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📌 1. Recap: Pod

• A Pod is the smallest deployable unit in Kubernetes.

• Pods wrap one or more containers.

• Pods are ephemeral:

  • If a Pod crashes, it won’t be recreated automatically.

  • This makes Pods unsuitable for production as-is.

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📌 2. What is a ReplicaSet?

• Ensures that a specified number of replicas of a Pod are running at all times.

• If a Pod fails or is deleted, the ReplicaSet creates a new one.

• Handles scaling (up/down replicas).

• But: ReplicaSet doesn’t support rolling updates.

3. Deployment

• A higher-level controller that manages ReplicaSets.

• Handles

  • Rolling updates (upgrade containers without downtime).

  • Rollbacks (go back to previous version).

  • Scaling (up/down easily).

• ✅ The most common way to run apps in Kubernetes. 👉 Think of ReplicaSet as: Pod + self-healing + scaling

🚀 Scaling and Rolling Updates in Kubernetes

📌 Scaling in Kubernetes

🔹 What is Scaling?

Scaling means increasing or decreasing the number of Pods in a Deployment or ReplicaSet.

• Horizontal Scaling → Increase or decrease the number of Pod replicas.

• Vertical Scaling → Adjust CPU/Memory resources of Pods (less common, requires pod restart).

Kubernetes makes scaling simple and allows both manual and automatic scaling.

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🔹 Manual Scaling with kubectl

Suppose you have a Deployment named nginx-deployment with 2 replicas.

• Check deployments:

kubectl get deployments

• Scale to 5 replicas:

kubectl scale deployment nginx-deployment --replicas=5

• Verify the pods:

kubectl get pods

• Scale back to 3 replicas:

kubectl scale deployment nginx-deployment --replicas=3

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🔹 Auto Scaling with HPA (Horizontal Pod Autoscaler)

Kubernetes can automatically scale Pods based on CPU or memory usage using Horizontal Pod Autoscaler (HPA). Enable autoscaling:

kubectl autoscale deployment nginx-deployment --min=2 --max=10 --cpu-percent=70

This configuration means:

• Minimum 2 Pods, maximum 10 Pods.

• If average CPU usage per Pod exceeds 70%, Kubernetes will add more Pods.

Check HPA:

kubectl get hpa

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🔄 Rolling Updates in Kubernetes

###🔹 What is a Rolling Update?

A Rolling Update gradually replaces old Pods with new ones without downtime.

• Old Pods are terminated after new Pods are running.

• Ensures the application remains available during the update.

• Default update strategy in Kubernetes is RollingUpdate.

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###🔹 Example: Deploy Nginx

Let’s say you deploy an Nginx app (v1.14):

apiVersion: apps/v1
kind: Deployment
metadata:
  name: nginx-deployment
spec:
  replicas: 3
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1.14.2
        ports:
        - containerPort: 80

Apply the deployment:

kubectl apply -f nginx-deployment.yaml

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🔹 Performing a Rolling Update Update the Nginx version:

kubectl set image deployment/nginx-deployment nginx=nginx:1.16.1

Check rollout progress:

kubectl rollout status deployment/nginx-deployment

Watch Pods update one by one:

kubectl get pods -w

🔹 Rollback if Something Goes Wrong Undo the update:

kubectl rollout undo deployment/nginx-deployment

Check history of rollouts:

kubectl rollout history deployment/nginx-deployment

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✅ Summary

• Scaling ensures your app can handle more/less traffic by changing Pod counts.

• Rolling Updates let you upgrade your app version with zero downtime.

• Kubernetes also supports rollback if something breaks.

• Together, these features make applications highly available and resilient.

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Ritesh Singh
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