1. Deploy the zebrands helm chart on Google Kubernetes Engine (GKE)


    Deploying a Helm chart to a Google Kubernetes Engine (GKE) cluster involves several steps. First, you'll need to create a GKE cluster if you don't already have one. Then, you'll use Pulumi to deploy the Helm chart onto the cluster.

    Let's go through these steps one by one.

    1. Create a GKE cluster: To run the Helm chart, you need a Kubernetes cluster. GKE is a managed environment for deploying, managing, and scaling containerized applications using Google infrastructure. We use gcp.container.Cluster to provision a GKE cluster.

    2. Deploy Helm Chart: Once the cluster is up and running, you can deploy the Helm chart to it. The kubernetes.helm.v3.Chart class from Pulumi's Kubernetes provider is used to deploy Helm charts.

    Below is a TypeScript Pulumi program that demonstrates how to do this. I'll walk you through the essential parts of the code afterward.

    import * as pulumi from "@pulumi/pulumi"; import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; // The Google Cloud project and region where we'll deploy the GKE cluster. const project = gcp.config.project; // Assuming that GCP project is set in the Pulumi config const region = gcp.config.region; // Assuming that GCP region is set in the Pulumi config // Create a GKE cluster. const cluster = new gcp.container.Cluster("zebrands-cluster", { // Specify the location to deploy the cluster location: region, initialNodeCount: 3, minMasterVersion: "latest", nodeVersion: "latest", nodeConfig: { preemptible: false, machineType: "n1-standard-1", oauthScopes: [ "https://www.googleapis.com/auth/cloud-platform", ], }, }); // Export the Kubeconfig file for the GKE cluster. export const kubeconfig = pulumi.all([cluster.name, cluster.endpoint, cluster.masterAuth]).apply(([name, endpoint, masterAuth]) => { const context = `${gcp.config.project}_${gcp.config.zone}_${name}`; return `apiVersion: v1 clusters: - cluster: certificate-authority-data: ${masterAuth.clusterCaCertificate} server: https://${endpoint} name: ${context} contexts: - context: cluster: ${context} user: ${context} name: ${context} current-context: ${context} kind: Config preferences: {} users: - name: ${context} user: auth-provider: config: cmd-args: config config-helper --format=json cmd-path: gcloud expiry-key: '{.credential.token_expiry}' token-key: '{.credential.access_token}' name: gcp `; }); // Create a Kubernetes provider instance that uses our GKE cluster from above. const k8sProvider = new k8s.Provider("k8sProvider", { kubeconfig: kubeconfig, }); // Deploy the zebrands Helm chart to the GKE cluster. const zebrandsChart = new k8s.helm.v3.Chart("zebrands", { chart: "zebrands", // The name of the chart, assuming 'zebrands' is available in the repository version: "1.0.0", // The version of the chart to deploy namespace: "default", // The Kubernetes namespace in which to deploy the chart }, { provider: k8sProvider }); // Export the Cluster name and Kubernetes provider, in case we need to use them outside of Pulumi. export const clusterName = cluster.name; export const k8sProviderName = k8sProvider.name;

    How the code works:

    • We start by importing the required Pulumi packages.
    • We're defining a GKE cluster using gcp.container.Cluster. The configuration includes the region, the number of nodes, the version of Kubernetes, the node configuration and the OAuth scopes needed for the nodes.
    • The next step is to prepare the kubeconfig data, which is required by any client (e.g., kubectl, Pulumi) to authenticate against the cluster.
    • A Pulumi Kubernetes provider is then instantiated with this kubeconfig. This Kubernetes provider object configures Pulumi to use the GKE cluster for deploying Kubernetes resources.
    • Finally, we're creating a Helm chart resource with k8s.helm.v3.Chart, pointing to the zebrands chart. This chart should be available in your Helm chart repository or a public repository.
    • There are export statements that output the cluster name and the Kubernetes provider reference, which can be useful when composing larger systems or for use in other Pulumi stacks.

    In a real-world scenario, the chart name and version would be replaced with the actual chart you want to deploy.

    To run this program:

    1. Set up Pulumi with GCP credentials.
    2. Install the necessary Pulumi packages for GCP and Kubernetes using NPM or Yarn.
    3. Save the above code into a file named index.ts.
    4. Run pulumi up to deploy these resources.

    Keep in mind that deploying a Kubernetes cluster using this code will incur costs in your GCP account, and you'll also need to ensure you have sufficient permissions to create and manage GKE clusters and other resources.