Railway Deployment Tutorial for an AI-Generated App

Railway Deployment Tutorial for an AI-Generated App

By Revdoku Content TeamUpdated
Table of Contents

Railway service page

Before you start

This Railway deployment tutorial is for an AI-generated app that needs a running server, such as an API, login system, database connection, or background process. Railway is a practical vibe coding hosting option because it can build the code from GitHub, run the server, and redeploy later changes automatically.

Before you begin, make sure you have:

  • A Railway account connected to GitHub
  • A GitHub repository for the app
  • A working local version of the app
  • The names and values of any required environment variables

Keep real secrets outside Git. Never commit an API key, database password, private token, or populated .env file.

1. Make the app production-ready

AI coding tools often create a development command but forget the production setup. Your app must have a start command, and its server must listen on Railway’s PORT environment variable.

Check these parts before publishing:

  • Start command: Add a production command such as npm start or uvicorn main:app.
  • Port: Read the port from the environment instead of fixing it to 3000 or 8000.
  • Host: Bind the server to 0.0.0.0, not only localhost.
  • Dependencies: Commit the manifest and lockfile, such as package.json and package-lock.json.

For Express, use process.env.PORT || 3000 and listen on 0.0.0.0. For FastAPI, a start command could be uvicorn main:app --host 0.0.0.0 --port $PORT. Railway documents more examples in its public networking troubleshooting guide.

2. Push it to GitHub

Create a GitHub repository, then upload or push the app. Before the first push:

  1. Add .env, private keys, and local database files to .gitignore.
  2. Commit the source code, dependency files, and production configuration.
  3. Confirm that the repository contains the server entry point.

An .env.example file may list variable names such as OPENAI_API_KEY= without including real values. This helps you remember what Railway needs without exposing credentials.

3. Create a Railway project from the repo

In Railway, choose New Project, select Deploy from GitHub repo, and authorize access if prompted. Pick the repository and deployment branch. Railway will inspect the project, install its dependencies, build it, and run the detected start command.

If detection fails, open the service’s Settings and enter a custom command under Deploy. Railway explains this option in its start command documentation.

Railway GitHub autodeploy guide

4. Add environment variables

Open the service, select Variables, and add each required value with New Variable or the Raw Editor. Common examples include:

  • OPENAI_API_KEY for an AI provider
  • DATABASE_URL for persistent data
  • NODE_ENV=production for a Node app

Enter secrets in Railway, never in a Git commit. Railway injects variables into the build and running service. It also supplies PORT, so you normally should not create that variable yourself. Review and deploy staged changes after editing variables. See Railway’s variables guide for the current controls.

5. Generate a public Railway domain

A deployed service is not automatically public. To expose it:

  1. Open the service’s Settings tab.
  2. Find Networking, then Public Networking.
  3. Select Generate Domain.

Railway creates an HTTPS address ending in .up.railway.app. Confirm that its target port matches the port used by your server. The official domain guide also covers custom domains and SSL.

Railway public domain guide

6. Test the deployment and logs

Open the public URL in a private browser window. Test the home page and one real server action, such as submitting a form, signing in, or sending an AI request. A page loading correctly does not prove that its API calls work.

Symptom What to inspect
Application failed to respond Host and PORT binding
Service exits immediately Start command and missing dependencies
Feature fails in production Environment variables and external URLs
Build fails Build logs and dependency versions

Click the deployment to inspect build and runtime output. Railway captures messages written to standard output and standard error. Its logging guide notes a limit of 500 log lines per second per replica, so avoid noisy debug logging in production.

Update the app

Push a new commit to the connected branch when you want to update the app. GitHub-linked services normally start a fresh deployment automatically, as described in Railway’s GitHub autodeploy guide. Test the public domain again after the deployment succeeds.

For client work, you can place that live demo beside a proposal, deck, or instructions in a private Revdoku bucket. The shared Revdoku link stays the same while you update the deliverables, and password or email gates let you control access and see when a client opens them.

Deployment checklist

Item What to check Why it matters
Start command A production server command exists Railway needs a process to run
Networking Server uses 0.0.0.0 and Railway’s PORT Public requests can reach the app
Secrets Values exist only in Railway Credentials stay out of Git
Domain A Railway domain is generated The app becomes publicly accessible
Testing Pages, server actions, and logs work The deployment is ready to share

Your site is live.

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