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Model monitoring in production: drift, decay, and alerting
A conventional service usually fails loudly. It times out, returns an error, exhausts memory, or stops responding.
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Keeping an XGBoost model honest: drift monitoring, champion/challenger, and retraining cadence
An XGBoost model can remain perfectly healthy from an infrastructure perspective while becoming operationally wrong. The endpoint still returns 200 OK . Latency stays flat. CPU and memory look normal.