[Feature] Built-in feature drift detection with alerting
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- Python
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Description
## Description
As a feature store, Feast is in a unique position to detect data drift between training and serving feature distributions. Built-in PSI/KS-test monitoring with configurable alerts would be very valuable.
## Use Case
- Detect when feature distributions shift significantly
- Alert ML engineers before model performance degrades
- Integrate with existing monitoring (Prometheus, Grafana)
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