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Latchu@DevOps
Latchu@DevOps

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Part-120: 🚀Build, Push, and Deploy a Docker Image to Google Artifact Registry on Google Kubernetes Engine

#kubernetes #devops #docker #googlecloud

In this tutorial, we’ll walk through the complete workflow of building a Docker image, pushing it to Google Artifact Registry, and deploying it on a Google Kubernetes Engine (GKE) cluster.

This hands-on guide is great for anyone learning containerization, Artifact Registry, or Kubernetes deployments on Google Cloud.

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🧠 What You’ll Learn

By the end of this tutorial, you’ll be able to:

  • Build and test a Docker image locally
  • Create and configure a Google Artifact Repository
  • Push Docker images securely to Artifact Registry
  • Deploy an application on GKE using Artifact Registry images
  • Access and verify your running app via a LoadBalancer service

🪜 Step 1: Introduction

Here’s the overall workflow we’ll follow:

  1. Build a Docker Image
  2. Create a Docker repository in Google Artifact Registry
  3. Set up authentication
  4. Push the image to the repository
  5. Pull the image in a GKE Deployment
  6. Access and verify the sample application in a browser

🧱 Step 2: Create a Dockerfile

Let’s create our first project directory and define a simple Nginx-based Docker image.

mkdir 01-Docker-Image
cd 01-Docker-Image
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Dockerfile

FROM nginx
COPY index.html /usr/share/nginx/html
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index.html

<!DOCTYPE html>
<html>
   <body style="background-color:rgb(185, 126, 120);">
      <h1>Welcome to Latchu@DevOps</h1>
      <p>Google Kubernetes Engine</p>
      <p>Google Artifact Registry - Demo</p>
      <p>Application Version: V1</p>
   </body>
</html>
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🏗️ Step 3: Build the Docker Image

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# Change directory
cd 01-Docker-Image

# Build Docker image
docker build -t myapp1:v1 .

# List Docker images
docker images myapp1
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🧪 Step 4: Run and Test the Image Locally 

# Run the image
docker run --name myapp1 -p 80:80 -d myapp1:v1

# Access in browser or via curl
curl http://localhost

# Check running containers
docker ps

# Stop and remove container
docker stop myapp1
docker rm myapp1
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At this point, your application should work locally.
Now let’s host it on Google Artifact Registry.

🗂️ Step 5: Create a Google Artifact Registry

In the Google Cloud Console:

Go to Artifact Registry → Repositories → Create

Configure as follows:

  • Name: gke-artifact-repo1
  • Format: Docker
  • Mode: Standard
  • Region: us-central1
  • Encryption: Google-managed key
  • Cleanup Policies: Default (dry run)

Click Create

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🔐 Step 6: Configure Authentication

To push Docker images to Artifact Registry, configure authentication.

# Configure authentication for your region
gcloud auth configure-docker us-central1-docker.pkg.dev
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If you’re using Cloud Shell, authentication is already set up.

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🚢 Step 7: Tag and Push Docker Image to Artifact Registry

Tag your local Docker image with the Artifact Registry path and push it:

# Tag the Docker Image
docker tag myapp1:v1 <LOCATION>-docker.pkg.dev/<GOOGLE-PROJECT-ID>/<GOOGLE-ARTIFACT-REGISTRY-NAME>/<IMAGE-NAME>:<IMAGE-TAG>

# Replace Values for docker tag command 
# - LOCATION, 
# - GOOGLE-PROJECT-ID, 
# - GOOGLE-ARTIFACT-REGISTRY-NAME, 
# - IMAGE-NAME, 
# - IMAGE-TAG
# Tag your Docker image

docker tag myapp1:v1 us-central1-docker.pkg.dev/gcp-zero-to-hero-468909/gke-artifact-repo1/myapp1:v1

# Authenticate to Google Cloud (if not done)
gcloud auth login

# Push the image
docker push us-central1-docker.pkg.dev/gcp-zero-to-hero-468909/gke-artifact-repo1/myapp1:v1
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🔍 Step 8: Verify the Image in Artifact Registry

Go to Google Cloud Console → Artifact Registry → gke-artifact-repo1,
and verify that your image (myapp1:v1) is successfully uploaded.

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☸️ Step 9: Deploy to GKE Using Artifact Registry Image

Now, let’s create Kubernetes manifests to deploy our image from Artifact Registry.

mkdir 02-kube-manifests-art
cd 02-kube-manifests-art
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01-kubernetes-deployment.yaml

apiVersion: apps/v1
kind: Deployment 
metadata: 
  name: myapp1-deployment
spec: 
  replicas: 2
  selector:
    matchLabels:
      app: myapp1
  template:  
    metadata: 
      name: myapp1-pod
      labels: 
        app: myapp1  
    spec:
      containers:
        - name: myapp1-container
          image: us-central1-docker.pkg.dev/gcp-zero-to-hero-468909/gke-artifact-repo1/myapp1:v1
          ports: 
            - containerPort: 80
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02-kubernetes-loadBalancer-service.yaml

apiVersion: v1
kind: Service 
metadata:
  name: myapp1-lb-service
spec:
  type: LoadBalancer
  selector:
    app: myapp1
  ports: 
    - name: http
      port: 80
      targetPort: 80
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🚀 Step 10: Deploy and Verify on GKE

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# Apply the manifests
kubectl apply -f 02-kube-manifests-art

# Check deployments and pods
kubectl get deploy
kubectl get pods

# Describe Pod (to confirm image source)
kubectl describe pod <POD-NAME>
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You should see an event similar to this:

Pulling image "us-central1-docker.pkg.dev/gcp-zero-to-hero-468909/gke-artifact-repo1/myapp1:v1"
Successfully pulled image "us-central1-docker.pkg.dev/gcp-zero-to-hero-468909/gke-artifact-repo1/myapp1:v1"
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Now check the service:

kubectl get svc
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Copy the EXTERNAL-IP of the LoadBalancer and open it in your browser:

http://<SVC-EXTERNAL-IP>
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🎉 Your app is now live on GKE, pulling images from Artifact Registry!

🧹 Step 11: Clean Up 

# Delete deployed resources
kubectl delete -f 02-kube-manifests-art
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🏁 Wrapping Up

In this tutorial, we’ve:

✅ Built and tested a Docker image locally
✅ Created a Google Artifact Registry
✅ Pushed an image securely to GAR
✅ Deployed the image to GKE via Kubernetes manifests

Google Artifact Registry is now the recommended and future-ready solution for container image management — replacing the older Google Container Registry (GCR).

🌟 Thanks for reading! If this post added value, a like ❤️, follow, or share would encourage me to keep creating more content.

— Latchu | Senior DevOps & Cloud Engineer

☁️ AWS | GCP | ☸️ Kubernetes | 🔐 Security | ⚡ Automation
📌 Sharing hands-on guides, best practices & real-world cloud solutions

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