1. Deploy the keycloak-db helm chart on Google Kubernetes Engine (GKE)


    To deploy the Keycloak DB Helm chart on Google Kubernetes Engine (GKE), we will go through a multi-step process:

    1. Set up a GKE cluster: We will create a GKE cluster where Keycloak will run. The cluster will be composed of multiple nodes (VM instances) that will be managed by Kubernetes.

    2. Install and configure Helm: Helm is a package manager for Kubernetes, which allows us to easily deploy and manage applications on Kubernetes clusters. We'll need to set up Helm in the GKE cluster to deploy Keycloak.

    3. Deploy Keycloak using Helm: Once Helm is ready, we will use it to deploy the Keycloak DB Helm chart which will create all the necessary Kubernetes resources (Pods, Services, Deployments, etc.) for running Keycloak.

    Here's a step-by-step Pulumi program written in TypeScript that will create a new GKE cluster and deploy the Keycloak DB Helm chart onto it:

    import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; import * as pulumi from "@pulumi/pulumi"; // Create a GKE cluster. const cluster = new gcp.container.Cluster("gke-cluster", { initialNodeCount: 2, minMasterVersion: "latest", nodeVersion: "latest", nodeConfig: { preemptible: true, 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 `; }); // Create a Provider for the GKE cluster const clusterProvider = new k8s.Provider("gke-provider", { kubeconfig: kubeconfig, }); // Using Helm to deploy Keycloak DB const keycloakChart = new k8s.helm.v3.Chart("keycloak-db", { chart: "keycloak", // This should represent the actual chart name for Keycloak DB if different. version: "x.y.z", // Specify the version of the chart. fetchOpts:{ repo: "http://charts.bitnami.com/bitnami", // Assuming Keycloak chart is in the Bitnami repo. }, }, { provider: clusterProvider }); // Export the Keycloak frontend service endpoint export const keycloakFrontend = keycloakChart.getResourceProperty("v1/Service", "keycloak-db", "status").loadBalancer.ingress[0].ip;


    • GKE Cluster: We create a new GKE cluster with initialNodeCount set to 2. This specifies that we want two nodes in our cluster initially.
    • Cluster Export: We export the cluster name and generate kubeconfig which is used by the Kubernetes provider to communicate with the GKE cluster.
    • Kubernetes Provider: We create a Pulumi Kubernetes provider which is responsible for deploying resources onto the Kubernetes cluster.
    • Helm Chart: We define a Helm chart from a public repository (like Bitnami repo here for illustration). Replace x.y.z with the actual chart version desired.
    • Keycloak Service Endpoint: After deploying the Helm chart, we export the endpoint of the Keycloak DB service assuming it's exposed via a LoadBalancer service. If it's not exposed via a LoadBalancer, corresponding access instructions will need to be adjusted.

    Make sure that you have Pulumi set up, along with access to a GCP account where you have the permission to create GKE clusters. You'll also need Helm installed and configured to work with your Kubernetes clusters.

    Remember, the specific configurations for the Node pool, such as machineType or oauthScopes and the Helm chart version, may need to be adjusted for the real-world scenario based on actual requirements and available resources.