1. Deploy the grafana-storage helm chart on Google Kubernetes Engine (GKE)


    To deploy the grafana-storage Helm chart on Google Kubernetes Engine (GKE) using Pulumi, you'll need to perform several steps:

    1. Set up a GKE cluster where your Helm chart will be deployed.
    2. Install and configure the Helm chart on your GKE cluster.

    In the Pulumi program below, we will use the @pulumi/gcp package to create a GKE cluster, and the @pulumi/kubernetes package to deploy the Helm chart to that cluster.

    Here's a step-by-step TypeScript program for deploying the grafana-storage Helm chart on GKE:

    import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; import * as pulumi from "@pulumi/pulumi"; // Step 1: Create a GKE cluster const cluster = new gcp.container.Cluster("my-gke-cluster", { initialNodeCount: 2, nodeConfig: { preemptible: true, machineType: "n1-standard-1", 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 Cluster name export const clusterName = cluster.name; // Kubeconfig for the cluster 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 `; }); // Step 2: Deploy the Helm chart for grafana-storage const grafanaStorageChart = new k8s.helm.v3.Chart("grafana-storage", { chart: "grafana", version: "6.1.17", // specify the version of the Helm chart fetchOpts:{ repo: "https://grafana.github.io/helm-charts", // specify the Helm chart repository }, values: { storage: { type: "pvc", size: "10Gi" }, persistence: { enabled: true, size: "10Gi" }, // specify more values as required }, }, { provider: new k8s.Provider("k8s-provider", { kubeconfig }) }); // Export the Helm chart deployment name export const grafanaReleaseName = grafanaStorageChart.name;


    In the program above:

    • We import the gcp, k8s, and pulumi modules as these are required to create the GKE cluster and deploy the Helm chart.
    • We create a GKE cluster with a given number of nodes and specific machine types using gcp.container.Cluster.
    • We configure the kubeconfig needed to interact with the cluster. This configuration is built using the cluster details and is tailored to work with the GCP authentication mechanism.
    • We declare a Helm chart release with k8s.helm.v3.Chart. In the values field, we specify the configuration for storage and persistence as would be necessary for Grafana.
    • We use fetchOpts to specify the location of the Helm chart repository.
    • We configure the k8s.Provider with the kubeconfig we created, which ensures that the Helm chart is deployed to the correct GKE cluster.
    • We export the name of the GKE cluster and the Helm chart deployment, which can be useful for querying the cluster and viewing the Helm release details after deployment.

    To apply this Pulumi program, save it to a index.ts file, and run the following commands in your terminal:

    pulumi up

    This will prompt Pulumi to perform an update, during which it will show you a preview of the resources that will be created. If you're happy with the changes, select yes when prompted to create the resources in your GCP project. After the update is completed, you'll see the outputs of the program, including the name of your GKE cluster and the Helm chart release name.