You've built your AI SaaS app with Shipfastai. Now it's time to deploy. This guide covers three popular deployment options and the trade-offs of each.
Option 1: Vercel + Railway (Recommended)
This is our recommended stack for most startups:
•Frontend: Vercel (optimized for Next.js)
•Backend: Railway (great for Python/FastAPI)
•Database: Supabase (included)
Deploying to Vercel
# Install Vercel CLI
npm i -g vercel
# Deploy
vercel --prod
Configure environment variables in the Vercel dashboard:
NEXT_PUBLIC_SUPABASE_URL=your-url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your-key
NEXT_PUBLIC_API_URL=https://your-railway-url
Deploying Backend to Railway
# Install Railway CLI
npm i -g @railway/cli
# Login and deploy
railway login
railway init
railway up
Option 2: AWS with Docker
For teams that need more control:
# Dockerfile
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
Deploy to ECS or App Runner for managed container hosting.
Option 3: Self-hosted
For enterprise deployments, use Docker Compose:
version: '3.8'
services:
frontend:
build: ./frontend
ports:
- "3000:3000"
backend:
build: ./backend
ports:
- "8000:8000"
Zero-Downtime Deployments
Regardless of platform, follow these practices:
1. Health checks - Configure proper health endpoints
2. Graceful shutdown - Handle SIGTERM signals
3. Database migrations - Run before deploying new code
4. Feature flags - Roll out features gradually
Monitoring
Set up monitoring from day one:
•Sentry for error tracking
•PostHog for product analytics
•Better Stack for uptime monitoring
Your users will thank you.