1. Deploy the redis-cache helm chart on Google Kubernetes Engine (GKE)


    To deploy the Redis Cache Helm chart on Google Kubernetes Engine (GKE), you need to perform the following high-level steps:

    1. Set up a GKE cluster: Before you can deploy the Helm chart, you need a running Kubernetes cluster. You can create a new cluster using Pulumi's GCP package.
    2. Install and configure Helm: Helm is a package manager for Kubernetes that allows you to define, install, and upgrade complex Kubernetes applications. For Helm to work with your GKE cluster, it needs to be installed on your local machine or within a CI/CD environment, and you need to configure it to communicate with your GKE cluster.
    3. Deploy the Redis Helm chart: Once Helm is set up, you can use it to deploy the Redis chart from a chart repository to your cluster.

    Below is a Pulumi program written in TypeScript that sets up a GKE cluster and deploys the Redis Helm chart. It assumes you have Pulumi installed, along with access to a Google Cloud account. The Google Cloud SDK should be authorized to access your account as usual, and the Pulumi CLI should be logged in.

    import * as gcp from "@pulumi/gcp"; import * as k8s from "@pulumi/kubernetes"; // Create a GKE cluster. const cluster = new gcp.container.Cluster("redis-cluster", { initialNodeCount: 2, minMasterVersion: "latest", // Use the latest GKE version available nodeVersion: "latest", nodeConfig: { // Using a machine type with sufficient resources for Redis 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 using 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}' name: gcp `; }); // Create a Kubernetes provider that uses our cluster's kubeconfig. const provider = new k8s.Provider("gkeK8s", { kubeconfig: kubeconfig, }); // Deploy the Redis helm chart using the Helm provider const redisChart = new k8s.helm.v3.Chart("redis-cache", { chart: "redis", version: "15.3.1", // You can specify the Redis chart version you want to deploy fetchOpts: { // Optional: Fetch the chart from a specified Helm chart repository repo: "https://charts.bitnami.com/bitnami", }, }, { provider }); // Export the Redis service endpoint export const redisEndpoint = redisChart.getResourceProperty("v1/Service", "redis-cache-redis-master", "status").apply(status => status.loadBalancer.ingress[0].ip);


    • We're creating a GKE cluster with gcp.container.Cluster. The chosen machine type n1-standard-1 should be sufficient for hosting a small Redis cache.
    • We configure the oauthScopes to give Kubernetes nodes the necessary Google Cloud permissions.
    • The kubeconfig variable is structured to interact with the cluster using kubectl.
    • We create a Pulumi Kubernetes provider that points to our GKE cluster. The provider will use the generated kubeconfig to interact with the cluster.
    • We then deploy the Redis chart using the k8s.helm.v3.Chart resource from the Pulumi Kubernetes package. We specify the chart name redis, the version, and the repository URL where the Redis Helm chart is located.
    • Finally, we export the endpoint of the Redis server service which can be used to connect to the Redis cache once the deployment is complete.

    Remember to have Helm and gcloud command-line tools installed, and you must be authenticated to the cluster for Helm to interact with it.