Guido.Tech/RENDER_DEPLOYMENT.md

Render.com Deployment Guide

Quick Start

1. Render.com Configuration

Service Type: Web Service

Build Command:

pip install -r requirements.txt

Start Command (choose one):

Option A: Shell Script (Recommended)

./start.sh

Option B: Python Supervisor

python start.py

Option C: Direct Command

python scripts/serve.py & python ai_intelligence_layer/main.py

2. Environment Variables

Set these in Render.com dashboard:

Required:

GEMINI_API_KEY=your_gemini_api_key_here
ENVIRONMENT=production
PRODUCTION_URL=https://your-app-name.onrender.com  # Your Render app URL

Optional:

ELEVENLABS_API_KEY=your_elevenlabs_api_key_here  # For voice features
GEMINI_MODEL=gemini-2.5-flash
STRATEGY_COUNT=3
FAST_MODE=true

Auto-configured (no need to set):

# These are handled automatically by the config system
AI_SERVICE_PORT=9000
AI_SERVICE_HOST=0.0.0.0
ENRICHMENT_SERVICE_URL=http://localhost:8000  # Internal communication

Important: Production URL

After deploying to Render, you'll get a URL like:

https://your-app-name.onrender.com

You MUST set this URL in the environment variables:

1. Go to Render dashboard → your service → Environment
2. Add: PRODUCTION_URL=https://your-app-name.onrender.com
3. The app will automatically use this for WebSocket connections and API URLs

3. Health Check

Health Check Path: /health (on port 9000)

Health Check Command:

curl http://localhost:9000/health

4. Port Configuration

• Enrichment Service: 8000 (internal)
• AI Intelligence Layer: 9000 (external, Render will expose this)

Render will automatically bind to PORT environment variable.

5. Files Required

• ✅ start.sh - Shell startup script
• ✅ start.py - Python startup supervisor
• ✅ Procfile - Render configuration
• ✅ requirements.txt - Python dependencies

6. Testing Locally

Test the startup script before deploying:

# Make executable
chmod +x start.sh

# Run locally
./start.sh

Or with Python supervisor:

python start.py

7. Deployment Steps

1. Push to GitHub:

   git add .
   git commit -m "Add Render deployment configuration"
   git push
   

2. Create Render Service:

   • Go to render.com
   • New → Web Service
   • Connect your GitHub repository
   • Select branch (main)

3. Configure Service:

   • Name: hpc-simulation-ai
   • Environment: Python 3
   • Build Command: pip install -r requirements.txt
   • Start Command: ./start.sh

4. Add Environment Variables:

   • GEMINI_API_KEY
   • ELEVENLABS_API_KEY (optional)

5. Deploy! 🚀

8. Monitoring

Check logs in Render dashboard for:

• 📊 Starting Enrichment Service on port 8000...
• 🤖 Starting AI Intelligence Layer on port 9000...
• ✨ All services running!

9. Connecting Clients

WebSocket URL:

wss://your-app-name.onrender.com/ws/pi

Enrichment API:

https://your-app-name.onrender.com/ingest/telemetry

10. Troubleshooting

Services won't start:

• Check environment variables are set
• Verify start.sh is executable: chmod +x start.sh
• Check build logs for dependency issues

Port conflicts:

• Render will set PORT automatically (9000 by default)
• Services bind to 0.0.0.0 for external access

Memory issues:

• Consider Render's paid plans for more resources
• Free tier may struggle with AI model loading

Architecture on Render

┌─────────────────────────────────────┐
│      Render.com Container           │
├─────────────────────────────────────┤
│                                     │
│  ┌───────────────────────────────┐ │
│  │   start.sh / start.py         │ │
│  └──────────┬────────────────────┘ │
│             │                       │
│    ┌────────┴─────────┐            │
│    │                  │            │
│    ▼                  ▼            │
│  ┌──────────┐   ┌──────────────┐  │
│  │Enrichment│   │AI Intelligence│  │
│  │Service   │   │Layer          │  │
│  │:8000     │◄──│:9000          │  │
│  └──────────┘   └──────┬────────┘  │
│                        │            │
└────────────────────────┼────────────┘
                         │
                    Internet
                         │
                    ┌────▼─────┐
                    │ Client   │
                    │(Pi/Web)  │
                    └──────────┘

Next Steps

1. Test locally with ./start.sh
2. Commit and push to GitHub
3. Create Render service
4. Configure environment variables
5. Deploy and monitor logs
6. Update client connection URLs

Good luck! 🎉