AI-102 Plan and manage an Azure AI solution Practice Question
You are deploying an Azure AI solution that uses Azure OpenAI Service. The solution must be deployed in a way that minimizes latency for users in Asia. However, the company's data residency policy requires data to stay in the United States. What should you do?
⚠ Common exam trap
Test-takers frequently assume caching (Option A) or global deployment (Option C) can solve latency without considering data residency, or they mistakenly think deploying in Asia (Option B) is acceptable despite the policy constraint.
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
✓
Deploy the service in a US region and use Azure Front Door with caching to reduce latency.
It satisfies both requirements: data residency (deploying in a US region keeps data within the United States) and latency reduction for Asian users. Azure Front Door with caching stores frequently accessed model responses at edge locations closer to users in Asia, minimizing round-trip time without moving the origin data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Azure CDN to cache the model responses in Asia.
Why it's wrong here
Azure OpenAI Service does not support CDN caching of responses.
- ✗
Deploy the Azure OpenAI Service in an Asian region and use Azure Front Door to route traffic.
Why it's wrong here
Data residency policy prohibits deployment outside US.
- ✗
Deploy the service in multiple regions globally and use Traffic Manager for routing.
Why it's wrong here
Data would leave the US.
- ✓
Deploy the service in a US region and use Azure Front Door with caching to reduce latency.
Why this is correct
Front Door provides low-latency access while keeping data in US.
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