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AIP-C01 practice question: GenAI solution design, proofs of concept and the Well-Architected Generative AI Lens (2 of 2)

Foundation Model Integration, Data Management, and Compliance A free question from our original AIP-C01 practice exam. Try it, then open the answer to see why each option is right or wrong.

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A hotel group collects about 30,000 guest reviews across its properties each day. Each night, the group wants a draft reply to every review, written in its own tone, so that front-desk staff can approve and post them in the morning.

No guest is waiting for a reply while it is written, and the group wants the lowest possible cost per reply.

The reviews arrive in a shared storage bucket by early evening, and the drafts must be ready before the first shift starts.

Which solution meets these requirements?

Choose one answer.

  1. A. Use an API Gateway endpoint backed by a Lambda function that calls the model synchronously for each review as it arrives, so every draft is written the moment its review is received.
  2. B. Write the day's reviews as JSONL files to Amazon S3, and have EventBridge Scheduler start an Amazon Bedrock batch inference job each evening that writes the drafts to S3.
  3. C. Deploy an AgentCore Runtime agent that a staff member starts each morning, and have it write one reply at a time as staff open each review.
  4. D. Host an open-weight model on a SageMaker AI real-time endpoint with instances that run around the clock, and send each review to the endpoint as a synchronous request during the night.
Show the answer and explanation

Answer: B

  • A. Wrong: Real-time calls are priced at the on-demand rate and risk throttling when thousands of reviews arrive together. No guest is waiting, so the real-time design costs more than the nightly need requires.
  • B. Right: Batch inference runs asynchronously over a large file set at a lower price than on-demand calls, and a schedule starts it each evening. The drafts are ready before the morning shift, which meets the cost and timing needs. Learn more: Process multiple prompts with batch inference (opens in a new tab)
  • C. Wrong: Writing drafts one at a time during the morning shift is slow and puts the work on staff at the time they need to approve replies. The group wants all drafts ready before the shift starts.
  • D. Wrong: The endpoint would run and bill for instances all day, although it is only used for one night's batch. That idle cost misses the lowest-cost requirement, even though the drafts would be ready on time.

Explanation

Nightly reviews with no waiting guest suit batch inference, which is priced below on-demand calls and can be started on a schedule with the output in S3 before the morning shift. Real-time calls, a staff-driven agent and a round-the-clock endpoint each cost more or run at the wrong time.

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