Google Kubernetes Engine (GKE) Tutorial: Cluster Creation, Connection & Deployment (Console & CLI)

Introduction

Google Kubernetes Engine (GKE) is a managed Kubernetes service by Google Cloud that simplifies deploying, managing, and scaling containerized applications. In this blog, we’ll cover:

• How to create a GKE cluster via the Console and CLI
• How to connect to your cluster
• How to deploy a sample application using kubectl

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Prerequisites

• A Google Cloud project with billing enabled
• IAM role: Kubernetes Engine Admin or Owner
• Cloud SDK installed for CLI-based steps

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Part 1: Creating a GKE Cluster using Google Cloud Console

1: Open GCP Console

Navigate to console.cloud.google.com, then go to:
Kubernetes Engine > Clusters > Create

2: Configure Cluster

• Cluster name: cluster-by-console
• Location type: Regional or zonal (e.g., us-central1)
• Machine type: e2-medium
• Number of nodes: e.g., 3
• Use default network and subnetwork
• Leave other settings as default or customize as needed

Click Create, and wait a few minutes for the cluster to be provisioned.

Part 2: Connecting to the GKE Cluster

After your cluster is ready, connect to it with:

gcloud container clusters get-credentials CLUSTER_NAME \
  --region us-central1 \
  --project YOUR_PROJECT_ID

Verify connection:

kubectl get all

Part 3: Creating a GKE Cluster using gcloud CLI

1: Authenticate and Set Project

gcloud auth activate-service-account --key-file=KEY_FILE_NAME
gcloud config set project YOUR_PROJECT_ID

2: Create Cluster

gcloud container clusters create cluster-by-cli \
  --region us-central1 \
  --num-nodes 3 \
  --machine-type e2-medium \
  --disk-type=pd-standard \
  --disk-size=100 \
  --release-channel regular \
  --enable-autoupgrade \
  --enable-ip-alias \
  --network default \
  --subnetwork default \
  --scopes=https://www.googleapis.com/auth/cloud-platform \
  --logging=SYSTEM,WORKLOAD \
  --monitoring=SYSTEM \
  --service-account=YOUR_SERVICE_ACCOUNT \
  --project YOUR_PROJECT_ID

Replace YOUR_SERVICE_ACCOUNT and YOUR_PROJECT_ID accordingly.

Part 4: Deploying an Application to GKE

1: Create a Deployment YAML (e.g., Flask app or Nginx)

Deployment.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: flask-hello
spec:
  replicas: 1
  selector:
    matchLabels:
      app: flask-hello
  template:
    metadata:
      labels:
        app: flask-hello
    spec:
      containers:
      - name: flask-container
        image: <your-dockerhub-username>/flask-hello:latest
        ports:
        - containerPort: 8080

Replace with your actual Docker image.

2: Apply the Deployment

kubectl apply -f Deployment.yaml

3: Expose the Deployment as a Service

kubectl expose deployment flask-hello --type=ClusterIP --port=80 --target-port=8080

4: Access the App via Port Forwarding

kubectl get pods  # find pod name
kubectl port-forward pod/<pod-name> 8080:8080

Then open your browser at http://localhost:8080

Part 5: Deleting the Cluster (when you’re done)

gcloud container clusters delete cluster-by-cli \
  --region us-central1 \
  --project YOUR_PROJECT_ID

Conclusion

In this tutorial, we explored how to:

• Create a GKE cluster using the Console and CLI
• Connect to it via kubectl
• Deploy and expose a sample application

GKE makes Kubernetes simpler by managing your control plane, scaling, and upgrades automatically. Whether you’re deploying from the Console or automating via CLI, GKE is a powerful tool for production-ready Kubernetes.