Google Kubernetes Engine (GKE) with a canary deployment

This example lives in the pulumi/examples repository. Check out just this directory to use it:

$ git clone --filter=blob:none --sparse https://github.com/pulumi/examples pulumi-examples
$ git -C pulumi-examples sparse-checkout set gcp-py-gke
$ cd pulumi-examples/gcp-py-gke

This example provisions a Google Kubernetes Engine (GKE) cluster, using infrastructure-as-code, and then deploys a Kubernetes Deployment into it, to test that the cluster is working. This demonstrates that you can manage both the Kubernetes objects themselves, in addition to underlying cloud infrastructure, using a single configuration language (in this case, Python), tool, and workflow.

Prerequisites#

1. Install Pulumi
2. Configure GCP credentials
3. Install Python

This example assumes that you have GCP’s gcloud CLI on your path. This is installed as part of the GCP SDK.

Deploying the example#

1. Create a new stack:

   pulumi stack init dev

2. Set the required configuration variables for this program:

   pulumi config set gcp:project [your-gcp-project-here]
   pulumi config set gcp:zone us-west1-a
   pulumi config set password --secret [your-cluster-password-here]
   pulumi config set master_version #any valid master version

   By default, your cluster will have 3 nodes of type n1-standard-1. This is configurable, however; for instance if you’d like to choose 5 nodes of type n1-standard-2 instead, you can run these commands:

   pulumi config set node_count 5
   pulumi config set node_machine_type n1-standard-2

   This shows how stacks can be configurable in useful ways. You can even change these after provisioning.

3. Install dependencies:

   python3 -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt

4. Deploy everything with the pulumi up command. This provisions all the GCP resources necessary, including your GKE cluster itself, and then deploys a Kubernetes Deployment running NGINX, all in a single gesture:

   pulumi up

   This will show you a preview, ask for confirmation, and then chug away at provisioning your cluster:

   Updating (dev)
   
        Type                            Name          Plan
    +   pulumi:pulumi:Stack             gcp-py-dev    create
    +   ├─ gcp:container:Cluster        gke-cluster   create
    +   ├─ pulumi:providers:kubernetes  gkeK8s        create
    +   └─ kubernetes:apps:Deployment   canary        create
    +   └─ kubernetes:core:Service      ingress       create
   
       Outputs:
       kubeConfig: "apiVersion: v1\n..."
   
   Resources:
       + 5 created
   
   Duration: 2m07s

   After about two minutes, your cluster will be ready, and its config will be printed.

5. From here, you may take this config and use it either in your ~/.kube/config file, or just by saving it locally and plugging it into the KUBECONFIG envvar. All of your usual gcloud commands will work too, of course. For instance:

   pulumi stack output kubeconfig --show-secrets > kubeconfig.yaml
   KUBECONFIG=./kubeconfig.yaml kubectl get po

   NAME                              READY     STATUS    RESTARTS   AGE
   canary-n7wfhtrp-fdbfd897b-lrm58   1/1       Running   0          58s

6. At this point, you have a running cluster. Feel free to modify your program, and run pulumi up to redeploy changes. The Pulumi CLI automatically detects what has changed and makes the minimal edits necessary to accomplish these changes. This could be altering the existing chart, adding new GCP or Kubernetes resources, or anything, really.

Cleaning up#

Once you’re finished experimenting, destroy your stack and remove it:

pulumi destroy
pulumi stack rm