1. Deploy the fastapi helm chart on Digital Ocean Kubernetes Service

    TypeScript

    To deploy the FastAPI Helm chart on the Digital Ocean Kubernetes Service using Pulumi, you will be working with a few key components:

    1. DigitalOcean Kubernetes Cluster: This is where your FastAPI application will be hosted. The digitalocean.KubernetesCluster resource allows you to provision a new Kubernetes cluster on DigitalOcean.
    2. Helm Chart: Helm is a package manager for Kubernetes, allowing you to define, install, and upgrade Kubernetes applications. You will use the kubernetes.helm.v3.Chart from the Pulumi Kubernetes provider to deploy the FastAPI Helm chart onto the cluster you provisioned.

    Here's how to set this up using Pulumi with TypeScript:

    1. Set up and Import Packages: First, you need to import the necessary Pulumi DigitalOcean and Kubernetes packages for TypeScript.
    2. Write the Main Program Logic: You'll use these packages to set up the DigitalOcean Kubernetes cluster and deploy a Helm chart for FastAPI.

    The following program explains step-by-step how we accomplish this. Make sure to have Pulumi CLI installed and you are authenticated with DigitalOcean API (usually by setting the DIGITALOCEAN_TOKEN environment variable).

    import * as pulumi from '@pulumi/pulumi'; import * as digitalocean from '@pulumi/digitalocean'; import * as kubernetes from '@pulumi/kubernetes'; // Create a DigitalOcean Kubernetes cluster. const cluster = new digitalocean.KubernetesCluster("do-cluster", { region: "nyc1", version: "latest", nodePool: { size: "s-2vcpu-2gb", name: "default", nodeCount: 3, }, }); // Once the cluster is provisioned, its kubeconfig can be accessed as an output property. // The Pulumi Kubernetes provider uses this kubeconfig to connect and interact with the cluster. export const kubeconfig = cluster.kubeConfigs[0].rawConfig; // Create a Kubernetes provider instance that uses the kubeconfig from the newly created cluster. const k8sProvider = new kubernetes.Provider("k8s-provider", { kubeconfig: kubeconfig, }); // Deploy the FastAPI Helm chart to the DigitalOcean Kubernetes cluster using the Helm provider. const fastapiChart = new kubernetes.helm.v3.Chart("fastapi-chart", { repo: "your_helm_chart_repo", // Replace with the repository containing the FastAPI Helm chart chart: "fastapi", values: { // Customize Helm chart values here if needed }, }, { provider: k8sProvider }); // Export the Kubernetes cluster name and the FastAPI service endpoint. // Depending on the Helm chart, you might have to adjust the way you retrieve the endpoint. export const clusterName = cluster.name; export const serviceEndpoint = fastapiChart.getResourceProperty("v1/Service", "fastapi", "status").apply(status => status.loadBalancer.ingress[0].ip);

    Explanation:

    1. We start by importing the Pulumi SDK, along with the DigitalOcean and Kubernetes packages.
    2. We then declare a DigitalOcean Kubernetes cluster. The KubernetesCluster class is instantiated with necessary parameters like the region, version, and node pool configuration.
    3. Once we have the cluster, we use the kubeconfig output to set up the Kubernetes provider for Pulumi. This provider is what Pulumi uses to communicate with the Kubernetes API.
    4. With the provider set up, we define a Helm chart resource. Here you should replace your_helm_chart_repo with the actual Helm repository that hosts the FastAPI chart, and set any values for the Helm chart configuration depending on its requirements.
    5. Finally, we export the name of the cluster and the service endpoint where the FastAPI app can be accessed, which might need to be adjusted depending on how the FastAPI Helm chart exposes the service.

    Next Steps:

    • You would need to install Pulumi and set up the DigitalOcean credentials as mentioned previously.
    • Replace your_helm_chart_repo with the actual Helm chart repository.
    • Execute pulumi up to preview and deploy the resources. This will provision the cluster and deploy the FastAPI application.

    Please note that since we're dealing with cloud resources, provisioning and deployment might take a few minutes. Also, the exported service endpoint may not be immediately available as the load balancer takes time to provision.