AI-102 Plan and manage an Azure AI solution Practice Question
You are responsible for managing costs for multiple Azure AI services in your organization. You notice that provisioned throughput units (PTUs) for Azure OpenAI are not fully utilized. What is the most cost-effective action to optimize spending?
⚠ Common exam trap
It's easy for candidates to confuse PTUs with standard Azure auto-scaling concepts (like VM scale sets) and assume auto-scaling is available for PTUs, when in fact PTUs are a fixed-capacity model that requires manual adjustment or a switch to PAYG for cost optimization.
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
✓
Reduce the number of provisioned PTUs or switch to pay-as-you-go
Provisioned throughput units (PTUs) represent a fixed capacity commitment. If PTUs are underutilized, the most cost-effective action is to reduce the number of PTUs or switch to the pay-as-you-go (PAYG) model, which charges only for tokens consumed. This directly aligns with cost optimization by eliminating the fixed cost of unused capacity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure auto-scaling to reduce PTUs during low usage
Why it's wrong here
Auto-scaling is not available for PTUs; PTUs are a fixed commitment.
- ✗
Move the resource to a different region with lower pricing
Why it's wrong here
Moving regions does not change PTU utilization.
- ✗
Stop the Azure OpenAI service when not in use
Why it's wrong here
You cannot stop the service; it is always provisioned.
- ✓
Reduce the number of provisioned PTUs or switch to pay-as-you-go
Why this is correct
Adjusting PTU commitment to actual usage or using token-based billing reduces costs.
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