DEV Community

Prithiviraj R
Prithiviraj R

Posted on

EKS-node-viewer: See Your EKS Costs in Real-Time (No Dashboard Needed)

#aws #eks #finops

🔥 Meet eks-node-viewer

A tiny CLI tool from AWS Labs. Built originally for Karpenter demos. Now open source. And honestly, underrated.

One command:

eks-node-viewer --resources cpu,memory
Enter fullscreen mode Exit fullscreen mode

You instantly see:

  • Every node in your cluster
  • CPU + Memory usage (based on pod requests)
  • Instance type (t3.medium, c6a.2xlarge...)
  • On-Demand vs Spot
  • Cost per hour AND per month
  • Pods per node

Real-time. In your terminal. No dashboard hopping. No Grafana. No console tab-switching.

🎯 When I Use It

I use eks-node-viewer when:

  • ✅ Debugging uneven pod scheduling across nodes
  • ✅ Checking if Karpenter consolidation is actually working
  • ✅ Quick cost sanity check before a prod deploy
  • ✅ Spotting nodes that are packed too tight (or wasting capacity)
  • ✅ Answering "why is my bill so high?" in 30 seconds

If you run multiple clusters (or even one busy prod cluster), this is a ridiculously fast way to understand what's happening.

🚀 Let's Build a Demo

I'll show you exactly how to use eks-node-viewer with a real EKS cluster.

What we'll do:

  1. Create an EKS cluster (1 node)
  2. Install eks-node-viewer
  3. Deploy workloads
  4. Watch costs in real-time
  5. See Karpenter-style scaling (optional)

Step 1: Create EKS Cluster

First, we need an EKS cluster. I'm using eksctl because it's the fastest way.

Create Cluster Config 

cat > eks-node-viewer-cluster.yaml << 'EOF'
apiVersion: eksctl.io/v1alpha5
kind: ClusterConfig

metadata:
  name: eks-node-viewer-demo
  region: us-east-1
  version: "1.31"

managedNodeGroups:
  - name: demo-nodes
    instanceType: t3.medium
    minSize: 1
    maxSize: 1
    desiredCapacity: 1
    volumeSize: 20
    labels:
      role: demo
    tags:
      Environment: demo
      Tool: eks-node-viewer
EOF
Enter fullscreen mode Exit fullscreen mode

Create the Cluster 

eksctl create cluster -f eks-node-viewer-cluster.yaml
Enter fullscreen mode Exit fullscreen mode

While it's creating, let's install eks-node-viewer.

Step 2: Install eks-node-viewer

Option 1: Using Go (Recommended) 

go install github.com/awslabs/eks-node-viewer/cmd/eks-node-viewer@latest
Enter fullscreen mode Exit fullscreen mode

Option 2: Using Homebrew (Mac) 

brew tap aws/tap
brew install eks-node-viewer
Enter fullscreen mode Exit fullscreen mode

Option 3: Download Binary 

# Download latest release
curl -LO https://github.com/awslabs/eks-node-viewer/releases/latest/download/eks-node-viewer_$(uname -s)_$(uname -m).tar.gz

# Extract
tar -xzf eks-node-viewer_*.tar.gz

# Move to PATH
sudo mv eks-node-viewer /usr/local/bin/
sudo chmod +x /usr/local/bin/eks-node-viewer
Enter fullscreen mode Exit fullscreen mode

Verify Installation 

eks-node-viewer --version
# Output: eks-node-viewer version v0.7.4
Enter fullscreen mode Exit fullscreen mode

Step 3: Connect to Cluster

Once your cluster is ready, update your kubeconfig:

# List clusters
aws eks list-clusters --region us-east-1

# Update kubeconfig
aws eks update-kubeconfig --name eks-node-viewer-demo --region us-east-1

# Verify connection
kubectl get nodes
Enter fullscreen mode Exit fullscreen mode

Output:

NAME                             STATUS   ROLES    AGE   VERSION
ip-192-168-13-156.ec2.internal   Ready    <none>   2m    v1.31.14-eks-70ce843
Enter fullscreen mode Exit fullscreen mode

✅ Cluster is ready!

Step 4: Run eks-node-viewer (Baseline)

Now for the magic. Run eks-node-viewer:

# Set AWS region (important!)
export AWS_REGION=us-east-1

# Run eks-node-viewer
eks-node-viewer --resources cpu,memory
Enter fullscreen mode Exit fullscreen mode

What you'll see:

1 nodes (550m/1930m) 28.5% cpu    ███████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ $0.042/hour | $30.368/month
        540Mi/3376720Ki  16.4% memory ███████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
6 pods (0 pending 6 running 6 bound)
Enter fullscreen mode Exit fullscreen mode

Let's break this down:

  • 1 nodes - You have 1 node (t3.medium)
  • 550m/1930m - Using 550 millicores out of 1930m available (28.5%)
  • 540Mi/3376720Ki - Using 540MB out of 3.3GB RAM (16.4%)
  • $0.042/hour | $30.368/month - This is costing you $30/month
  • 6 pods - System pods (coredns, kube-proxy, aws-node, metrics-server)

📸 Screenshot this! This is your baseline.

Step 5: Deploy Nginx (Watch Costs Update)

Keep eks-node-viewer running in Terminal 1.

Open a NEW terminal (Terminal 2) and deploy nginx:

# Set region
export AWS_REGION=us-east-1

# Deploy nginx with 5 replicas
kubectl create deployment nginx --image=nginx --replicas=5

# Check deployment
kubectl get deployments
kubectl get pods
Enter fullscreen mode Exit fullscreen mode

Output:

NAME    READY   UP-TO-DATE   AVAILABLE   AGE
nginx   5/5     5            5           30s
Enter fullscreen mode Exit fullscreen mode

Switch back to Terminal 1 (eks-node-viewer).

You'll see it update in real-time:

1 nodes (750m/1930m) 38.9% cpu    ████████████████░░░░░░░░░░░░░░░░░░░░░░░░ $0.042/hour | $30.368/month
        840Mi/3376720Ki  25.5% memory ███████████░░░░░░░░░░░░░░░░░░░░░░░░░░░
11 pods (0 pending 11 running 11 bound)
Enter fullscreen mode Exit fullscreen mode

What changed:

  • CPU usage: 28.5% → 38.9%
  • Memory usage: 16.4% → 25.5%
  • Pods: 6 → 11 (added 5 nginx pods)
  • Cost: Still $30/month (same node)

📸 Screenshot this!

Step 6: Deploy CPU-Intensive App

Let's stress the CPU and watch it happen live:

# Deploy stress test (Terminal 2)
kubectl create deployment stress --image=polinux/stress \
  --replicas=3 -- stress --cpu 1 --timeout 3600s

# Check pods
kubectl get pods | grep stress
Enter fullscreen mode Exit fullscreen mode

In eks-node-viewer (Terminal 1):

1 nodes (1550m/1930m) 80.3% cpu   ████████████████████████████████░░░░░░░░ $0.042/hour | $30.368/month
        1140Mi/3376720Ki  34.6% memory ██████████████░░░░░░░░░░░░░░░░░░░░░░░░
14 pods (0 pending 14 running 14 bound)
Enter fullscreen mode Exit fullscreen mode

What changed:

  • CPU usage: 38.9% → 80.3% 🔥
  • Memory usage: 25.5% → 34.6%
  • Pods: 11 → 14 (added 3 stress pods)
  • Cost: Still $30/month (same node, but now heavily utilized)

📸 Screenshot this!

This is the key insight: You can see your node is now 80% utilized. If you add more workloads, you'll need another node (and another $30/month).

Step 7: Scale Up (Watch Node Get Packed)

Let's push it further:

# Scale nginx to 20 replicas (Terminal 2)
kubectl scale deployment nginx --replicas=20

# Watch pods
kubectl get pods | grep nginx | wc -l
Enter fullscreen mode Exit fullscreen mode

In eks-node-viewer:

1 nodes (1850m/1930m) 95.9% cpu   ████████████████████████████████████████ $0.042/hour | $30.368/month
        1640Mi/3376720Ki  49.8% memory ████████████████████░░░░░░░░░░░░░░░░░░
29 pods (0 pending 29 running 29 bound)
Enter fullscreen mode Exit fullscreen mode

What changed:

  • CPU usage: 80.3% → 95.9% 🚨
  • Memory usage: 34.6% → 49.8%
  • Pods: 14 → 29 (added 15 more nginx pods)
  • Node is almost maxed out!

📸 Screenshot this!

Real-world insight: If you were using Karpenter, it would see this 95% CPU usage and provision a new node. You'd see a second line appear in eks-node-viewer with another $30/month cost.

Step 8: Check Pod Distribution

In eks-node-viewer, you can see exactly how pods are distributed:

# Run with pods resource
eks-node-viewer --resources cpu,memory,pods
Enter fullscreen mode Exit fullscreen mode

Output:

1 nodes (1850m/1930m) 95.9% cpu    ████████████████████████████████████████ $0.042/hour | $30.368/month
        1640Mi/3376720Ki  49.8% memory ████████████████████░░░░░░░░░░░░░░░░░░
        29/110 pods       26.4% pods   ███████████░░░░░░░░░░░░░░░░░░░░░░░░░░░
29 pods (0 pending 29 running 29 bound)
Enter fullscreen mode Exit fullscreen mode

New info:

  • 29/110 pods - You have 29 pods running, max capacity is 110 pods per node
  • 26.4% pods - You're using 26% of pod capacity

This is useful for understanding if you're hitting pod limits (which can happen before CPU/memory limits).

📸 Screenshot this!

Step 9: Cleanup (Watch Resources Free Up)

Let's clean up and watch the resources free up in real-time:

# Delete deployments (Terminal 2)
kubectl delete deployment nginx stress

# Watch pods terminating
kubectl get pods
Enter fullscreen mode Exit fullscreen mode

In eks-node-viewer:

1 nodes (550m/1930m) 28.5% cpu    ███████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░ $0.042/hour | $30.368/month
        540Mi/3376720Ki  16.4% memory ███████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
6 pods (0 pending 6 running 6 bound)
Enter fullscreen mode Exit fullscreen mode

Back to baseline!

  • CPU: 95.9% → 28.5%
  • Memory: 49.8% → 16.4%
  • Pods: 29 → 6
  • Cost: Still $30/month (node still exists)

📸 Screenshot this!

🎯 Real-World Use Cases

Use Case 1: "Why is my bill so high?"

Before eks-node-viewer:

  1. Open AWS Console
  2. Go to EC2 → Instances
  3. Filter by cluster
  4. Manually check instance types
  5. Look up pricing
  6. Calculate total
  7. Check utilization in Grafana
  8. Realize you have 10 nodes at 20% utilization 😱

With eks-node-viewer:

eks-node-viewer --resources cpu,memory
Enter fullscreen mode Exit fullscreen mode

Output:

10 nodes (2000m/19300m) 10.4% cpu   ████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ $0.416/hour | $303.68/month
         5400Mi/33767200Ki 16.4% memory ███████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
60 pods (0 pending 60 running 60 bound)
Enter fullscreen mode Exit fullscreen mode

Instant insight: You're paying $303/month for 10 nodes that are only 10% utilized. You could consolidate to 2-3 nodes and save $200/month.

Time saved: 15 minutes → 30 seconds

Use Case 2: "Pods are pending"

Scenario: You deploy a new app and pods are stuck in Pending state.

kubectl get pods
# NAME                    READY   STATUS    RESTARTS   AGE
# my-app-7d8f9c5b-xk2lp   0/1     Pending   0          2m
Enter fullscreen mode Exit fullscreen mode

Check eks-node-viewer:

3 nodes (5700m/5790m) 98.4% cpu   ████████████████████████████████████████ $0.126/hour | $91.10/month
        11200Mi/10130160Ki 113.2% memory ████████████████████████████████████████
85 pods (5 pending 80 running 80 bound)
Enter fullscreen mode Exit fullscreen mode

Instant insight: Nodes are at 98% CPU and 113% memory (overcommitted). You need more nodes.

Solution: Scale up or let Karpenter add nodes.

Use Case 3: "Is Karpenter working?"

Scenario: You installed Karpenter but you're not sure if it's actually consolidating nodes.

Terminal 1: Run eks-node-viewer

eks-node-viewer --resources cpu,memory
Enter fullscreen mode Exit fullscreen mode

Terminal 2: Scale down workload

kubectl scale deployment my-app --replicas=2
Enter fullscreen mode Exit fullscreen mode

Watch eks-node-viewer:

  • After 30 seconds (Karpenter's default consolidation delay)
  • You should see nodes disappear
  • Cost should decrease

If nodes DON'T disappear: Karpenter isn't working. Check your NodePool configuration.

Use Case 4: "On-Demand vs Spot Cost Comparison"

Filter by capacity type:

# Show only On-Demand nodes
eks-node-viewer --node-selector karpenter.sh/capacity-type=on-demand

# Show only Spot nodes
eks-node-viewer --node-selector karpenter.sh/capacity-type=spot
Enter fullscreen mode Exit fullscreen mode

Example output:

On-Demand:

5 nodes (5000m/9650m) 51.8% cpu   ████████████████████░░░░░░░░░░░░░░░░░░░ $0.208/hour | $151.84/month
Enter fullscreen mode Exit fullscreen mode

Spot:

5 nodes (5000m/9650m) 51.8% cpu   ████████████████████░░░░░░░░░░░░░░░░░░ $0.062/hour | $45.26/month
Enter fullscreen mode Exit fullscreen mode

Instant insight: Same workload, same utilization, but Spot is 70% cheaper ($151 vs $45).

🧹 Cleanup

When you're done with the demo:

# Delete deployments
kubectl delete deployment nginx stress

# Delete cluster
eksctl delete cluster --name eks-node-viewer-demo --region us-east-1

# Verify deletion
aws eks list-clusters --region us-east-1
Enter fullscreen mode Exit fullscreen mode

🎯 Key Takeaways

What eks-node-viewer Shows You

✅ Real-time cost - Per hour and per month

✅ Instance types - t3.medium, c6a.2xlarge, etc.

✅ Capacity type - On-Demand vs Spot

✅ Resource usage - CPU, Memory, Pods

✅ Utilization bars - Visual representation

✅ Pod distribution - How many pods per node

When to Use It

✅ Cost visibility - Quick cost checks

✅ Capacity planning - Before deploying new apps

✅ Debugging - Why are pods pending?

✅ Karpenter monitoring - Is consolidation working?

✅ Optimization - Finding underutilized nodes

Why It's Better Than Alternatives

✅ No setup - Just install and run

✅ No dashboard - Works in terminal

✅ Real-time - Updates as things change

✅ Cost-aware - Shows pricing automatically

✅ Fast - Answer questions in seconds

🚀 Try It Yourself

5-minute quick start:

# 1. Install
go install github.com/awslabs/eks-node-viewer/cmd/eks-node-viewer@latest

# 2. Set region
export AWS_REGION=us-east-1

# 3. Run
eks-node-viewer --resources cpu,memory

# 4. Deploy something
kubectl create deployment nginx --image=nginx --replicas=10

# 5. Watch it update!
Enter fullscreen mode Exit fullscreen mode

That's it. You'll get it immediately.

📚 Resources

💬 Final Thoughts

eks-node-viewer is one of those tools that seems simple but becomes indispensable once you start using it.

Before: Checking costs meant opening 5 tabs, clicking through dashboards, and doing mental math.

After: One command. Instant visibility. Make decisions in seconds.

If you run EKS (especially with Karpenter), try this once. You'll understand why it's underrated.

Have you used eks-node-viewer? What's your favorite use case? Let me know in the comments! 👇

AWS #EKS #Kubernetes #Karpenter #DevOps #CloudCost #CostOptimization #eks-node-viewer

Happy Learning
Prithiviraj Rengarajan
DevOps Engineer

Top comments (0)