Introduction

Google Cloud Run is a fully managed serverless platform that allows you to run stateless containers. It's an excellent choice for deploying Node.js applications, offering scalability, ease of use, and cost-effectiveness. In this guide, we'll walk through the process of deploying a Node.js application on Google Cloud Run.

Prerequisites

Before we begin, make sure you have:

1. A Google Cloud Platform (GCP) account
2. Google Cloud SDK installed on your local machine
3. Node.js and npm installed
4. Docker installed (for local testing)

Step 1: Prepare Your Node.js Application

First, let's create a simple Express.js application:

const express = require('express');
const app = express();
const port = process.env.PORT || 8080;

app.get('/', (req, res) => {
  res.send('Hello from Google Cloud Run!');
});

app.listen(port, () => {
  console.log(`Server running on port ${port}`);
});

Save this as app.js in your project directory.

Step 2: Create a Dockerfile

Next, create a Dockerfile in your project root:

FROM node:14

WORKDIR /usr/src/app

COPY package*.json ./

RUN npm install

COPY . .

EXPOSE 8080

CMD [ "node", "app.js" ]

This Dockerfile sets up the environment for your Node.js application.

Step 3: Create a .dockerignore File

Create a .dockerignore file to exclude unnecessary files from your Docker image:

node_modules
npm-debug.log

Step 4: Build and Test Your Container Locally

Before deploying, it's a good idea to test your container locally:

docker build -t my-nodejs-app .
docker run -p 8080:8080 my-nodejs-app

Visit http://localhost:8080 to ensure your app is working correctly.

Step 5: Set Up Google Cloud Project

If you haven't already, create a new Google Cloud project:

gcloud projects create my-nodejs-project
gcloud config set project my-nodejs-project

Enable the necessary APIs:

gcloud services enable run.googleapis.com

Step 6: Build and Push Your Container Image

Use Google Cloud Build to build and push your container image:

gcloud builds submit --tag gcr.io/my-nodejs-project/my-nodejs-app

This command builds your container and pushes it to Google Container Registry.

Step 7: Deploy to Google Cloud Run

Now, deploy your application to Cloud Run:

gcloud run deploy my-nodejs-service \
  --image gcr.io/my-nodejs-project/my-nodejs-app \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated

This command creates a new Cloud Run service named my-nodejs-service using your container image.

Step 8: Access Your Deployed Application

After deployment, Cloud Run will provide you with a URL to access your application. You can also find this URL using:

gcloud run services describe my-nodejs-service --platform managed --region us-central1

Managing Your Deployment

Updating Your Application

To update your application, simply rebuild your container and redeploy:

gcloud builds submit --tag gcr.io/my-nodejs-project/my-nodejs-app
gcloud run deploy my-nodejs-service --image gcr.io/my-nodejs-project/my-nodejs-app

Monitoring and Logging

Google Cloud provides built-in monitoring and logging for Cloud Run services. Access these features in the Google Cloud Console under the "Monitoring" and "Logging" sections.

Scaling

Cloud Run automatically scales your application based on incoming requests. You can configure the maximum number of instances and concurrency:

gcloud run services update my-nodejs-service \
  --max-instances=10 \
  --concurrency=80

Best Practices

1. Optimize Your Container: Keep your container image small and efficient.
2. Handle Graceful Shutdowns: Implement proper shutdown handling in your Node.js application.
3. Use Environment Variables: Store configuration in environment variables rather than hardcoding them.
4. Implement Health Checks: Add a health check endpoint to your application for better reliability.

Troubleshooting

If you encounter issues:

1. Check your application logs in the Google Cloud Console.
2. Ensure your application is listening on the port specified by the PORT environment variable.
3. Verify that your Dockerfile is correctly configured.
4. Double-check that all necessary APIs are enabled in your Google Cloud project.