Kubernetes Autoscaling for OpsMate Platform

Pre-Lab Preparation

  • Amazon EKS Cluster is running

  • kubectl is configured

  • Metrics Server can be installed

  • OpsMate image exists in Amazon ECR

  • Worker nodes are in Ready state

Understanding Kubernetes Autoscaling

What is Horizontal Pod Autoscaler (HPA)?

HPA automatically changes the number of Pods based on resource usage.

Example:

Low Traffic

2 Pods Running

High Traffic

8 Pods Running

 

Traffic Reduced

2 Pods Running Again

Task 1: Verify Cluster Connectivity

Verify cluster

kubectl cluster-info

Verify nodes

kubectl get nodes

Check namespaces

kubectl get ns

Task 2: Create OpsMate Namespace

Create OpsMate Namespace

kubectl create namespace opsmate

Set default namespace

kubectl config set-context --current --namespace=opsmate

Verify

kubectl config view --minify | grep namespace

Task 3 : Install Metrics Server

Why Metrics Server?

Kubernetes Autoscaler requires CPU and memory metrics.

Metrics Server collects:

  • CPU usage

  • Memory usage

  • Pod resource metrics

Without Metrics Server, HPA will not work.

Install Metrics Server

kubectl apply -f https://github.com
/kubernetes-sigs/metrics-server/releases
/latest/download/components.yaml

Verify deployment

kubectl get deployment metrics-server -n kube-system

Verify Pods:

kubectl get pods -n kube-system

Task 4: Create OpsMate Deployment

Create deployment file:

nano deployment.yaml

Apply deployment

kubectl apply -f deployment.yaml

Verify

kubectl get deployments

Verify Pods

kubectl get pods

Task 5: Expose Application

Expose deployment

kubectl expose deployment opsmate-app \
--port=80 \
--type=LoadBalancer

Verify Service

kubectl get svc

Verify HPA

kubectl get hpa

Describe Autoscaler

kubectl describe hpa opsmate-app

Task 6: Generate Load for Autoscaling

Now we will simulate high traffic.

Create load generator Pod:

kubectl run load-generator \
--image=busybox \
-it --rm \
-- /bin/sh

Inside the container run:

while true; do wget -q -O- http://opsmate-app; done

This continuously sends requests to the application.

Keep this running for several minutes.

Open another terminal

Task 7: Monitor Autoscaling Behavior

Watch HPA activity

kubectl get hpa -w

You will notice:

TARGETS

70%

80%

95%

Task 8: Analyze Resource Optimization

Observe:

Situation

Pods

Normal Traffic

2

Heavy Traffic

Multiple

Low Traffic Again

Reduced

This demonstrates:

  • Efficient resource management

  • Better application availability

  • Reduced infrastructure cost

 

Great job!

  • Installed Metrics Server

  • Deployed OpsMate application

  • Configured Kubernetes resource requests and limits

  • Enabled Horizontal Pod Autoscaler

  • Generated application load

  • Monitored scaling behavior

  • Observed automatic scale-up and scale-down

  • Optimized Kubernetes resource utilization

Checkpoint

kubernate_lab_1

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