AI-102 Implement generative AI solutions Practice Question
You are building a generative AI solution using Azure OpenAI Service. You want to deploy the model to a specific Azure region to minimize latency for users in Europe. Which deployment parameter must you set?
⚠ Common exam trap
It's easy for candidates to confuse deployment parameters (region, capacity, model version) with inference parameters (temperature, max tokens), leading them to select temperature or model version as the answer for minimizing latency.
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 Azure region of the Azure OpenAI resource.
The Azure region of the Azure OpenAI resource directly determines the physical data center location where the model is deployed. By selecting a region in or near Europe (e.g., France Central, Sweden Central, UK South), you minimize network round-trip latency for European users. The region is set at the resource creation level and cannot be changed after deployment.
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 model version (e.g., 0613).
Why it's wrong here
Model version is not location-specific.
- ✗
The temperature parameter.
Why it's wrong here
Temperature controls randomness.
- ✓
The Azure region of the Azure OpenAI resource.
Why this is correct
Region determines physical location.
- ✗
The deployment name.
Why it's wrong here
Deployment name is arbitrary.
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Senior Network & Security Engineer · founder of Courseiva
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