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


    To deploy the Senlin Helm chart on Google Kubernetes Engine (GKE), we'll go through the following steps:

    1. Set up a GKE Cluster: We'll create a GKE cluster where our applications and services will run.

    2. Deploy the Senlin Helm Chart: Once we have our Kubernetes cluster ready, we'll use the Helm Chart to deploy Senlin. Helm is a package manager for Kubernetes, which allows us to define, install, and upgrade complex Kubernetes applications. A Helm Chart is a set of pre-configured Kubernetes resources that can be managed as a single unit.

    For this scenario, we will be using two main Pulumi classes:

    • gcp.container.Cluster: This class allows us to create a Google Kubernetes Engine cluster.
    • kubernetes.helm.v3.Chart: This class allows us to deploy Helm charts to a Kubernetes cluster.

    Here's a step-by-step TypeScript program using Pulumi to deploy the Senlin Helm chart on a GKE cluster:

    import * as pulumi from "@pulumi/pulumi"; import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; const name = "senlin-cluster"; // Create a GKE cluster const cluster = new gcp.container.Cluster(name, { 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; // Export the Kubeconfig to access the Cluster from 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}'`; }); // Create a Kubernetes provider instance that uses our cluster from above. const k8sProvider = new k8s.Provider(name, { kubeconfig: kubeconfig, }); // Deploy Senlin Helm Chart using the Kubernetes provider const senlinChart = new k8s.helm.v3.Chart("senlin", { chart: "senlin", version: "1.0.0", fetchOpts:{ repo: "http://helm-repository-url/", // Specify the Helm repository URL here }, }, { provider: k8sProvider }); // Export the Senlin Helm chart deployment name export const senlinChartName = senlinChart.getResourceName("v1/Service", "default", "senlin");

    In this program:

    • We create a gcp.container.Cluster object to provision a new GKE cluster. The cluster is configured to have 2 nodes, use the N1 standard machine type n1-standard-1, and have the necessary OAuth scopes.

    • We then export the cluster name and generate kubeconfig for accessing the cluster. This kubeconfig can be used with the kubectl command-line tool to interact with the Kubernetes cluster.

    • We create a k8s.Provider object, which knows how to talk to our GKE cluster using the generated kubeconfig.

    • Finally, we declare a k8s.helm.v3.Chart object that installs the Senlin Helm chart onto our cluster with the specified version and Helm repository URL. You need to provide the correct Helm chart repository URL where the Senlin chart is located.

    Make sure to replace "http://helm-repository-url/" with the actual URL of the Helm chart repository where Senlin is hosted.

    To run this code, you will need to:

    1. Ensure you have Pulumi installed and configured with the correct cloud credentials.
    2. Install Node.js and npm if you haven't already.
    3. Create a new directory, navigate into it, and then create a new Pulumi project using pulumi new gcp-typescript.
    4. Replace the contents of the index.ts file with the program above.
    5. Run pulumi up to preview and deploy the changes.

    Remember that managing cloud resources cost money and might incur charges, so be mindful of the resources you are creating.