1. Deploy the elasticsearch-master helm chart on Digital Ocean Kubernetes Service


    Deploying an Elasticsearch Helm chart onto a DigitalOcean Kubernetes Service involves two primary steps:

    1. Provisioning a Kubernetes cluster on DigitalOcean.
    2. Deploying the elasticsearch-master Helm chart onto the Kubernetes cluster.

    For provisioning a Kubernetes cluster on Digital Ocean, you'd use the digitalocean.KubernetesCluster resource. This resource allows you to create, update, and manage Kubernetes clusters in your DigitalOcean account.

    Once the cluster is ready, you can deploy the elasticsearch-master Helm chart using the kubernetes.helm.v3.Chart resource from the Pulumi Kubernetes provider. Helm charts help streamline the installation and management of Kubernetes applications.

    Below is a complete Pulumi TypeScript program that accomplishes these tasks:

    import * as pulumi from "@pulumi/pulumi"; import * as digitalocean from "@pulumi/digitalocean"; import * as k8s from "@pulumi/kubernetes"; // Create a DigitalOcean Kubernetes cluster const cluster = new digitalocean.KubernetesCluster("do-cluster", { region: "nyc1", version: "latest", // You could specify a particular version of Kubernetes here. nodePool: { name: "default", size: "s-2vcpu-2gb", // Select the size that fits your needs or budget. nodeCount: 2, // Number of nodes in the NodePool. }, }); // Export the DigitalOcean kubeconfig to connect to your cluster. export const kubeconfig = cluster.kubeConfigs[0].rawConfig; // Instantiate the Helm chart for elasticsearch-master. const elasticsearchChart = new k8s.helm.v3.Chart("elasticsearch-master", { chart: "elasticsearch", // The name of the chart version: "7.9.3", // The version of the chart fetchOpts: {repo: "https://helm.elastic.co"}, // The repository where the chart is located. // You can include additional configuration here, using key-value pairs in `values`. }, { provider: new k8s.Provider("k8s-provider", {kubeconfig: kubeconfig}) }); // Export the Elasticsearch endpoint to access your Elasticsearch instance. export const elasticsearchEndpoint = elasticsearchChart.getResourceProperty("v1/Service", "elasticsearch-master", "status").apply(status => status.loadBalancer.ingress[0].ip);

    In this program:

    • We import the necessary modules from Pulumi's DigitalOcean and Kubernetes SDKs.
    • We create a Kubernetes cluster on DigitalOcean using the digitalocean.KubernetesCluster resource. You can customize the region, Kubernetes version, size, and number of nodes according to your requirements.
    • We export the kubeconfig, which contains configuration information like cluster IP, user credentials, certs, etc., used to communicate with the cluster.
    • We then define a Pulumi Kubernetes provider instance using the kubeconfig so that Pulumi can instruct Kubernetes what to do. When provided this kubeconfig, the Kubernetes provider knows which cluster to deploy resources to.
    • We deploy the elasticsearch-master Helm chart using the k8s.helm.v3.Chart resource. The charts parameters like name, repo, and version must be specified accurately according to the Helm chart you're deploying.
    • Finally, we export the elasticsearchEndpoint, which can be used to interact with the Elasticsearch instance once it becomes available. Note that this field assumes that your Elasticsearch Service exposes a LoadBalancer and might vary based on actual configuration.

    The above Pulumi program creates a cluster and deploys Elasticsearch without manual configuration of Kubernetes or Helm CLI tools. The values of region, size, and nodeCount in the digitalocean.KubernetesCluster resource, and the chart, version, and repo in the k8s.helm.v3.Chart resource can be adjusted according to the actual requirements and the Elasticsearch chart's documentation.

    Remember to install the required Pulumi packages in your project using npm install or yarn add before running the Pulumi program, like so:

    npm install @pulumi/pulumi @pulumi/digitalocean @pulumi/kubernetes