AI-103 Plan And Manage AN Azure AI Solution Practice Question
Which TWO techniques are effective for improving the performance of an Azure AI application?
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
✓
Implementing caching for common query results.
Caching and regional proximity (or global distribution) directly improve performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increasing the number of subscription keys.
Why it's wrong here
Adding more keys does not improve performance.
- ✗
Disabling all logging to reduce overhead.
Why it's wrong here
While logging has cost, disabling it doesn't meaningfully impact inference performance.
- ✗
Switching to the 'Free' tier.
Why it's wrong here
The Free tier has lower performance limits.
- ✓
Implementing caching for common query results.
Why this is correct
Caching reduces the need for expensive model inference calls.
- ✓
Deploying the AI resource in a region closer to the end-users.
Why this is correct
Reducing network round-trip time is a primary factor in latency.
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.