AI-200 Containerized AI Workloads Practice Question
Which TWO of the following techniques help optimize the performance of containerized AI models in AKS?
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
✓
Tune pod resource limits and requests.
Resource tuning and node selection are the most effective ways to optimize 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.
- ✓
Tune pod resource limits and requests.
Why this is correct
Ensures optimal resource utilization.
- ✗
Disable all logging.
Why it's wrong here
This hinders debugging and is not a performance optimization.
- ✗
Use the standard CNI instead of Azure CNI.
Why it's wrong here
Azure CNI is generally better for performance in AKS.
- ✗
Increase the replica count to 100 for all services.
Why it's wrong here
Causes resource starvation and inefficiency.
- ✓
Use dedicated node pools for GPU tasks.
Why this is correct
Avoids resource contention with non-AI tasks.
About these practice questions
This AI-200 question is part of Courseiva's 503-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-200 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-200 exam.