AI-102 Plan and manage an Azure AI solution Practice Question
A company is deploying a solution using Azure AI Vision to analyze images of products on a retail website. They need to ensure that the image analysis is performed within a specific geographic boundary for data residency compliance. What should they configure?
⚠ Common exam trap
Many exam-takers confuse network isolation (private endpoints) with data residency, or assume that replication or tier changes can alter where data is stored, when in fact the region of the resource itself is the sole determinant for compliance.
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 Azure AI Vision resource in the desired Azure region
Azure AI Vision resources are regional Azure resources, meaning all data processing and storage occur within the Azure region where the resource is deployed. By deploying the resource in the desired geographic region, you ensure that image analysis and any derived data remain within that boundary, satisfying data residency compliance requirements. This is the fundamental mechanism for controlling data location in Azure AI services.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Deploy the Azure AI Vision resource in the desired Azure region
Why this is correct
Deploying the Azure AI Vision resource in the target Azure region keeps image processing and stored data within that geography, satisfying the data residency constraint. Regional deployment determines where inference occurs; unlike global endpoints, no cross-geography replication happens. Microsoft Entra ID governs access but does not affect processing location.
- ✗
Create a private endpoint for the Vision resource
Why it's wrong here
A private endpoint gives private IP connectivity over Azure Private Link; it does not change the region where image analysis executes. It is the right choice for blocking public network access, whereas residency requires deploying the Vision resource in the permitted geography.
- ✗
Enable multi-region replication on the Vision resource
Why it's wrong here
Multi-region replication copies data across regions but does not pin processing to one boundary; it widens the geographic footprint. It suits disaster recovery and read locality, not residency. A single-region deployment in the required geography satisfies the compliance requirement.
- ✗
Use the Free tier of Azure AI Vision
Why it's wrong here
The Free tier changes pricing and quota limits, not where inference runs; requests still execute in the resource's region. It is tempting for cost control during prototyping, but residency depends on the resource's location, not its pricing tier.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 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-102 exam.