MLOps

Practices and tools for deploying, monitoring, and maintaining machine learning models in production. MLOps extends DevOps principles to ML — version control for models and data, automated training pipelines, performance monitoring, drift detection, and rollback capabilities. Without MLOps, models deployed to production silently degrade as the real world diverges from training data.