1. Deploy the simple-mssql helm chart on Google Kubernetes Engine (GKE)


    Deploying a Helm chart on Google Kubernetes Engine (GKE) involves several steps. First, you will need to create a GKE cluster. Next, you will need to set up the Helm client and install the chart on the cluster. In Pulumi, you can do both of these using TypeScript.

    Below, I will provide you with a Pulumi program that creates a GKE cluster and deploys the simple-mssql Helm chart to it.

    The program uses two main resources:

    1. gcp.container.Cluster: A resource that creates a GKE cluster. We'll configure it with the necessary settings, but we'll keep it simple for the purpose of this explanation.
    2. kubernetes.helm.v3.Chart: A resource to deploy the Helm chart to the GKE cluster. This assumes the Helm chart simple-mssql is available in a repository.

    Before you run this program, make sure Pulumi is installed and your GCP account is properly set up with the right permissions, and that you have authenticated Pulumi with GCP.

    Here's the full Pulumi program in TypeScript to accomplish your goal:

    import * as pulumi from "@pulumi/pulumi"; import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; // Create a GKE cluster const cluster = new gcp.container.Cluster("my-gke-cluster", { // Define the cluster settings as needed. Adjust the number of nodes, machine type, etc., according to your needs. initialNodeCount: 2, minMasterVersion: "latest", // Use the latest version of GKE, or specify the version you need. nodeVersion: "latest", nodeConfig: { machineType: "n1-standard-1", // Choose the machine type based on your requirements. oauthScopes: [ "https://www.googleapis.com/auth/compute", "https://www.googleapis.com/auth/devstorage.read_only", "https://www.googleapis.com/auth/logging.write", "https://www.googleapis.com/auth/monitoring" ], }, }); // Export the Kubeconfig 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 `; }); // Set up the Kubernetes provider using the generated kubeconfig from the cluster const k8sProvider = new k8s.Provider("k8s-provider", { kubeconfig: kubeconfig }); // Install the simple-mssql Helm chart const mssqlChart = new k8s.helm.v3.Chart("simple-mssql", { chart: "simple-mssql", fetchOpts: { // Specify the repository where the Helm chart is located. Replace with the correct URL for the simple-mssql chart. repo: "http://charts.example.com/", }, }, { provider: k8sProvider }); // Export the Helm chart resources export const helmChartResources = mssqlChart.resources;

    Let's explain what each part of the code does:

    • We start by importing the required modules from Pulumi for GCP and Kubernetes.
    • We create a new GKE cluster with a specified number of nodes and the right configurations for OAuth scopes. We specify the machineType and cluster versions as well.
    • The kubeconfig variable constructs the configuration needed to communicate with the created GKE cluster using the cluster's endpoint and the masterAuth data.
    • We then create a new Pulumi Kubernetes provider that uses the kubeconfig from the GKE cluster we created. This provider will allow us to deploy Kubernetes resources to our cluster.
    • After that, we instantiate the simple-mssql Helm chart deployment. We specify where the Helm chart is located using the fetchOpts.repo. You need to replace this URL with the actual repository where the simple-mssql chart can be found.
    • Finally, we export the Helm chart's resources so that we can interact with them outside of Pulumi as needed.

    To run this Pulumi program:

    1. Save the above code in a file with a .ts extension (e.g., index.ts).
    2. Run pulumi up in the terminal in the same directory as the code file.

    Pulumi will execute the instructions to create the GKE cluster and deploy the Helm chart. If there are any prompts, you may need to respond to them (typically to confirm the creation of resources). Once completed, you'll be able to see the GKE cluster and Helm deployment in your Google Cloud Console.