Deploy the frps helm chart on AWS EKS

Question

Pulumi · Accepted Answer

To deploy the FRPS (Fast Reverse Proxy Server) Helm chart on an AWS Elastic Kubernetes Service (EKS) cluster, we’ll go through the overall process step by step. Here's what we will cover:

1. **Setting up an EKS Cluster**: We’ll first define the required AWS resources to run an EKS cluster.
2. **Configuring the Kubernetes Provider**: Once the EKS cluster is setup, we’ll configure the Kubernetes provider to interact with our cluster.
3. **Deploying the Helm Chart**: Finally, we'll deploy the `frps` Helm chart to the EKS cluster using Pulumi's Helm Release resource.

Let's start by writing a Pulumi program in TypeScript to accomplish these tasks.

### Program Explanation
Firstly, we will need to set up the EKS cluster. For this, we will use the `eks.Cluster` resource from the Pulumi EKS package. This creates an EKS cluster and automatically sets up the required VPC, subnets, and other associated networking resources if not specified.

Secondly, we will create an instance of the `kubernetes.Provider` and pass the kubeconfig that we get from our newly created EKS cluster. This provider instance will be used to install the Helm chart into our cluster.

Lastly, we will use the `helm.v3.Chart` resource from Pulumi's Kubernetes package to deploy the FRPS Helm Chart. The helm chart can be added by providing the chart name and repository where the Helm chart is located.

### The Pulumi Program

```typescript
import * as pulumi from "@pulumi/pulumi";
import * as eks from "@pulumi/eks";
import * as k8s from "@pulumi/kubernetes";
import * as awsx from "@pulumi/awsx";

// Step 1: Create an EKS Cluster
const cluster = new eks.Cluster("frps-cluster", {
    instanceType: "t2.medium", // choose an appropriate instance type for your workload
    desiredCapacity: 2,        // specify the number of worker nodes
    minSize: 1,                // minimum number of worker nodes
    maxSize: 3,                // maximum number of worker nodes
    storageClasses: "gp2",     // use gp2 as the default storage class (general purpose SSD)
});

// Step 2: Configure Kubernetes Provider
const provider = new k8s.Provider("frps-k8s-provider", {
    kubeconfig: cluster.kubeconfig.apply(JSON.stringify), // use the kubeconfig from created EKS cluster
});

// Step 3: Deploy the FRPS Helm chart
const frpsChart = new k8s.helm.v3.Chart("frps", {
    chart: "frps",  // this is the chart name in the Helm repository
    version: "x.y.z", // replace with the specific version you want to deploy
    fetchOpts: {  // replace the repo URL with the actual location of the FRPS Helm chart
        repo: "https://your-helm-chart-repository",
    },
}, { provider: provider });

// Export the cluster's kubeconfig.
export const kubeconfig = cluster.kubeconfig;
```

This is a basic setup, and typically, you'd want to further configure your EKS cluster and Helm chart with more specific options suitable for your use case. The `desiredCapacity`, `minSize`, and `maxSize` are tunable parameters that define the scaling behavior of your worker nodes.

Regarding the FRPS helm chart, the `chart` and `version` parameters must be corresponding to the actual Helm chart you wish to deploy. Also, you should replace the `repo` attribute of `fetchOpts` with the actual URL of the Helm repository that hosts the FRPS chart. This URL depends on where the Helm chart for FRPS is located; usually, this is stored in a Helm repository, but it may also be in a public repository like Helm Hub or an artifact repository you control.

Remember, you'll need to have the Pulumi CLI installed and configured with your AWS credentials before running this program. Once you have this configured, you can run `pulumi up` to deploy the resources defined in the program.

The `kubeconfig` export at the end of the program will provide you with the necessary data to manage your Kubernetes cluster using `kubectl` or any other Kubernetes tool that requires this configuration.