What is model monitoring architecture in classification systems?

Model monitoring tracks performance, drift, and system health in deployed classification models.

Monitoring systems collect logs, prediction distributions, feature statistics, latency metrics, and error rates. They detect anomalies using thresholds or ML-based detectors. Monitoring ensures model reliability and triggers retraining pipelines when degradation is detected.