Drift Monitoring
How to detect behavioral drift and quality regression in LLM systems.
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Drift Monitoring
Drift monitoring detects changes in behavior, quality, safety, or cost signals over time.
Enterprise drift monitoring depends on evaluation baselines and controlled rollouts.
See also
Monitoring (LLMOps) Prompt Regression AI Rollback RunbookFAQ
What is drift in LLM systems?
A change in output behavior, quality, safety, or cost patterns over time.
What causes drift?
Model updates, routing changes, data changes, user behavior shifts, or prompt edits.
How do we detect drift?
Continuous sampling + evaluation baselines + alerts on key metrics.
What do we do when drift is detected?
Freeze changes, verify on test sets, rollback, and document evidence.
What’s the first improvement?
Establish a baseline evaluation set and run it regularly.