DEPLOYMENT_GUIDE.md

🚀 Deployment Guide

AI-Powered Shipment Route Optimization System

Created by: Zayeem Khateeb

📋 Deployment Options

Option 1: Docker Deployment (Recommended)

Prerequisites

• Docker and Docker Compose installed
• 4GB RAM minimum
• 10GB disk space

Steps

# 1. Build and run with Docker Compose
docker-compose up -d

# 2. Access your application
http://localhost:8050

# 3. View logs
docker-compose logs -f dashboard

# 4. Stop deployment
docker-compose down

Option 2: Cloud Deployment (Heroku)

Prerequisites

• Heroku CLI installed
• Git repository

Steps

# 1. Login to Heroku
heroku login

# 2. Create Heroku app
heroku create your-shipment-optimizer

# 3. Set environment variables
heroku config:set FLASK_ENV=production
heroku config:set SECRET_KEY=your-secret-key

# 4. Deploy
git add .
git commit -m "Deploy AI Shipment Optimizer"
git push heroku main

# 5. Open your app
heroku open

Option 3: Vercel Deployment

Prerequisites

• Vercel CLI or GitHub integration

Steps

# 1. Install Vercel CLI
npm i -g vercel

# 2. Deploy
vercel

# 3. Follow prompts and get your URL

Option 4: Railway Deployment

Steps

# 1. Install Railway CLI
npm install -g @railway/cli

# 2. Login
railway login

# 3. Deploy
railway up

# 4. Get your URL
railway domain

Option 5: Local Production Server

Steps

# 1. Install production server
pip install gunicorn

# 2. Run production server
gunicorn -w 4 -b 0.0.0.0:8050 deploy:app

# 3. Access at http://localhost:8050

🔧 Environment Variables

Create .env file with:

# Database
DATABASE_URL=your_database_url

# API Keys
OPENWEATHER_API_KEY=your_weather_api_key
GOOGLE_MAPS_API_KEY=your_maps_api_key

# Security
SECRET_KEY=your-secret-key-here

# App Config
FLASK_ENV=production
PORT=8050

📊 Performance Optimization

For Production:

1. Enable caching: Redis configured in docker-compose
2. Database optimization: PostgreSQL with proper indexing
3. Load balancing: Multiple worker processes
4. Monitoring: Built-in health checks

Scaling:

• Horizontal: Multiple container instances
• Vertical: Increase CPU/RAM allocation
• Database: Separate database server

🔒 Security Checklist

• ✅ Environment variables for secrets
• ✅ Non-root Docker user
• ✅ HTTPS in production (handled by platform)
• ✅ Input validation and sanitization
• ✅ Database connection security

📈 Monitoring

Health Check Endpoint:

GET /health

Metrics Available:

• Total shipments processed
• ML model accuracy
• Response times
• Error rates

🆘 Troubleshooting

Common Issues:

1. Port already in use

   # Change port in docker-compose.yml or .env
   PORT=8051
   

2. Database connection failed

   # Check DATABASE_URL in .env
   # Ensure database is running
   

3. ML model training fails

   # Check data format
   # Increase memory allocation
   

📞 Support

For deployment issues:

1. Check logs: docker-compose logs dashboard
2. Verify environment variables
3. Ensure all dependencies are installed
4. Check system requirements

Your AI-Powered Shipment Route Optimization System is ready for production! 🎉