AI-103 Implement Generative AI And Agentic Solutions Practice Question
Which Azure AI Foundry feature helps identify drift in model performance after deployment?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Model Monitoring
Model monitoring tracks performance metrics over time to identify drift.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Model Monitoring
Why this is correct
Monitoring tracks performance and identifies drift.
- ✗
Data Drift Analysis via Compute
Why it's wrong here
Monitoring is the built-in managed service.
- ✗
Prompt Flow Tracing
Why it's wrong here
Tracing is for individual execution analysis.
- ✗
Model Catalog
Why it's wrong here
Catalog is for model selection.
About these practice questions
This AI-103 question is part of Courseiva's 510-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-103 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-103 exam.