MLOps & Infrastructure · intermediate · concept 140 of 176

⚙️ML Monitoring & Observability

Watching ML models in production for degradation. Models decay over time as data distributions shift. Monitoring detects data drift, concept drift, and performance drops before they impact users. Training-serving skew, features computed differently offline and online, is the classic silent killer here.