml"  # <---- Reference to the config.toml configMap
         token: gitlab-runner-secret
      EOF
   

10. Apply the custom resource definition file:

    kubectl apply -f gitlab-runner.yml
    

That’s it! You’ve configured GitLab Runner to use the GKE. In the next step, you can check if your configuration is working.

Verify your configuration

To check if runners are running in the GKE cluster, you can either:

• Use the following command:

  kubectl get pods
  

  You should see the following output. This shows that your runners are running in the GKE cluster:

  NAME                             READY   STATUS    RESTARTS   AGE
  gitlab-runner-hash-short_hash    1/1     Running   0          5m
  

• Check the job log in GitLab:

  1. On the left sidebar, select Search or go to and find your project.
  2. Select Build > Jobs and find the job.
  3. To view the job log, select the job status.