AI-300 Genaiops Infrastructure Practice Question
A team is scaling a GenAI application that utilizes multiple models via model-as-a-service. You notice that inference requests are being throttled. What is the most effective infrastructure-level adjustment to handle the increased load?
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
✓
Purchase and deploy Provisioned Throughput Units (PTUs) for the specific model deployment.
Provisioned throughput units (PTUs) allow for dedicated capacity, which is the standard way to prevent throttling for high-scale GenAI workloads in Azure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Purchase and deploy Provisioned Throughput Units (PTUs) for the specific model deployment.
Why this is correct
PTUs provide dedicated, guaranteed capacity for high-volume inference, bypassing standard rate limits.
- ✗
Change the model version to a lower-parameter variant.
Why it's wrong here
While this reduces compute, it is a model-level change rather than an infrastructure-level scaling adjustment.
- ✗
Move the deployment to a different subscription within the same Azure region.
Why it's wrong here
Quotas are generally applied at the region/subscription level, so this would not effectively solve throttling.
- ✗
Increase the number of instances in the associated Azure Kubernetes Service (AKS) cluster.
Why it's wrong here
Model-as-a-service does not rely on your own AKS cluster for inference throttling management.
About these practice questions
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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-300 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-300 exam.