A Generative AI Engineer is responsible for monitoring a financial RAG assistant that supports real-time trade advisory. Business stakeholders require assurance that: The assistant's advice is grounded in retrieved documents The model output quality remains consistent Any degradation or drift is detected early Which monitoring approach BEST supports these goals in a production-grade Databricks deployment?