Using kubernetes autoscaling with gateway.networking.k8s.io

Question

Pulumi · Accepted Answer

Autoscaling in Kubernetes is a mechanism that automatically adjusts the number of running Pods in a Deployment, ReplicaSet, or StatefulSet based on the current load. Autoscaling can be an efficient way to handle changes in traffic and load on your services. In the context of Kubernetes, autoscaling is typically achieved through the Horizontal Pod Autoscaler (HPA) resource, which scales the number of Pod replicas based on observed metrics such as CPU utilization or custom metrics provided by third-party services.

In Kubernetes, `gateway.networking.k8s.io` is not an autoscaler resource but part of the Gateway API, a set of resources intended for service networking in a Kubernetes cluster. The Gateway API provides more advanced and extensible routing capabilities than the standard Ingress API. It is composed of several resources, amongst which the Gateway resource is central and enables the management of HTTP/TCP traffic for applications.

To combine autoscaling with using `gateway.networking.k8s.io`, we would typically deploy an HPA resource that targets the workload (e.g., a Deployment) of the service we're exposing via a Gateway resource. The Gateway would manage ingress traffic to the service, and the HPA would manage the scaling of service replicas to accommodate the traffic load.

Here's a Pulumi TypeScript program that sets up a basic autoscaling scenario with a Gateway in a Kubernetes cluster. For brevity, the program assumes you have a Deployment already and we will be defining an HPA to autoscale it, and a Gateway resource to manage ingress traffic.

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

// Placeholder for your existing Deployment name and namespace
const deploymentName = "my-deployment";
const namespace = "default";

// Define an HorizontalPodAutoscaler that targets the Deployment
const hpa = new k8s.autoscaling.v2.HorizontalPodAutoscaler("my-hpa", {
    metadata: {
        namespace: namespace,
    },
    spec: {
        scaleTargetRef: {
            apiVersion: "apps/v1",
            kind: "Deployment",
            name: deploymentName,
        },
        minReplicas: 1,
        maxReplicas: 10,
        // For the sake of this example, we pretend to scale based on CPU usage crossing 50%.
        // In a real-world scenario, this could be any metric of interest.
        metrics: [{
            type: "Resource",
            resource: {
                name: "cpu",
                target: {
                    type: "Utilization",
                    averageUtilization: 50,
                },
            },
        }],
    },
}, { provider: /* assume a provider is already configured */ });

// Define a Gateway resource that configures Layer-7 load balancing
const gateway = new k8s.networking.v1beta1.Gateway("my-gateway", {
    metadata: {
        namespace: namespace,
        // Additional metadata here...
    },
    spec: {
        // Gateway specifications would be placed here, such as listener details,
        // but for this example, we'll keep it simple and without concrete implementation details.
        // ...
    },
}, { provider: /* assume a provider is already configured */ });

// Export the name of the HPA and Gateway so that their status can be observed
export const hpaName = hpa.metadata.name;
export const gatewayName = gateway.metadata.name;
```

To explain what's happening here:

- We import the Kubernetes package from Pulumi's SDK to create resources within a Kubernetes cluster.
- We declare an `HorizontalPodAutoscaler` resource targeting a hypothetical Deployment named `my-deployment`. The HPA is configured to scale between 1 to 10 replicas based on CPUs' average utilization exceeding 50%.
- We create a placeholder `Gateway` resource. In a real-world scenario, this would include detailed configurations for routing, such as setting up listeners and rules for routing traffic to backend services.
- Finally, we export the HPA and Gateway names allowing you to reference these resources' statuses outside of Pulumi.

Remember, the above program is a template and requires a valid, running Kubernetes cluster managed by Pulumi and may need to be adjusted to fit specific use cases or cluster configurations. The HPA and Gateway definitions should be expanded with proper selectors, labels, and specifications to meet the actual routing and scaling requirements of your application.