1. Deploy the mongodb-bi-connector helm chart on Digital Ocean Kubernetes Service


    To accomplish your goal of deploying the MongoDB BI Connector Helm chart on Digital Ocean's Kubernetes Service using Pulumi, we'll proceed with the following steps:

    1. Set up a Kubernetes cluster on Digital Ocean.
    2. Deploy the Helm chart for MongoDB BI Connector to the cluster.

    We'll use Pulumi's DigitalOcean provider to provision the Kubernetes cluster and Pulumi's Kubernetes provider to deploy the Helm chart. Here's how you can achieve this:

    Setting up the Kubernetes Cluster on Digital Ocean

    First, we need to create a new Kubernetes cluster on Digital Ocean. For this, we'll utilize the digitalocean.KubernetesCluster resource, which allows us to define the desired state for our cluster including the number of nodes, their size, and the region where the cluster should be located.

    Deploying the Helm Chart

    Next, to deploy the MongoDB BI Connector, we'll use the kubernetes.helm.v3.Chart resource from Pulumi's Kubernetes provider. This resource allows us to deploy Helm charts into a Kubernetes cluster. We'll need to specify the chart name and any additional values you might want to override.

    Below is the TypeScript program you would use to deploy this infrastructure. Please copy this code into a new Pulumi project:

    import * as pulumi from '@pulumi/pulumi'; import * as digitalocean from '@pulumi/digitalocean'; import * as k8s from '@pulumi/kubernetes'; // Create a Digital Ocean Kubernetes cluster const cluster = new digitalocean.KubernetesCluster('do-cluster', { region: 'nyc3', // New York region version: 'latest', // Specifies the desired Kubernetes version nodePool: { name: 'do-pool', size: 's-2vcpu-2gb', // The size of Droplets to use in the node pool nodeCount: 2, // Number of nodes in the node pool }, }); // Export the Digital Ocean Kubernetes cluster kubeconfig export const kubeconfig = cluster.kubeConfigs[0].rawConfig; // Create a Kubernetes provider instance using the kubeconfig from the cluster we just created const k8sProvider = new k8s.Provider('k8s-provider', { kubeconfig: cluster.kubeConfigs[0].rawConfig, }); // Deploy the MongoDB BI Connector Helm chart const mongodbBiConnectorChart = new k8s.helm.v3.Chart('mongodb-bi-connector', { chart: 'mongodb-bi-connector', // The name of the chart version: 'x.y.z', // Replace with the desired chart version fetchOpts: { repo: 'https://helm.mongodb.com/', // The Helm repository URL }, }, { provider: k8sProvider }); // Optional step: Export the URL by which the MongoDB BI Connector is accessible // This might depend on how the Helm chart exposes the service (e.g., LoadBalancer, NodePort) // Check the specific Helm chart documentation for more details // export const mongodbBiConnectorUrl = ...


    • We import the required modules such as @pulumi/pulumi, @pulumi/digitalocean, and @pulumi/kubernetes.
    • We create a Kubernetes cluster in the New York (nyc3) region, specifying the version of Kubernetes, the size, and the number of Droplet nodes in our node pool.
    • We export the kubeconfig, which is needed to interact with the Kubernetes cluster using kubectl or other Kubernetes tools.
    • We create a Pulumi Kubernetes provider, which uses the exported kubeconfig to access our Kubernetes cluster.
    • We deploy the MongoDB BI Connector using the Helm chart by specifying the chart name and version (you need to replace 'x.y.z' with the actual version of the Helm chart you want to use), and the Helm repository where the chart is located.

    After running this program with pulumi up, Pulumi will provision a new Kubernetes cluster in Digital Ocean and deploy the MongoDB BI Connector Helm chart to it.

    Keep in mind that the specific values for the cluster and mongodbBiConnectorChart should be modified according to your particular requirements, such as region, droplet size, number of nodes, Helm chart version, and any custom values for the BI Connector configuration. Additionally, note that the export const kubeconfig line allows you to export the cluster configuration so you can use kubectl to interact with the cluster from your local machine.