Scaling applications based on resource usage with Nomad

Question

Pulumi · Accepted Answer

Scaling applications based on resource usage within a Nomad cluster typically involves adjusting the number of instances of a given service or job in response to the current demand or load. Nomad provides built-in support for scaling with its Autoscaler feature.

To demonstrate this concept using Pulumi, we would typically integrate with the cloud provider's services where the Nomad cluster is hosted. For instance, AWS Auto Scaling Groups or Kubernetes Horizontal Pod Autoscalers might be used to automatically increase or decrease the number of Nomad clients based on CPU or memory consumption. However, since the Pulumi Registry Results do not show a direct Nomad integration, I will guide you through setting up a scalable Kubernetes cluster, which is a common environment where Nomad could be deployed.

Below, I will outline the steps using Pulumi to set up a Kubernetes cluster with autoscaling features enabled. This program will:

1. Create a Kubernetes cluster.
2. Enable the Kubernetes cluster autoscaler.
3. Deploy a sample application.
4. Define a Horizontal Pod Autoscaler (HPA) to scale the application based on CPU usage.

Pulumi enables you to define your infrastructure using real programming languages, providing the benefits of loops, functions, and real programming languages error-checking.

Here is a Pulumi program written in TypeScript:

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

// Create a Kubernetes cluster.
const cluster = new aws.eks.Cluster("my-cluster", {
    instanceType: "t2.medium",
    desiredCapacity: 2,
    minSize: 1,
    maxSize: 4,
    deployDashboard: false,
});

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

// Create a Kubernetes provider instance using the cluster's kubeconfig.
const provider = new k8s.Provider("provider", {
    kubeconfig: cluster.kubeconfig,
});

// Create a namespace for the application.
const ns = new k8s.core.v1.Namespace("app-ns", {}, { provider: provider });

// Deploy a sample application.
const appLabels = { app: "my-app" };
const deployment = new k8s.apps.v1.Deployment("app-deployment", {
    metadata: { namespace: ns.metadata.name },
    spec: {
        selector: { matchLabels: appLabels },
        replicas: 1,
        template: {
            metadata: { labels: appLabels },
            spec: {
                containers: [{
                    name: "app",
                    image: "nginx", // Just for demonstration; replace with your own application.
                    ports: [{ containerPort: 80 }],
                    resources: {
                        requests: {
                            cpu: "100m",
                            memory: "200Mi",
                        },
                        limits: {
                            cpu: "500m",
                            memory: "500Mi",
                        },
                    },
                }],
            },
        },
    },
}, { provider: provider });

// Define a Horizontal Pod Autoscaler to scale the application.
const appHpa = new k8s.autoscaling.v1.HorizontalPodAutoscaler("app-hpa", {
    metadata: { namespace: ns.metadata.name },
    spec: {
        scaleTargetRef: {
            apiVersion: "apps/v1",
            kind: "Deployment",
            name: deployment.metadata.name,
        },
        minReplicas: 1,
        maxReplicas: 10,
        targetCPUUtilizationPercentage: 50,
    },
}, { provider: provider });

// Export the name of the namespace
export const namespaceName = ns.metadata.name;

```

This program does the following:

- Imports the necessary Pulumi libraries for Kubernetes and AWS.
- Creates an Amazon EKS cluster with autoscaling enabled.
- Creates a Kubernetes provider that is configured to communicate with the created cluster.
- Defines a namespace where the application will reside.
- Deploys a sample Nginx application and sets the desired CPU and memory for request and limits.
- Finally, it creates an HPA resource targeting the deployed application, with rules to scale between 1 and 10 replicas based on CPU utilization hitting a 50% threshold.

Remember that you would need the Pulumi CLI installed and configured with appropriate cloud provider credentials (AWS in this case) to run this program successfully. To deploy the above program, you would execute `pulumi up` within the directory containing this code.

Keep in mind that this example only demonstrates scaling an application in Kubernetes, not in a Nomad cluster specifically. If you were using Nomad, you could potentially manage the cloud environment with Pulumi and use Nomad's native scaling mechanisms for job scaling within that environment. However, integrating Nomad's scaling capabilities would require additional configuration and potential custom scripting, as Pulumi does not have a direct integration for Nomad's autoscaling as of my knowledge cutoff in early 2023.