1. Deploy the codecov helm chart on Google Kubernetes Engine (GKE)

    TypeScript

    To deploy the codecov helm chart on Google Kubernetes Engine (GKE), you will need to follow these general steps:

    1. Set up a new GKE cluster or use an existing one.
    2. Configure Pulumi to use the gcp provider for deploying resources on Google Cloud.
    3. Install and configure Helm support in Pulumi for deploying Helm charts.
    4. Use the Pulumi Helm package to deploy the codecov Helm chart onto the GKE cluster.

    In the TypeScript Pulumi code below, we will:

    • Define a GKE cluster.
    • Use the Pulumi harness provider, which provides a Helm resource, to deploy the codecov Helm chart.

    First, you need to ensure you have Pulumi CLI installed and are authenticated with GCP. Set up your GCP credentials through the gcloud CLI or export your GOOGLE_APPLICATION_CREDENTIALS as an environment variable pointing to the service account key file.

    Now let's create the TypeScript program. Remember that you need Node.js and @pulumi/pulumi and @pulumi/gcp packages installed to run the following Pulumi code.

    Here's the complete Pulumi program which you can use the pulumi up command to deploy:

    import * as pulumi from "@pulumi/pulumi"; import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; import * as helm from "@pulumi/kubernetes/helm/v3"; // Create a GKE cluster const cluster = new gcp.container.Cluster("codecov-cluster", { initialNodeCount: 2, minMasterVersion: "latest", nodeVersion: "latest", nodeConfig: { // You can specify the machine type, disk size, etc. machineType: "e2-medium", 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; // 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: ${context} user: auth-provider: config: cmd-args: config config-helper --format=json cmd-path: gcloud expiry-key: '{.credential.token_expiry}' token-key: '{.credential.access_token}' name: gcp `; }); // Initialize a new Kubernetes provider instance using the kubeconfig const k8sProvider = new k8s.Provider("k8s-provider", { kubeconfig: kubeconfig, }); // Deploy the codecov Helm chart on the GKE cluster using the Helm Release resource const codecovChart = new helm.Chart("codecov-helm-chart", { chart: "codecov", // You will need to specify the correct repository where the codecov chart is located. // For this example, I'm assuming it's in a hypothetical helm repo 'myhelmrepo'. fetchOpts: { repo: "https://charts.myhelmrepo.com/", }, // Specify the necessary values for the helm chart. You should refer to the documentation // or values file of the chart for the set of acceptable configuration options. values: { // Example values, these will vary based on actual helm chart parameters // replicaCount: 1, // service: { // type: "LoadBalancer", // }, }, }, { provider: k8sProvider }); // Export the URL for the deployed codecov application export const codecovUrl = pulumi.interpolate`http://${codecovChart.getResourceProperty("v1/Service", "codecov-helm-chart-codecov", "status")["loadBalancer"]["ingress"][0]["ip"]}`;

    Explanation

    In this program:

    • We import the required Pulumi packages for Google Cloud, Kubernetes, and Helm.
    • We define a GKE cluster with the gcp.container.Cluster class, specifying the initial node count and other node configurations like machine type and necessary OAuth scopes.
    • We then export two key pieces of information:
      • The clusterName which is the name of the created GKE cluster.
      • The kubeconfig which contains the kubeconfig file content, allowing kubectl and Pulumi's Kubernetes Provider to interact with our GKE cluster.
    • Next, we create a Kubernetes provider instance that uses the exported kubeconfig.
    • Using the helm.Chart resource, we deploy the codecov Helm chart onto our GKE cluster by specifying the chart's name and repository location. Ensure you replace the repo URL with the actual repository where the codecov Helm chart is hosted.
    • We may include chart values which configure the Helm chart deployment. These values need to match with the codecov Helm chart's expected configuration parameters.
    • Finally, we export the potential codecovUrl which will contain the public IP address of the Service created by the Helm chart, allowing us to access the codecov application.

    To apply this Pulumi program, save the code to a file named index.ts, then run pulumi up. Pulumi will handle the creation of the resources for you. Observe the output on the console to ensure the deployment process finishes successfully, and take note of any exported values, which include the cluster name and codecov URL.