Deploying Node.js to AWS Elastic Beanstalk with CI/CD

A backend isn't really shipped until deploying it is boring. For the Buffdudes platform, the deployment pipeline that took a Node.js, TypeScript, and Express service to 60K+ users without drama was built on GitHub Actions, AWS Elastic Beanstalk, and RDS, fronted by Nginx and Redis. Here's how the pieces fit, and why this stack is a sensible default for a solo or small team.

Why Elastic Beanstalk

Elastic Beanstalk sits in a useful middle ground. Raw EC2 gives you total control and total responsibility — you own the OS, the process manager, the load balancer wiring, all of it. Fully managed serverless removes that burden but imposes its own model. Elastic Beanstalk handles the provisioning, the load balancer, health checks, and rolling deploys, while still letting you treat the app as a normal long-running Node.js server.

For a backend with persistent connections, background work, and a conventional Express app, that "managed but still a real server" posture is exactly right. I didn't want to reinvent deploy orchestration; I wanted to push code and have it go live safely.

The database: RDS

The application database is PostgreSQL on RDS, kept deliberately separate from the application tier. That separation matters: the app instances managed by Elastic Beanstalk can be replaced, scaled, or redeployed without touching the data. RDS handles backups, patching, and availability, so the most precious part of the system — the data — isn't coupled to the lifecycle of a deploy.

Nginx and Redis out front

In front of the Node.js app sits Nginx, handling incoming traffic and acting as a reverse proxy to the application. Redis does the caching heavy lifting — most importantly the leaderboard caches and other hot reads that would otherwise hammer PostgreSQL on every request. Putting these in front of the app meant the Node.js process could stay focused on application logic while Nginx and Redis absorbed the load patterns each is built for.

The CI/CD pipeline

The pipeline runs on GitHub Actions, triggered on pushes to the main branch. The shape is the same one I'd recommend to anyone:

1. Install and build. Pull dependencies cleanly and compile the TypeScript so a broken build fails in CI, not in production.
2. Verify. Run the checks that gate a release. A failing check stops the deploy before anything reaches AWS.
3. Deploy to Elastic Beanstalk. On a green build, the workflow ships the new version to the Elastic Beanstalk environment, which performs a rolling update so the service stays available through the swap.

The win here is psychological as much as technical: merging to main is deploying. There's no separate manual ritual where a human SSHes into a box and hopes. The pipeline is the single, repeatable path to production, which means deploys happen more often and each one carries less risk.

Zero downtime in practice

"Zero downtime" isn't one feature — it's the combination. Elastic Beanstalk's rolling deploys mean instances are replaced gradually rather than all at once. RDS being separate means data survives every app deploy untouched. Nginx and Redis in front absorb load and smooth over the moment of transition. And the CI/CD gate means broken builds never get the chance to go live in the first place.

The takeaway

You don't need an exotic platform to run a real product reliably. GitHub Actions for the pipeline, Elastic Beanstalk for managed-but-real app hosting, RDS for durable data, and Nginx plus Redis out front is a stack that's understandable by one person and robust enough for tens of thousands of users. The goal was never clever infrastructure — it was to make shipping safe, repeatable, and boring. That's what let me keep moving fast without breaking things.