How to Increase Node.js Memory Allocation in an EKS Cluster?

[Lalit_Waghulkar]

Hello 24x7,

I have an EKS cluster where I'm running a Node.js application in the pods. I've encountered an issue where the Node.js application crashes when its memory usage exceeds 512MB. Although I have increased the memory limits for the pods, I need guidance on how to increase the memory allocation for the Node.js application itself.

Here's what I've done so far:

• Increased the pod memory limits and requests in the Kubernetes deployment YAML file.
• Ensured the cluster nodes have sufficient memory to handle the increased allocation.

However, the Node.js application still crashes once it hits the 512MB memory usage mark. I understand this might be due to the default memory allocation limit set by Node.js.

Could you please provide detailed steps on how to increase the memory limit for the Node.js application within the Kubernetes environment? Any specific configurations or parameters that need to be adjusted would be greatly appreciated. Additionally, please advise on any best practices to ensure the application runs smoothly with the increased memory allocation.

[Administrator]

To increase Node.js memory allocation in an Amazon EKS (Elastic Kubernetes Service) cluster, you'll need to adjust the memory limits of the Kubernetes Pod running the Node.js application. Here’s a step-by-step guide to achieve this:

Step 1: Modify Node.js Memory Allocation

1. Update Node.js Startup Script:
Adjust the `--max-old-space-size` parameter to allocate more memory to the Node.js process. You can do this by updating the start script in your `package.json` or in the command you use to start your Node.js application.

json
"scripts": {
"start": "node --max-old-space-size=4096 index.js"
}

This example allocates 4 GB of memory to the Node.js process.

Step 2: Update Kubernetes Deployment

1. Edit Deployment YAML:
Update the Kubernetes Deployment configuration to request and limit more memory. Open your deployment YAML file and modify the `resources` section:

yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: your-deployment-name
spec:
  replicas: 1
  selector:
    matchLabels:
      app: your-app-label
  template:
    metadata:
      labels:
       app: your-app-label
    spec:
      containers:
      -   name: your-container-name
          image: your-image
          resources:
            requests:
             memory: "4Gi"
            limits:
             memory: "4Gi"
         env:
         -  name: NODE_OPTIONS
            value: "--max-old-space-size=4096"
         ports:
         -  containerPort: 3000

This example sets both the memory request and limit to 4 GB. The `NODE_OPTIONS` environment variable is used to pass the `--max-old-space-size` flag to the Node.js process.

Step 3: Apply the Changes

1. Apply the updated YAML:
Use `kubectl` to apply the changes to your cluster.

kubectl apply -f your-deployment-file.yaml

```

Step 4: Verify the Changes

1. Check the Pod Status:
Verify that the Pod is running with the updated memory allocation.

kubectl get pods

2. Describe the Pod:
Check the detailed configuration of the running Pod to ensure the memory limits are correctly applied.

kubectl describe pod your-pod-name

3. Monitor Resource Usage:
You can monitor the resource usage of your Pod to ensure it's utilizing the allocated memory appropriately.

kubectl top pod your-pod-name

Additional Considerations

Horizontal Pod Autoscaling:
If your application requires scaling based on resource usage, consider setting up Horizontal Pod Autoscaling (HPA) to automatically adjust the number of Pods based on memory usage.

- Cluster Node Capacity:
Ensure that your EKS cluster nodes have sufficient memory to accommodate the increased memory requests from your Pods. You might need to scale up your nodes or choose instances with more memory.

By following these steps, you can increase the memory allocation for your Node.js application running in an EKS cluster, ensuring it has the necessary resources for optimal performance.

[Lalit_Waghulkar]

Thank you for the detailed steps.