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🚀 Deployment Guide

This guide covers multiple deployment options for your Exoplanet Classifier React/FastAPI application.

🐳 Docker Deployment (Recommended)

Local Docker

# Build and run with Docker Compose
docker-compose up --build

# Or build manually
docker build -t exoplanet-classifier .
docker run -p 8000:8000 exoplanet-classifier

Cloud Docker (Railway, Render, etc.)

  1. Push your code to GitHub
  2. Connect your repository to your cloud provider
  3. Use the provided Dockerfile and docker-compose.yml

🌐 Railway Deployment (Easiest)

Railway automatically detects the railway.json configuration.

Steps:

  1. Sign up at railway.app
  2. Connect GitHub repository
  3. Deploy - Railway will automatically:
    • Build the React frontend
    • Install Python dependencies
    • Start the FastAPI server
    • Serve both frontend and backend

Environment Variables (if needed):

  • PORT - Railway sets this automatically
  • PYTHONPATH=/app

⚡ Vercel + Railway (Hybrid)

Deploy frontend to Vercel and backend to Railway for optimal performance.

Frontend (Vercel):

  1. Connect your GitHub repo to vercel.com
  2. Set root directory to frontend/
  3. Update frontend/vercel.json with your Railway backend URL
  4. Deploy

Backend (Railway):

  1. Deploy backend using Railway (see above)
  2. Copy your Railway app URL
  3. Update frontend/vercel.json to point to your Railway URL

🐍 Heroku Deployment

  1. Install Heroku CLI
  2. Login and create app: 
    heroku login
heroku create your-app-name
  3. Deploy: 
    git push heroku main

☁️ AWS/GCP/Azure

Option 1: Container Service

  • Use the provided Dockerfile
  • Deploy to ECS (AWS), Cloud Run (GCP), or Container Instances (Azure)

Option 2: Serverless

  • Backend: Deploy FastAPI to AWS Lambda, Google Cloud Functions, or Azure Functions
  • Frontend: Deploy React build to S3 + CloudFront (AWS), Cloud Storage (GCP), or Blob Storage (Azure)

🔧 Environment Configuration

Production Environment Variables:

# Backend
PYTHONPATH=/app
PYTHONUNBUFFERED=1
PORT=8000

# Frontend (if separate deployment)
VITE_API_URL=https://your-backend-url.railway.app

Update API URL in Frontend:

If deploying separately, update frontend/src/lib/api.ts:

const API_BASE_URL = import.meta.env.VITE_API_URL || 'http://localhost:8000'

📊 Monitoring & Health Checks

Your deployment includes:

  • Health check endpoint at /
  • API documentation at /docs
  • Automatic restarts on failure
  • Static file serving for React app

🚨 Troubleshooting

Common Issues:

  1. Frontend not loading:

    • Ensure React build files exist in static/ directory
    • Check that static file serving is enabled

  2. API not responding:

    • Verify all Python dependencies are installed
    • Check that model file exists: properly_trained_model.joblib

  3. CORS errors:

    • Backend includes CORS middleware for localhost:5173
    • For production, update CORS origins in api/main.py

Logs:

  • Railway: Check deployment logs in dashboard
  • Heroku: heroku logs --tail
  • Docker: docker logs <container-id>

🎯 Recommended Deployment

For beginners: Use Railway - it's the easiest and handles everything automatically.

For production: Use Railway + Vercel - backend on Railway, frontend on Vercel for optimal performance.

For enterprise: Use AWS/GCP/Azure with container services for full control.