1. Deploy the cosi-driver-nutanix helm chart on Google Kubernetes Engine (GKE)

    TypeScript

    To deploy the cosi-driver-nutanix Helm chart on Google Kubernetes Engine (GKE), we will outline the necessary steps and then provide a Pulumi program written in TypeScript. The program will use Pulumi's Google Cloud Platform (GCP) package to create a GKE cluster and then deploy the Helm chart to that cluster using Pulumi's Helm package. Here's a high-level overview of what we'll accomplish:

    1. Setting Up the GKE Cluster: We'll start by provisioning a new GKE cluster using Pulumi. The cluster will have all the necessary configurations to run our Helm chart.

    2. Installing Helm and Tiller: Pulumi's Helm package can manage the deployment without directly interacting with Tiller. We'll define the Helm Release resource within our Pulumi program.

    3. Deploying the Helm Chart: Finally, we'll deploy the cosi-driver-nutanix chart to our GKE cluster.

    Detailed Explanation

    GKE Cluster Provisioning

    We will use @pulumi/gcp to create a new GKE cluster. A cluster typically requires a name, the zone or region where it is hosted, a description, and configuration details like the machine type for the nodes, the number of nodes, and the network settings.

    Deploying Helm Chart

    Pulumi supports Helm through a Helm Release resource (@pulumi/kubernetes/helm/v3). To deploy a Helm chart, you simply specify the chart name, version, and any values you want to override.

    Additional Notes

    • Make sure you have GCP project setup and Pulumi configured.
    • This program assumes you have the correct access rights to create and manage GKE clusters and deploy Helm charts on GCP.

    Now let's see what the Pulumi TypeScript program would look like for setting this up:

    import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; import * as helm from "@pulumi/kubernetes/helm"; // Create a GKE cluster const cluster = new gcp.container.Cluster("gke-cluster", { initialNodeCount: 2, nodeVersion: "latest", minMasterVersion: "latest", nodeConfig: { machineType: "n1-standard-1", }, }); // Export the Cluster name export const clusterName = cluster.name; // Create a K8s Provider instance of the cluster const k8sProvider = new k8s.Provider("k8s-provider", { kubeconfig: cluster.kubeConfigRaw, }); // Install the cosi-driver-nutanix Helm chart const helmChart = new helm.v3.Chart("cosi-driver-nutanix-chart", { chart: "cosi-driver-nutanix", // You might need to add a repository or specify a different chart version depending on your use case. // version: "Specify your chart version here", // repositoryOpts: { // repo: "URL-of-Helm-Chart-repository" // }, // Set any helm values here that you want to override. values: { // For example, you can specify the driver and provisioner Image: // driver: { // image: { // repository: "nutanix/csi-driver", // tag: "Specify your image tag here" // }, // provisioner: { // image: { // repository: "nutanix/csi-provisioner", // tag: "Specify your image tag here" // } // } }, }, { provider: k8sProvider }); // Export the status of the deployed Helm chart export const helmChartStatus = helmChart.status;

    How to Use This Program

    1. Save this code to a file named index.ts.
    2. To run this program, you need to have Pulumi installed and configured. Ensure your Pulumi CLI is authenticated to your GCP account.
    3. In the terminal, navigate to the directory where index.ts is located.
    4. Run pulumi up in the terminal. Pulumi will perform the deployment and provide a CLI prompt showing the resources that will be created.
    5. Review the changes and, if they are acceptable, confirm the prompt to proceed.
    6. Pulumi will create a GKE cluster and deploy the Helm chart as specified.
    7. Once completed, Pulumi will output any exported values such as clusterName and helmChartStatus.

    Remember that the code above is a starting point. Depending on the Helm chart you want to deploy and its requirements, you might need to specify different chart properties, value overrides, and potentially cluster configurations.