Evaluation and Monitoring — Databricks Certified Generative AI Engineer Associate

The official DATABRICKS documentation our Evaluation and Monitoring practice questions are cited to. Review the primary sources, then practise.

Official references for this objective

Databricks — The 52x Multiplier: How Zepto Mastered AI Agent Evaluation at Scale | Databricks

establishing “Evaluation as Infrastructure”—covering LLM-as-a-Judge calibration, strategic sampling, and automated feedback loops
Databricks — Agent as a Judge: Scaling AI Evaluation for the Agentic Era | Databricks

running on Phoenix’s own production traces
Databricks — Stop Guessing, Start Scoring: LLM Extraction Evaluation on Databricks | Databricks

we use managed MLflow, custom scorers, and a Databricks App with Lakebase to capture SME feedback and structured ground truth