AI-102 Implement generative AI solutions Practice Question
Network Topology
You run the Azure CLI command shown in the exhibit. After a few minutes, the deployment fails with a quota error. What is the most likely cause?
⚠ Common exam trap
The trap here is that candidates might confuse a quota error with a model deprecation or SKU issue, but the error message's explicit mention of 'quota' directly points to capacity limits, not configuration or availability problems.
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
✓
The requested capacity of 10 exceeds the available quota for the gpt-4 model in that region.
The quota error indicates that the requested capacity (10 units) for the gpt-4 model exceeds the available quota in the target region. Azure OpenAI deployments require sufficient model-specific quota, which is region- and model-specific. The error is not related to SKU name validity, model version deprecation, or resource group existence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The SKU name 'Standard' is invalid for Azure OpenAI deployments.
Why it's wrong here
'Standard' is a valid Azure OpenAI SKU name, so it cannot trigger a quota error; the failure stems from insufficient provisioned quota in the subscription or region. It is tempting because SKU validation errors do occur, and choosing a SKU is a genuine deployment step — but SKU validity is checked before quota allocation.
- ✗
The model version '0613' is deprecated and no longer available.
Why it's wrong here
A deprecated model version produces a model-not-found or unsupported-version error, not a quota error; the deployment fails because the subscription lacks available capacity for that model in the region. Version selection matters when retiring models, but deprecation surfaces as a validation failure, not a quota exhaustion.
- ✓
The requested capacity of 10 exceeds the available quota for the gpt-4 model in that region.
Why this is correct
The deployment failed because the requested capacity of 10 exceeds the available quota for the gpt-4 model in that region. Azure OpenAI enforces per-model, per-region capacity quotas, so requesting more than the allotted units triggers a quota error.
- ✗
The resource group name 'myResourceGroup' does not exist.
Why it's wrong here
A missing resource group produces an authorisation or not-found error immediately, not a quota error after several minutes of deployment. It is tempting because resource group existence is a common prerequisite, but quota errors arise from exceeding subscription limits on resources such as vCPUs or public IP addresses.
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JA
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.