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MLOps & Infrastructure · intermediate · concept 205 of 311 · Updated Nov 4, 2026

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.

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Data driftConcept driftModel degradationAlertingRetrainingTraining-serving skew

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