hardMultiple SelectObjective-mapped
AIF-C01 Practice Question: Deploying a generative AI application using…
A company is deploying a generative AI application using Amazon Bedrock and needs to optimize costs. They expect variable traffic with occasional high spikes. Which TWO strategies would help reduce costs while maintaining performance?
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
✓
Enable model caching to serve repeated prompts without re-inference
Model caching reduces cost for repeated queries, and batch inference is cheaper for non-real-time workloads. Provisioned throughput is expensive and not cost-optimal for variable traffic. Fine-tuning and using the largest model increase costs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable model caching to serve repeated prompts without re-inference
Why this is correct
Caching avoids repeated computation for identical requests.
- ✓
Use on-demand inference with batch processing for non-real-time requests
Why this is correct
Batch inference is cheaper than real-time for asynchronous tasks.
- ✗
Always use the largest available foundation model for quality
Why it's wrong here
Larger models are more expensive; right-sizing is better.
- ✗
Use provisioned throughput to handle spikes
Why it's wrong here
Provisioned throughput guarantees capacity but is costly; not cost-optimal for variable traffic.
- ✗
Fine-tune a larger model for better accuracy
Why it's wrong here
Fine-tuning and larger models increase cost.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services 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 AIF-C01 exam.