Deploy the provider-aws helm chart on Google Kubernetes Engine (GKE)

Question

Pulumi · Accepted Answer

To deploy the AWS Load Balancer Controller Helm chart on a Google Kubernetes Engine (GKE) cluster using Pulumi, you'll follow these steps:

1. Set up a GKE cluster.
2. Configure kubectl to connect to the GKE cluster.
3. Add the AWS Load Balancer Controller Helm chart repository.
4. Deploy the AWS Load Balancer Controller Helm chart to the GKE cluster.

We'll use the `@pulumi/gcp` and `@pulumi/kubernetes` packages to create GKE cluster resources and deploy Helm charts, respectively.

Before you start, you must have Pulumi installed and configured with Google Cloud credentials. Also, ensure that Helm is installed if you need to add repositories or package charts locally.

Here's a detailed TypeScript program that performs the steps:

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

// Create a GKE cluster
const cluster = new gcp.container.Cluster("aws-load-balancer-controller-cluster", {
    initialNodeCount: 2,
    minMasterVersion: "latest",
    nodeVersion: "latest",
    nodeConfig: {
        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 and Kubeconfig
export const clusterName = cluster.name;
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 referencing the kubeconfig
const k8sProvider = new k8s.Provider("k8s-provider", {
    kubeconfig: kubeconfig,
});

// Add the AWS Load Balancer Controller Helm chart repository
const awsLoadBalancerRepoName = "aws-load-balancer-controller";
const awsLoadBalancerRepoUrl = "https://aws.github.io/eks-charts";

const awsLoadBalancerRepo = new k8s.helm.v3.Repository("awsLoadBalancerRepo", {
    name: awsLoadBalancerRepoName,
    url: awsLoadBalancerRepoUrl,
}, { provider: k8sProvider });

// Deploy the AWS Load Balancer Controller Helm chart
const awsLoadBalancerChartName = "aws-load-balancer-controller";
const awsLoadBalancerReleaseName = "aws-load-balancer-controller-release";
const awsLoadBalancerNamespace = "kube-system";

const awsLoadBalancerChart = new k8s.helm.v3.Chart(awsLoadBalancerReleaseName, {
    chart: awsLoadBalancerChartName,
    version: "1.4.0", // Specify the version of the chart to deploy
    namespace: awsLoadBalancerNamespace,
    repositoryOpts: {
        repo: awsLoadBalancerRepo.name,
    },
    // Values for the Helm chart
    values: {
        clusterName: cluster.name,
        // Set the important values for your AWS Load Balancer Controller instance
        // Make sure to include the required AWS related configurations:
        // - AWS region
        // - AWS credentials secret reference, if not using IRSA or EC2 instance role.
        // ... add required values here.
    },
}, { provider: k8sProvider });

// Export the Helm chart deployment status
export const awsLoadBalancerChartStatus = awsLoadBalancerChart.status;
```

This program does the following:
- Sets up a new GKE cluster with the required node count and machine types.
- Generates a kubeconfig file that will allow us to interact with the cluster using `kubectl`.
- Creates a Kubernetes provider instance that uses the created kubeconfig.
- Adds the AWS Load Balancer Controller Helm repository.
- Deploys the AWS Load Balancer Controller Helm chart to the GKE cluster. You will need to specify the chart version and any other values that are necessary for the chart to function properly.

Keep in mind that this program assumes you are granting the AWS Load Balancer Controller the required permissions on AWS. This typically involves setting up an IAM role and attaching the appropriate policies. Also, you may need to set up an Identity Provider (IdP) in your cluster for IAM roles for service accounts (IRSA