AI-200 Containerized AI Workloads Practice Question
You are deploying an AI workload to AKS and want to ensure that pods belonging to your application are distributed across different fault domains (availability zones) for high availability. Which Kubernetes feature should you configure?
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
✓
Topology spread constraints
Topology spread constraints allow you to configure how pods are spread across failure domains such as regions, zones, or nodes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Resource quotas
Why it's wrong here
Resource quotas limit aggregate resource consumption per namespace.
- ✓
Topology spread constraints
Why this is correct
Topology spread constraints ensure high availability by distributing pods across availability zones.
- ✗
Node taints and tolerations
Why it's wrong here
Taints and tolerations restrict which nodes pods can schedule onto, not zone balancing.
- ✗
Horizontal Pod Autoscaler
Why it's wrong here
HPA scales replica counts based on metrics, not zone distribution.
About these practice questions
This AI-200 question is part of Courseiva's 507-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.