Implementing global load balancing with GKE multi-cluster ingress

Question

Pulumi · Accepted Answer

Global load balancing with GKE (Google Kubernetes Engine) multi-cluster ingress allows you to route traffic to multiple Kubernetes clusters across different regions. This capability ensures high availability and disaster recovery. Traffic is intelligently routed to the closest cluster that has healthy instances of the required service. One of the key components to achieve this is Google Cloud's Multi-cluster Ingress (MCI), which is part of the GKE Hub and relies on the concept of multi-cluster services.

In this Pulumi TypeScript program, we'll set up multi-cluster ingress for two GKE clusters. Here are the key steps we will follow:

1. Define two GKE clusters in different regions.
2. Enable Multi-cluster Ingress on both clusters through GKE Hub (using the `Feature` resource).
3. Deploy an application to both clusters and expose it using a `Service`.
4. Create a `MultiClusterIngress` and `MultiClusterService` to globally load balance traffic between the clusters.

Note that the actual creation of clusters and applications might involve additional details that depend on your specific use case, which we'll not cover exhaustively here. This program assumes that you have two existing clusters you want to work with.

Before running this Pulumi program, ensure that you have set up Google Cloud credentials properly (such as via `gcloud` CLI or environment variables).

Let's start with the Pulumi TypeScript program:

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

// 1. Assuming we have two pre-configured GKE clusters managed by Pulumi
// You would normally have something like `const cluster1 = new gcp.container.Cluster(...);`
const cluster1Name = 'gke-cluster-1';
const cluster2Name = 'gke-cluster-2';

// 2. Enable Multi-cluster Ingress on both clusters through GKE Hub
const project = gcp.config.project;
const location = gcp.config.region;

// Enable the "multiclusteringress" feature on GKE Hub Feature
const mciFeature = new gcp.gkehub.Feature("multiclusteringress-feature", {
    location,
    project,
    featureId: "multiclusteringress",
    spec: {
        multiclusteringress: {
            configMembership: `/projects/${project}/locations/global/memberships/${cluster1Name}`, // Assuming cluster1 is the config cluster
        },
    },
});

// 3. Deploy an application to both clusters and expose it using a Kubernetes `Service` in each cluster.
// This step might involve the use of a K8s provider for each cluster and deploying resources using `k8s.yaml.ConfigFile` or other resource definitions.

// 4. Create a MultiClusterIngress and MultiClusterService to globally load balance traffic between the clusters.
// Usually, you need to switch context to each Kubernetes cluster and apply the relevant resources.
// The following resources would need to be applied to each cluster:
// MultiClusterIngress (MCI)
// MultiClusterService (MCS)

// Multi-cluster Ingress definition (as YAML or translated to Pulumi resources)
// const multiClusterIngress = new k8s.yaml.ConfigFile("mci", {
//     file: "multi-cluster-ingress.yaml" // File containing the MultiClusterIngress resource
// });
//
// Multi-cluster Service definition (as YAML or translated to Pulumi resources)
// const multiClusterService = new k8s.yaml.ConfigFile("mcs", {
//     file: "multi-cluster-service.yaml" // File containing the MultiClusterService resource
// });

// Note: Since multi-cluster resources management requires coordination between clusters,
// you'd typically use `kubectl` with config-management tools or a continuous delivery system
// that supports multi-cluster deployments (like Google Cloud Deploy or Spinnaker).

// The YAML files for `multi-cluster-ingress.yaml` and `multi-cluster-service.yaml`
// would define the services in each cluster and how they should be exposed via the global HTTP(S) load balancer.

// Expose any outputs if needed (e.g., cluster details, ingress IP addresses)
export const mciFeatureName = mciFeature.metadata.name;
```

In this program, we create a `Feature` to enable multi-cluster ingress for the specified clusters in GKE Hub. The `Feature` object allows you to configure various Google Kubernetes Engine capabilities on enrolled clusters in a centralized manner.

Remember to replace the placeholders like `cluster1Name`, `cluster2Name`, and filenames for `multi-cluster-ingress.yaml` and `multi-cluster-service.yaml` with your actual cluster names and resource file paths.

The provided code is a structural outline that needs specific cluster and application configuration to be fully functional. You'll need to apply your YAML files for the multi-cluster ingress and service resources via `kubectl` or your preferred CI/CD system.

The exact configurations within your YAML files will depend on your services and how you want to balance traffic between regions or clusters. This setup is for demonstration purposes showcasing infrastructure setup, and more complex microservices might require additional configuration.

Remember to check out and refer to the official [GCP Ingress for Anthos documentation](https://cloud.google.com/kubernetes-engine/docs/concepts/multi-cluster-ingress) for more detailed information on setting up multi-cluster ingress on GKE, and the [Pulumi GKE Hub Feature documentation](https://www.pulumi.com/registry/packages/gcp/api-docs/gkehub/feature/) for specific Pulumi resource options and configurations.