MQL5-Google-Onedrive/docs/Cloud_Deployment_Guide.md

Cloud Deployment Guide

This guide explains how to deploy the MQL5 Trading Automation system to various cloud platforms.

⚠️ Important: These deployment methods run the automation system (Python scripts) or a headless MT5 instance. They do not enable custom indicators or EAs on the Exness Web Terminal. For charting and manual trading with custom tools, you must use the Exness MetaTrader 5 Desktop Application.

Supported Platforms

• Render.com - Simple web service deployment
• Railway.app - Container-based deployment
• Fly.io - Global edge deployment
• Docker - Container deployment (any platform)
• Heroku - Legacy support (via Docker)

Prerequisites

• GitHub repository pushed and accessible
• Account on chosen cloud platform
• Python 3.8+ support on platform

Platform-Specific Deployment

1. Render.com Deployment

Configuration File: render.yaml

Steps:

1. Push to GitHub:

   git push origin main
   

2. Create Render Service:

   • Go to https://render.com
   • Click "New +" → "Web Service"
   • Connect your GitHub repository
   • Render will auto-detect render.yaml

3. Configure Environment Variables (if needed):

   • PYTHONUNBUFFERED=1
   • TZ=UTC (or your timezone)

4. Deploy:

   • Click "Create Web Service"
   • Render will build and deploy automatically

Manual Deploy Script:

python scripts/deploy_cloud.py render

2. Railway.app Deployment

Configuration File: railway.json

Steps:

1. Install Railway CLI:

   npm i -g @railway/cli
   

2. Login:

   railway login
   

3. Initialize Project:

   railway init
   

4. Deploy:

   railway up
   

Or use Railway Dashboard:

• Go to https://railway.app
• Create new project
• Connect GitHub repository
• Railway will auto-detect railway.json

Manual Deploy Script:

python scripts/deploy_cloud.py railway

3. Fly.io Deployment

Configuration File: fly.toml

Steps:

1. Install Fly CLI:

   # Windows (PowerShell)
   powershell -Command "iwr https://fly.io/install.ps1 -useb | iex"
   
   # macOS/Linux
   curl -L https://fly.io/install.sh | sh
   

2. Login:

   fly auth login
   

3. Launch App:

   fly launch
   

4. Deploy:

   fly deploy
   

Manual Deploy Script:

python scripts/deploy_cloud.py flyio

4. Docker Deployment

Configuration Files: Dockerfile, docker-compose.yml

Local Docker Build:

# Build image
docker build -t mql5-automation .

# Run container
docker run -d --name mql5-automation \
  -v $(pwd)/config:/app/config \
  -v $(pwd)/logs:/app/logs \
  mql5-automation

# Or use docker-compose
docker-compose up -d

Deploy to Cloud with Docker:

Any platform that supports Docker:

• AWS ECS/Fargate
• Google Cloud Run
• Azure Container Instances
• DigitalOcean App Platform
• Vercel (with Docker support)

Manual Deploy Script:

python scripts/deploy_cloud.py docker --build

5. Heroku Deployment

Using Docker:

1. Create heroku.yml:

   build:
     docker:
       web: Dockerfile
   

2. Deploy:

   heroku container:push web
   heroku container:release web
   

Configuration

Environment Variables

All platforms support these environment variables:

PYTHONUNBUFFERED=1          # Python output buffering
TZ=UTC                      # Timezone
LOG_LEVEL=INFO              # Logging level
MAX_RETRIES=3               # Component retry count

Volume Mounts

For persistent storage (logs, config):

• Render: Use Render Disk (paid plans)
• Railway: Use Railway Volumes
• Fly.io: Use Fly Volumes
• Docker: Use bind mounts or volumes

Monitoring

Health Checks

All platforms support health checks:

• Render: Configured in render.yaml
• Railway: Automatic
• Fly.io: Configured in fly.toml
• Docker: Use docker-compose.yml healthcheck

Logs

Access logs on each platform:

• Render: Dashboard → Logs tab
• Railway: Dashboard → Deployments → View Logs
• Fly.io: fly logs
• Docker: docker logs mql5-automation

Continuous Deployment

GitHub Actions Integration

All platforms support automatic deployment on push:

1. Render: Enable "Auto-Deploy" in settings
2. Railway: Enable "Auto Deploy" in project settings
3. Fly.io: Use GitHub Actions workflow (see below)

GitHub Actions Workflow

Create .github/workflows/deploy-cloud.yml:

name: Deploy to Cloud

on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Deploy to Render
        uses: johnletey/railway-deploy@master
        env:
          RAILWAY_TOKEN: ${{ secrets.RAILWAY_TOKEN }}

Cost Considerations

Free Tiers

• Render: Free tier available (limited hours)
• Railway: $5 credit/month
• Fly.io: Free tier with limits
• Docker: Free on self-hosted

Paid Plans

• Render: $7/month for always-on
• Railway: Pay-as-you-go
• Fly.io: Pay-as-you-go
• Docker: Varies by platform

Troubleshooting

Common Issues

1. Build Failures:

• Check Python version compatibility
• Verify all dependencies in requirements.txt
• Review build logs

2. Runtime Errors:

• Check environment variables
• Verify file permissions
• Review application logs

3. Connection Issues:

• Verify network configuration
• Check firewall rules
• Review platform-specific networking docs

Getting Help

• Render: https://render.com/docs
• Railway: https://docs.railway.app
• Fly.io: https://fly.io/docs
• Docker: https://docs.docker.com

Quick Deploy Commands

# Setup all platform configs
python scripts/deploy_cloud.py all

# Deploy to specific platform
python scripts/deploy_cloud.py render
python scripts/deploy_cloud.py railway
python scripts/deploy_cloud.py flyio
python scripts/deploy_cloud.py docker --build

Next Steps

After deployment:

1. Monitor Logs: Check platform dashboard for logs
2. Test Functionality: Verify automation is running
3. Set Up Alerts: Configure notifications for failures
4. Scale if Needed: Adjust resources based on usage

Support

For deployment issues:

• Email: Lengkundee01.org@domain.com
• GitHub Issues: https://github.com/A6-9V/MQL5-Google-Onedrive/issues
• WhatsApp: Agent community