AI-300 Mlops Infrastructure Practice Question
You want to track your model experiments and compare their performance metrics. Which Azure ML feature provides this capability?
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
✓
Experiments
The Experiments and Run History in Azure ML automatically log and compare metrics across different runs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Environments
Why it's wrong here
Environments define dependencies, not run metrics.
- ✗
Model Registry
Why it's wrong here
The registry manages versions of artifacts, not run-by-run metrics.
- ✗
Compute targets
Why it's wrong here
Compute targets execute the runs, but don't track metrics.
- ✓
Experiments
Why this is correct
Experiments are the standard container for tracking and comparing ML runs.
About these practice questions
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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-300 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-300 exam.