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SadakAI Deployment Guide

This guide covers deploying SadakAI to production environments.

🏭 Production Architecture

┌─────────────────────────────────────────────────────────────┐
│                        CDN (Cloudflare)                      │
└────────────────────────┬────────────────────────────────────┘
                        │
         ┌──────────────┴──────────────┐
         │                             │
    ┌────▼────┐                  ┌────▼────┐
    │ Vercel  │                  │ Railway │
    │Frontend │                  │  API    │
    └─────────┘                  └────┬────┘
                                      │
                    ┌─────────────────┼─────────────────┐
                    │                 │                 │
               ┌────▼────┐     ┌────▼────┐     ┌────▼────┐
               │ Neon DB  │     │  R2     │     │ Sentry  │
               │(Postgres)│     │(Storage)│     │(Logs)   │
               └─────────┘     └─────────┘     └─────────┘

🚀 Quick Deploy

Option 1: Vercel + Railway (Recommended)

1. Deploy Frontend to Vercel

# Install Vercel CLI
npm i -g vercel

# Navigate to dashboard
cd dashboard

# Login to Vercel
vercel login

# Deploy
vercel --prod

Or connect your GitHub repository to Vercel:

  1. Go to https://vercel.com
  2. Import your repository
  3. Configure:
    • Framework: Next.js
    • Build Command: npm run build
    • Output Directory: .next
  4. Add environment variables
  5. Deploy

2. Deploy Backend to Railway

# Install Railway CLI
npm i -g @railway/cli

# Login
railway login

# Create project
railway init

# Add PostgreSQL plugin
railway add -p postgres

# Deploy
railway up

Or use Railway's GitHub integration.

Option 2: Docker Compose (Self-Hosted)

# Clone and configure
git clone https://github.com/your-username/SadakAI.git
cd SadakAI

# Edit environment
cp .env.example .env
nano .env

# Deploy
docker-compose -f docker-compose.prod.yml up -d

⚙️ Environment Configuration

Production Environment Variables

Backend (.env)

# Database - Use PostgreSQL in production
DATABASE_URL=postgresql://user:password@host:5432/sadakai

# Cloudflare R2 Storage (recommended for production)
R2_ENDPOINT=https://your-account.r2.cloudflarestorage.com
R2_ACCESS_KEY=your_access_key
R2_SECRET_KEY=your_secret_key
R2_BUCKET=sadakai-images

# API Security
API_KEY=generate_strong_random_key

# Model Path
MODEL_PATH=/app/weights/best.pt

Frontend (.env)

NEXT_PUBLIC_API_URL=https://your-api-domain.com

🗄️ Database Setup

Option 1: Neon (Serverless PostgreSQL)

  1. Create account at https://neon.tech
  2. Create new project
  3. Copy connection string
  4. Add to environment variables

Option 2: Railway PostgreSQL

# Add PostgreSQL to Railway project
railway add -p postgres

Option 3: Supabase

  1. Create project at https://supabase.com
  2. Get connection string from settings
  3. Enable PostGIS extension: 
    CREATE EXTENSION postgis;

☁️ Storage Setup

Cloudflare R2 (Recommended - Free Egress)

  1. Create Cloudflare account
  2. Create R2 bucket
  3. Get API credentials
  4. Add to environment

Alternative: AWS S3

# Update storage service for S3
import boto3

s3 = boto3.client('s3',
    aws_access_key_id=AWS_ACCESS_KEY,
    aws_secret_access_key=AWS_SECRET_KEY,
    region_name='us-east-1'
)

🔒 Security Checklist

  • Enable HTTPS everywhere
  • Set strong API keys
  • Configure CORS properly
  • Add rate limiting
  • Enable database encryption
  • Set up monitoring (Sentry)
  • Configure backups
  • Use environment variables for secrets

📊 Monitoring

Sentry Integration

# Install Sentry SDK
pip install sentry-sdk

# Configure in main.py
import sentry_sdk
sentry_sdk.init(
    dsn="your-sentry-dsn",
    traces_sample_rate=0.1
)

LogRocket

# Add to layout.tsx
import LogRocket from 'logrocket';
LogRocket.init('your-app-id');

🔄 CI/CD

GitHub Actions

# .github/workflows/deploy.yml
name: Deploy

on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      
      - name: Deploy to Vercel
        run: |
          npm i -g vercel
          vercel --prod --token=${{ secrets.VERCEL_TOKEN }}

📈 Performance Optimization

Frontend

  1. Enable Image Optimization

    // next.config.js
images: {
  domains: ['your-bucket.r2.cloudflarestorage.com'],
}

  2. Add Caching Headers

    // next.config.js
async headers() {
  return [
    {
      source: '/:path*',
      headers: [
        { key: 'Cache-Control', value: 'public, max-age=3600' }
      ]
    }
  ]
}

Backend

  1. Enable Gzip Compression
  2. Use Redis for Caching (optional)
  3. Configure Worker Processes 
    gunicorn api.main:app -w 4 -k uvicorn.workers.UvicornWorker

🆘 Troubleshooting

Common Issues

Frontend Build Fails

# Clear cache and rebuild
rm -rf .next
npm run build

API Returns 500

  • Check logs: railway logs
  • Verify DATABASE_URL
  • Check model weights exist

Map Not Loading

  • Verify API is accessible
  • Check CORS settings
  • Ensure map tiles accessible

📞 Support

For deployment issues:

  1. Check application logs
  2. Verify environment variables
  3. Test database connection
  4. Contact maintainer

🔄 Updating

Frontend Updates

# Pull latest changes
git pull origin main

# Rebuild
npm run build

Backend Updates

# Pull latest changes
git pull origin main

# Rebuild Docker image
docker-compose build api

# Restart services
docker-compose restart api

Need help? Open an issue on GitHub or contact the maintainer.