Deploy AI Models on Render
Complete guide to deploying AI models on Render with managed services
Deploy AI Models on Render
Render provides fully managed infrastructure for deploying AI models with automatic scaling.
Prerequisites
- Render account
- GitHub/GitLab repository
- Docker knowledge (optional)
- Basic understanding of web services
Deployment Options
1. Web Service
For API endpoints:
# render.yaml
services:
- type: web
name: ai-model-api
env: python
buildCommand: pip install -r requirements.txt
startCommand: uvicorn app:app --host 0.0.0.0 --port $PORT
envVars:
- key: PYTHON_VERSION
value: 3.10.0
- key: HUGGING_FACE_TOKEN
sync: false
instance_count: 2
instance_size_slug: professional-s
2. Background Worker
For async processing:
services:
- type: worker
name: ai-model-worker
env: python
buildCommand: pip install -r requirements.txt
startCommand: python worker.py
3. Docker Deployment
FROM python:3.10-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
EXPOSE 8000
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]
Configuration
Environment Variables
Add via Render Dashboard:
- HUGGING_FACE_TOKEN
- MODEL_NAME
- MAX_BATCH_SIZE
- CACHE_DIR
Health Checks
@app.get("/health")
async def health_check():
return {"status": "healthy"}
Persistent Disks
Attach disks for model caching:
services:
- type: web
name: ai-model
disk:
name: model-cache
mountPath: /app/cache
sizeGB: 50
Auto-Scaling
Configure in Render Dashboard:
- Minimum instances: 1
- Maximum instances: 10
- CPU threshold: 70%
- Memory threshold: 80%
Monitoring
- View real-time logs
- Monitor resource usage
- Set up alerts
- Track deployment history
Cost Optimization
- Use appropriate instance types
- Enable auto-scaling
- Implement caching
- Optimize Docker images
- Use spot instances for dev
Production Checklist
- [ ] Set up custom domain
- [ ] Configure SSL/TLS
- [ ] Add environment variables
- [ ] Attach persistent disks
- [ ] Configure auto-scaling
- [ ] Set up health checks
- [ ] Enable monitoring
- [ ] Configure backups
- [ ] Set up CI/CD
- [ ] Document deployment
Related Guides
Deploy AI Models on AWS
Complete guide to deploying open-source AI models on Amazon Web Services
Deploy AI Models on Google Cloud Platform
Complete guide to deploying open-source AI models on GCP
Deploy AI Models on Microsoft Azure
Complete guide to deploying open-source AI models on Azure
Deploy AI Models with Docker
Complete guide to containerizing and deploying AI models with Docker