Google Kubernetes Engine (GKE)

4

Google Kubernetes Engine (GKE) is a managed Kubernetes service provided by Google Cloud that allows you to deploy, manage, and scale containerized applications easily.

Instead of managing servers manually, GKE automatically manages:

• Cluster infrastructure

• Kubernetes control plane

• Node management

• Auto scaling

• Monitoring

Key Components of GKE

Component	Description
Cluster	Group of machines running Kubernetes
Node	VM instance running containers
Pod	Smallest deployable unit containing containers
Deployment	Manages application replicas
Service	Exposes application to network
Load Balancer	Distributes traffic across pods

---

Kubernetes Architecture Explained

Kubernetes Cluster Structure

4

Control Plane (Master)

Manages the cluster.

Main components:

• API Server – Entry point for commands

• Scheduler – Assigns pods to nodes

• Controller Manager – Maintains system state

Worker Nodes

Machines where containers run.

Node contains:

• Kubelet – Communicates with master

• Container Runtime – Runs containers

• Pods – Application containers

---

Lab Architecture

4

Workflow:

1️⃣ Create GKE Cluster
2️⃣ Deploy hello-app container
3️⃣ Create LoadBalancer service
4️⃣ Access via external IP

---

Lab Practical Steps (Command Line)

Step 1: Activate Cloud Shell

Open Cloud Shell in the Google Cloud Console.

Cloud Shell is a virtual machine with tools like:

• gcloud

• kubectl

• docker

---

Step 2: Set Default Region and Zone

gcloud config set compute/region us-east1

gcloud config set compute/zone us-east1-d

Explanation

• Region → geographical area

• Zone → data center location inside region

Example

us-east1 → Region

us-east1-d → Zone

---

Create a GKE Cluster

gcloud container clusters create --machine-type=e2-medium --zone=us-east1-d lab-cluster

Explanation

Parameter	Meaning
gcloud container clusters create	Create Kubernetes cluster
--machine-type=e2-medium	VM instance type
--zone	Cluster location
lab-cluster	Cluster name

Output Example

NAME: lab-cluster
LOCATION: us-east1-d
NODE VERSION: 1.22
NUM NODES: 3
STATUS: RUNNING

The cluster now contains:

• 1 Control plane

• 3 Worker nodes

---

Authenticate with the Cluster

gcloud container clusters get-credentials lab-cluster

Explanation

This command:

• Downloads cluster credentials

• Configures kubectl

• Allows communication with the cluster

Output example:

kubeconfig entry generated for lab-cluster

---

Deploy an Application

kubectl create deployment hello-server --image=gcr.io/google-samples/hello-app:1.0

Explanation

Part	Meaning
kubectl	Kubernetes CLI tool
create deployment	Create application deployment
hello-server	Deployment name
--image	Container image

Image used:

gcr.io/google-samples/hello-app:1.0

This creates:

• Deployment

• Pods

• Running containers

---

Expose the Application

kubectl expose deployment hello-server --type=LoadBalancer --port 8080

Explanation

Parameter	Meaning
expose	Creates service
--type=LoadBalancer	Creates external load balancer
--port 8080	Application port

---

View Service

kubectl get service

Example output:

NAME           TYPE           CLUSTER-IP     EXTERNAL-IP     PORT
hello-server   LoadBalancer   10.39.244.36   35.202.234.26   8080

Explanation

Field	Meaning
CLUSTER-IP	Internal IP
EXTERNAL-IP	Public IP
PORT	Application port

---

Access Application

Open browser:

http://EXTERNAL-IP:8080

Example:

http://35.202.234.26:8080

Output:

Hello World
Version 1.0
Hostname: hello-server

---

12. Delete the Cluster

gcloud container clusters delete lab-cluster

Confirm:

Y

Why Delete?

• Avoid resource usage

• Prevent cloud costs

• Clean environment

---

Important Kubernetes Commands (Exam Notes)

Command	Use
kubectl get pods	View running pods
kubectl get services	View services
kubectl get deployments	View deployments
kubectl describe pod	Detailed pod info
kubectl delete pod	Delete pod

---

Key Features of GKE

✔ Automatic scaling

✔ Load balancing

✔ Rolling updates

✔ Self-healing nodes

✔ Monitoring with Cloud Monitoring

✔ Automatic upgrades

---

Advantages of Using GKE

Feature	Benefit
Managed Kubernetes	No infrastructure management
Auto Scaling	Handles traffic automatically
High Availability	Reliable applications
Container Orchestration	Efficient container management

---

✅ Lab Summary

In this lab you learned:

1. How to create a Kubernetes cluster in GKE

2. How to deploy containerized applications

3. How to expose applications using services

4. How to access applications via external IP

5. How to delete the cluster