Deploying AI Applications to Production
Deploying AI Applications to Production
An AI demo is not a production system. Deployment requires security, monitoring, and scalability planning.
1) Backend API Layer
- Never expose API keys in frontend
- Implement authentication
- Rate limit requests
2) Containerization
Use Docker to ensure consistent environments across staging and production.
3) Monitoring
- Log requests and responses
- Track error rates
- Monitor latency
4) Scaling Strategy
Use load balancers and autoscaling infrastructure.
5) Summary
Deployment transforms experimental AI into reliable enterprise systems.
