Databricks GENAI-ASSOC Evaluation and Monitoring Guide

Study Databricks GENAI-ASSOC Evaluation and Monitoring: key concepts, common traps, and exam decision cues.

The exam ends with the discipline that keeps GenAI systems from drifting out of control. Databricks expects you to know how to evaluate quality, choose metrics, trace behavior, use logging, and monitor live systems with cost and safety in mind.

Work this domain in order

Lesson Focus
6.1 Metrics, Judges & Tracing Learn how Databricks tests evaluation metrics, judges, custom scorers, tracing, and expert feedback loops.
6.2 Logging, Gateway & Cost Learn the current Databricks monitoring and operations surfaces for live GenAI systems.

Fast routing inside this chapter

If the question is really about… Go first to…
evaluation metrics, scorers, judges, tracing, or SME feedback 6.1 Metrics, Judges & Tracing
live endpoint behavior, inference logging, AI Gateway, or cost controls 6.2 Logging, Gateway & Cost

What strong answers usually do

  • separate offline evaluation from live monitoring
  • choose metrics and judges that match the deployment scenario
  • use monitoring to learn from live behavior, not only to count tokens

In this section

Revised on Sunday, May 10, 2026