SAP-C03 practice question: AI workload costs (Bedrock tiers, batch inference, caching, cross-Region inference) (2 of 2)
Cost-Optimized Architecture Design A free question from our original SAP-C03 practice exam. Try it, then open the answer to see why each option is right or wrong.
A retailer runs a product-advice assistant on Amazon Bedrock in us-east-1. Traffic is high and steady across the day and night, and shoppers expect answers within a couple of seconds, so the team needs guaranteed capacity for that steady baseline.
During promotions, traffic bursts well above the baseline, and on-demand requests in us-east-1 are throttled. Burst requests may be processed in any US Region but never outside the US.
The team wants no extra capacity commitment for the bursts and no Region-selection logic of its own.
Which TWO designs meet these requirements at the LOWEST cost? (Choose two.)
Choose two answers.
AA. Purchase provisioned throughput for the model sized to the steady baseline, and send the baseline traffic to the provisioned model.
BB. Send all requests, including the shopper-facing ones, through batch inference jobs that run every hour, and read the results when the job finishes.
CC. Send requests that exceed the provisioned throughput through the US geographic cross-Region inference profile for the model, which routes them among US Regions with available capacity.
DD. Purchase provisioned throughput sized to the highest promotion peak, so that every request, including the bursts, runs on dedicated capacity.
EE. Enable model access in us-west-2 as well, and have the application send each burst request to whichever Region returned fewer throttling errors in the previous minute.
Show the answer and explanation
Answers: A, C
A. Right: Correct. Provisioned throughput gives guaranteed capacity for the predictable, round-the-clock baseline. Sizing it to the baseline rather than the peak avoids paying for capacity that sits idle outside promotions.
B. Wrong: Batch inference is for offline work with no interactive response time. Shoppers would wait for the next job, which breaks the couple-of-seconds expectation.
C. Right: Correct. A geographic cross-Region inference profile spreads on-demand requests across US Regions, so bursts are less likely to be throttled and stay within the US. It needs no commitment, and Bedrock chooses the Region, so the team writes no routing logic.
D. Wrong: Peak-sized provisioned throughput covers the bursts, but the retailer pays for that capacity every hour while promotions are occasional. It is also the extra commitment the team wants to avoid.
E. Wrong: This spreads bursts across two US Regions, but the team would write and maintain the Region-selection logic. A cross-Region inference profile does this routing for them.
Explanation
Provisioned throughput sized to the baseline guarantees capacity for steady traffic, and a US cross-Region inference profile absorbs bursts across US Regions with no commitment or custom routing. Hourly batch jobs break the response time, peak-sized provisioned throughput wastes money, and home-made Region selection adds code.
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