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🚀 Render Deployment Guide - Ciousten V1.3

Complete guide for deploying Ciousten backend on Render.com

📋 Prerequisites

  • GitHub repository with Ciousten code
  • Render.com account (free tier works)
  • OpenRouter API key (for AI features)

🎯 Deployment Steps

1. Connect Repository

  1. Go to Render Dashboard
  2. Click "New +" → "Blueprint"
  3. Connect your GitHub repository
  4. Select Ciousten---Video-Insights---Reports

2. Configure Environment Variables

In Render dashboard, set these environment variables:

Required

OPENROUTER_API_KEY=sk-or-v1-your-key-here

Auto-Configured (from render.yaml)

PORT=8000
PYTHONUNBUFFERED=1
ENVIRONMENT=production
DATA_DIR=/app/data
REPORTS_DIR=/app/reports
LOG_LEVEL=INFO

3. Deploy

  1. Click "Apply" to deploy from blueprint
  2. Wait 5-10 minutes for initial build
  3. Check deployment logs for any errors

✅ Verification

Health Check

curl https://your-app.onrender.com/health

Expected response:

{
  "status": "healthy",
  "version": "1.3.0",
  "system": {
    "cpu_percent": 5.2,
    "memory_percent": 45.3,
    ...
  }
}

API Docs

Visit: https://your-app.onrender.com/docs

Root Endpoint

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

🔧 Configuration Details

Disk Storage

disk:
  name: ciousten-data
  mountPath: /app/data
  sizeGB: 1  # Free tier limit

What's stored:

  • Uploaded videos
  • Processed frames
  • Segmentation results
  • Generated reports

Note: Free tier disk is ephemeral and resets on redeploy

Health Checks

healthCheckPath: /health

Interval: Every 30 seconds
Timeout: 10 seconds
Start Period: 40 seconds
Retries: 3

Auto Deploy

autoDeploy: true
buildFilter:
  paths:
    - backend/**
    - render.yaml

Triggers: Only deploys when backend code or render.yaml changes

🚀 Performance Optimizations

Multi-Stage Docker Build

# Builder stage - compile dependencies
FROM python:3.10-slim as builder
RUN pip install --user -r requirements.txt

# Production stage - minimal image
FROM python:3.10-slim
COPY --from=builder /root/.local /root/.local

Benefits:

  • Smaller image size (~500MB vs ~1GB)
  • Faster deployments
  • Better caching

Uvicorn Configuration

uvicorn app.main:app \
  --host 0.0.0.0 \
  --port ${PORT} \
  --workers 1 \
  --log-level info

Settings:

  • workers 1: Free tier has limited resources
  • log-level info: Balanced logging
  • Dynamic port binding

🔒 Security Features

Environment Variables

  • ✅ API keys not in code
  • ✅ Secrets synced from dashboard
  • ✅ Production environment flag

CORS Configuration

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],  # Configured for public API
    allow_methods=["*"],
    allow_headers=["*"],
)

Rate Limiting

  • Upload: 5 requests/hour
  • Sample: 10 requests/hour
  • Analysis: 10 requests/hour
  • General: 100 requests/hour

📊 Monitoring

Render Dashboard

  • CPU usage
  • Memory usage
  • Request count
  • Response times
  • Error rates

Application Logs

# View logs in Render dashboard
# Or use Render CLI
render logs -f

Health Endpoint

Monitor at: /health

Returns:

  • System metrics (CPU, memory, disk)
  • Service status
  • Active sessions
  • Version info

API Statistics

Monitor at: /api/stats

Returns:

  • Total requests
  • Requests per endpoint
  • Error counts
  • Response times
  • Top endpoints

🐛 Troubleshooting

Build Failures

Issue: Docker build fails
Solution: Check Dockerfile syntax and paths

Issue: Dependency installation fails
Solution: Verify requirements.txt versions

Runtime Errors

Issue: Health check fails
Solution: Check logs for startup errors

Issue: CORS errors
Solution: Verify CORSMiddleware is first

Issue: Sample video not found
Solution: Auto-download feature will handle this

Performance Issues

Issue: Slow responses
Solution: Check CPU/memory usage in dashboard

Issue: Timeouts
Solution: Increase timeout in render.yaml

📈 Scaling

Free Tier Limits

  • Memory: 512 MB
  • CPU: Shared
  • Disk: 1 GB (ephemeral)
  • Bandwidth: 100 GB/month
  • Build Minutes: 500/month

Upgrade Options

Starter Plan ($7/month):

  • 512 MB RAM
  • Persistent disk
  • No sleep on inactivity

Standard Plan ($25/month):

  • 2 GB RAM
  • More CPU
  • Better performance

🔄 CI/CD Pipeline

Automatic Deployment

1. Push to GitHub main branch
2. Render detects changes
3. Builds Docker image
4. Runs health checks
5. Deploys to production
6. Verifies deployment

Manual Deployment

# Trigger manual deploy
render deploy

Rollback

# Rollback to previous version
render rollback

📚 Environment Variables Reference

Required

Variable Description Example
OPENROUTER_API_KEY AI analysis API key sk-or-v1-...

Optional

Variable Description Default
PORT Server port 8000
ENVIRONMENT Environment name production
DATA_DIR Data storage path /app/data
REPORTS_DIR Reports path /app/reports
LOG_LEVEL Logging level INFO

🎯 Best Practices

1. Environment Variables

  • ✅ Use Render dashboard for secrets
  • ✅ Never commit API keys
  • ✅ Use environment-specific configs

2. Logging

  • ✅ Use structured logging
  • ✅ Log important events
  • ✅ Monitor error rates

3. Health Checks

  • ✅ Implement comprehensive health endpoint
  • ✅ Check all critical services
  • ✅ Return detailed status

4. Error Handling

  • ✅ Graceful degradation
  • ✅ User-friendly error messages
  • ✅ Automatic retry for transient errors

5. Performance

  • ✅ Use multi-stage builds
  • ✅ Minimize image size
  • ✅ Cache dependencies
  • ✅ Optimize database queries

🔗 Useful Links

✅ Deployment Checklist

Pre-Deployment

  • Code pushed to GitHub
  • render.yaml configured
  • Dockerfile optimized
  • Environment variables set
  • API keys added to Render

Deployment

  • Blueprint applied
  • Build successful
  • Health check passing
  • Logs reviewed
  • No errors in console

Post-Deployment

  • Test health endpoint
  • Test API endpoints
  • Verify CORS working
  • Check sample video
  • Monitor performance

Production

  • Set up monitoring
  • Configure alerts
  • Document deployment
  • Train team
  • Plan for scaling

🎉 Success Metrics

Deployment

  • ✅ Build time: < 5 minutes
  • ✅ Deploy time: < 2 minutes
  • ✅ Health check: Passing
  • ✅ Uptime: > 99%

Performance

  • ✅ Response time: < 200ms
  • ✅ Error rate: < 1%
  • ✅ CPU usage: < 50%
  • ✅ Memory usage: < 80%

Status: ✅ Production Ready
Version: 1.3.0
Platform: Render.com
Made by: Aditya Shenvi @2025