What is MLOps?

MLOps is the set of practices for reliably deploying, monitoring, and maintaining machine-learning systems in production — the ML equivalent of DevOps. It covers data and feature pipelines, model versioning, automated training/evaluation, deployment, monitoring for drift and performance, and rollback. The key difference from traditional software: ML systems depend on data that changes, so they degrade silently over time and need continuous monitoring and retraining, not just code deployment.