How to Build and Deploy Your First Application on Google Cloud

Building and deploying applications on the cloud has become a vital skill for modern developers. With the vast array of tools available, it’s crucial to choose the right platform. Google Cloud Platform (GCP) is a comprehensive and robust cloud service that offers everything from virtual machines to managed Kubernetes clusters.

In this blog, we’ll guide you through the process of building and deploying your first application on Google Cloud, helping you understand the essential steps, tools, and best practices for success.

Step 1: Set Up a Google Cloud Account

Before you start building and deploying an application on Google Cloud, you need to create an account on Google Cloud Platform (GCP).

1. Create an Account:

• Visit the Google Cloud website.
• Sign up for a new Google Cloud account, or log in if you already have one.
• Google Cloud offers a free trial with $300 in credits for new users, so you can get started without worrying about costs upfront.

2. Create a Project:

• Once logged in, go to the Google Cloud Console.
• Click on “Select a Project” in the top navigation and then click on “New Project”.
• Provide a project name and a billing account (if necessary) and hit “Create”.

Projects help organize resources, track billing, and manage permissions, so it’s good practice to keep your applications within separate projects.

Step 2: Choose Your Application Framework

Before you begin, decide which framework or programming language you’ll use for your first application. Google Cloud supports a variety of programming languages such as Python, Node.js, Java, Go, and more.

Popular Frameworks:

• Node.js: Good for building scalable web applications.
• Python: Great for data-driven applications, machine learning, and web apps.
• Java: Ideal for enterprise-level applications.

For this tutorial, let’s assume we’re building a simple web application using Python Flask, a lightweight framework perfect for beginners.

Set Up Your Development Environment:

• Install Python: If you don’t have Python installed, download it from here.
• Install Flask: Open a terminal or command prompt and run:

pip install flask

Sample Python Flask Application:

Create a new directory for your app and inside it, create a Python file app.py with the following code:

from flask import Flask

app = Flask(__name__)

@app.route('/')
def hello_world():
    return "Hello, Google Cloud!"

if __name__ == '__main__':
    app.run(debug=True)
  

This is a simple application that returns “Hello, Google Cloud!” when accessed in a browser.

Step 3: Prepare Your Application for Google Cloud

Dockerize Your Application

Google Cloud supports containerized applications, and using Docker to package your app will make deployment easier and more scalable. First, create a Dockerfile in your project directory:

# Use an official Python runtime as a parent image
FROM python:3.8-slim

# Set the working directory in the container
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# Install any needed packages specified in requirements.txt
RUN pip install -r requirements.txt

# Make port 5000 available to the world outside this container
EXPOSE 5000

# Define environment variable
ENV NAME World

# Run app.py when the container launches
CMD ["python", "app.py"]
  

In the requirements.txt file, add:

flask

Now, you can build the Docker image using the following command:

docker build -t flask-app .

Run the Docker container locally to ensure everything works:

docker run -p 5000:5000 flask-app

Access http://localhost:5000 in your browser. If you see “Hello, Google Cloud!”, your app is ready for deployment.

Push to Google Container Registry

First, authenticate your Google Cloud account using the gcloud CLI:

gcloud auth login

1. Tag your Docker image with the Container Registry URL:

docker tag flask-app gcr.io/YOUR_PROJECT_ID/flask-app:v1

2. Push your image to Google Container Registry:

docker push gcr.io/YOUR_PROJECT_ID/flask-app:v1

3. Replace YOUR_PROJECT_ID with your actual Google Cloud Project ID.

Step 4: Deploy Your Application to Google Cloud

Option 1: Deploy with Google Cloud Run (Recommended for simplicity)

Google Cloud Run is a fully managed platform that enables you to run your containerized applications easily. It abstracts away the infrastructure and auto-scales your application based on traffic.

Enable Cloud Run in your project:

gcloud services enable run.googleapis.com

1. Deploy the application to Cloud Run:

gcloud run deploy flask-app \
  --image gcr.io/YOUR_PROJECT_ID/flask-app:v1 \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated
  

2. This will automatically create a new Cloud Run service and deploy your container to it.

3. After deployment, you’ll receive a URL where your app is accessible.

4. Open the URL in your browser to see your deployed application!

Option 2: Deploy with Google Kubernetes Engine (GKE)

For more complex use cases, such as managing microservices or requiring fine-grained control over the infrastructure, Google Kubernetes Engine (GKE) is a better option.

Create a Kubernetes cluster:

gcloud container clusters create flask-cluster \
  --num-nodes 3 \
  --zone us-central1-a
  

1. Authenticate kubectl to your cluster:

gcloud container clusters get-credentials flask-cluster --zone us-central1-a --project YOUR_PROJECT_ID
  

2. Create Kubernetes deployment and service YAML files for your application.

Apply the deployment to GKE:

kubectl apply -f deployment.yaml
kubectl apply -f service.yaml
  

Once deployed, you can access your application via the external IP of the GKE service.

Step 5: Monitor and Scale Your Application

Google Cloud provides integrated tools to monitor and scale your application.

Monitoring: Use Google Cloud Monitoring to track the performance of your application. Set up alerts to notify you if the application experiences high latency or downtime.

Scaling: Both Cloud Run and GKE support autoscaling. For Cloud Run, scaling happens automatically based on incoming requests. GKE provides auto-scaling features based on CPU usage or custom metrics.

Step 6: Next Steps and Best Practices

Once your application is up and running on Google Cloud, consider the following best practices for optimizing your cloud deployment:

• Security: Use Google Cloud’s IAM to control access to your resources and services. Ensure that your application is protected from unauthorized access.
• CI/CD Pipelines: Set up continuous integration and continuous deployment (CI/CD) pipelines with Cloud Build to automate the testing and deployment of your application.
• Data Storage: If your application requires persistent storage, consider using Cloud SQL or Firestore for scalable, fully managed database solutions.
• Cost Management: Use Google Cloud’s Billing Console to monitor and manage the costs associated with your cloud resources.

Conclusion: Your First Google Cloud Application is Live!

Congratulations, you’ve successfully built and deployed your first application on Google Cloud! Whether you chose Google Cloud Run for its simplicity or Google Kubernetes Engine for its flexibility, you now have the skills to scale and manage your applications on the cloud.

Ready to explore more cloud-native technologies? Start learning about other Google Cloud services and grow your cloud application development skills today!