AIF-C01 Applications of Foundation Models Practice Question
A startup uses Amazon Bedrock with a provisioned throughput to generate product images. They now have unpredictable traffic and want to reduce costs. What should they do?
⚠ Common exam trap
Many exam-takers assume provisioned throughput is always more cost-effective for any workload, overlooking that on-demand mode is specifically designed to eliminate idle costs for unpredictable traffic patterns.
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
✓
Switch to on-demand mode in Amazon Bedrock.
On-demand mode in Amazon Bedrock allows you to pay per inference request without committing to a provisioned throughput, making it ideal for unpredictable traffic patterns. This eliminates the cost of idle capacity while still providing access to the same foundation models. Option D directly addresses the need to reduce costs when traffic is variable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch to batch inference using Amazon Bedrock.
Why it's wrong here
Batch is not designed for real-time image generation and may not support image models.
- ✗
Keep the provisioned throughput but reduce the number of units.
Why it's wrong here
Reducing units still incurs fixed cost for lower throughput.
- ✗
Use a different model or service like Amazon SageMaker with spot instances.
Why it's wrong here
SageMaker requires managing infrastructure and spot instances are not guaranteed.
- ✓
Switch to on-demand mode in Amazon Bedrock.
Why this is correct
On-demand mode is serverless and cost-effective for variable traffic.
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