1. Deploy the quickstart-python helm chart on Google Kubernetes Engine (GKE)


    To deploy the quickstart-python Helm chart on Google Kubernetes Engine (GKE), we'll need to perform a few steps:

    1. Create a GKE Cluster: We will begin by provisioning a GKE cluster using Pulumi's GCP provider.
    2. Install the Helm Chart: After the cluster is up and running, we will install the quickstart-python Helm chart into our GKE cluster.

    I'll guide you through a Pulumi TypeScript program that accomplishes these steps. Note that you will need to have Pulumi CLI installed, and appropriate GCP credentials configured.

    Let's start by defining the GKE cluster:

    import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; import * as pulumi from "@pulumi/pulumi"; // Create a GKE cluster const cluster = new gcp.container.Cluster("my-gke-cluster", { initialNodeCount: 2, minMasterVersion: "latest", nodeVersion: "latest", nodeConfig: { preemptible: true, machineType: "n1-standard-1", oauthScopes: [ "https://www.googleapis.com/auth/cloud-platform", ], }, }); // Export the Cluster name export const clusterName = cluster.name; // Export the Kubeconfig to access the cluster with kubectl 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 `; });

    This code snippet does the following:

    • Imports the necessary Pulumi libraries for GCP and Kubernetes.
    • Creates a GKE cluster with two nodes using the n1-standard-1 machine type, which are preemptible VMs. This can help reduce costs, but they may be terminated and replaced by the cloud provider at any time.
    • Exports the cluster name and the generated Kubeconfig. The Kubeconfig is essential to interact with the cluster using kubectl or any Kubernetes client libraries.

    Next, we need to set up the Helm chart deployment. This requires Pulumi's Kubernetes provider to install the Helm chart.

    // The following code assumes the Pulumi program has already been provided // above, including the creation of a GKE cluster named `my-gke-cluster`. // Create a Kubernetes provider instance that uses our cluster from above. const k8sProvider = new k8s.Provider("my-k8s-provider", { kubeconfig: kubeconfig, }); // Deploy the `quickstart-python` Helm chart into the `my-gke-cluster`. const chart = new k8s.helm.v3.Chart("quickstart-python", { chart: "quickstart-python", version: "1.0.0", // specify the exact chart version fetchOpts: { repo: "https://charts.example.com/", // specify the correct Helm chart repository }, }, { provider: k8sProvider }); // Export the Chart name export const chartName = chart.name;

    This code snippet accomplishes the following:

    • Uses the Kubernetes provider configured with the Kubeconfig obtained from our GKE cluster, allowing us to interact with the cluster.
    • Installs the quickstart-python Helm chart in our GKE cluster. Since Helm charts are usually versioned and stored in repositories, you need to specify the repository URL and the version you want to deploy.
    • Exports the name of the deployed Helm chart for reference.

    Ensure to replace "https://charts.example.com/" with the actual URL of the Helm chart repository that hosts the quickstart-python chart and specify the correct version.

    Combining these two code snippets into a single Pulumi program will create a GKE cluster and deploy the quickstart-python Helm chart onto it.