1. Deploy the plausible-analytics helm chart on Google Kubernetes Engine (GKE)

    TypeScript

    To deploy the Plausible Analytics Helm chart on Google Kubernetes Engine (GKE), you will need to follow a few steps. Firstly, you need to create a GKE cluster where the Helm chart will be deployed. Once the cluster is ready, configure Pulumi to work with the Kubernetes cluster and then use the Helm chart integration with Pulumi to deploy Plausible Analytics.

    Here's a breakdown of the steps:

    1. Create a GKE Cluster: Use Pulumi's google-native.container/v1beta1.Cluster resource to create a new GKE cluster. You need to specify details such as the number of nodes, machine type, etc.

    2. Create a Kubernetes Provider: After the cluster is created, you will need to configure Pulumi to interact with it. This involves creating a Kubernetes provider that uses the cluster's context.

    3. Deploy the Helm Chart: With the provider configured, use the pulumi-kubernetes's Helm chart resource to deploy Plausible Analytics to your GKE cluster.

    Here's the TypeScript program that gives you the necessary code for this process:

    import * as gcp from '@pulumi/gcp'; import * as pulumi from '@pulumi/pulumi'; import * as k8s from '@pulumi/kubernetes'; // Create a new GKE cluster const cluster = new gcp.container.Cluster("plausible-cluster", { initialNodeCount: 2, minMasterVersion: "latest", nodeVersion: "latest", nodeConfig: { 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; // Obtain a kubeconfig. You need to replace '<' and '>' with proper values for your GKE 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 `; }); // Create a Kubernetes provider instance that uses our cluster from above. const k8sProvider = new k8s.Provider("gkeK8s", { kubeconfig: kubeconfig, }); // Deploy the Plausible Analytics Helm chart const plausibleAnalyticsChart = new k8s.helm.v3.Chart("plausible-analytics", { chart: "plausible", version: "1.0.0", // Specify the version of the chart you want to deploy fetchOpts:{ repo: "https://helm.plausible.io/", }, }, { provider: k8sProvider }); // Export the plausible service endpoint export const plausibleServiceEndpoint = plausibleAnalyticsChart.getResource("v1/Service", "plausible-analytics");

    This program creates a GKE cluster with two nodes using n1-standard-1 machines and then defines a pulumi Kubernetes provider with the kubeconfig of the created GKE cluster.

    Next, it deploys Plausible Analytics using its Helm chart. The fetchOpts specifies the Helm repository where the chart can be found. It's important to replace 1.0.0 with the actual version number of Plausible Analytics Helm chart you want to deploy.

    This Pulumi program needs to be run using the Pulumi CLI, which will automatically carry out the actions defined in the code when you run pulumi up.

    Remember to adjust the placeholder text in kubeconfig with your project's information and the GKE cluster you want to target. Also replace 1.0.0 with the desired Plausible Analytics Helm chart version available in the Helm chart repository at the time of deployment.

    To use this code, you'd write it to a file named index.ts, and then run pulumi up in the same directory as the file, after logging into the Pulumi service with pulumi login.

    Pulumi will print out the status of the resources being created and will provide you with the endpoints and other outputs you have specified once the deployment is complete.