MLOps & AI Deployment

MLOps is the discipline that connects AI model development with production reliability. Practitioners learn to build CI/CD pipelines for models, implement A/B testing and canary deployments for AI features, set up monitoring for model drift and performance degradation, manage model versioning and rollback, and optimize inference costs as traffic grows. The discipline has expanded in 2026 to include LLMOps-specific practices such as prompt versioning, token cost tracking, and latency optimization for real-time AI applications.