AIF-C01 Applications of Foundation Models Practice Question

Exhibit

Refer to the exhibit.

CloudWatch Log message:
{
  "timestamp": "2025-02-12T10:15:30.000Z",
  "message": "ThrottlingException: Rate exceeded for modelId anthropic.claude-v2. RequestId: abc123",
  "logGroup": "/aws/bedrock/modelinvocations",
  "logStream": "modelinvocations/us-west-2/123456789012"
}

Refer to the exhibit. A developer sees this error when calling Amazon Bedrock for inference. What is the MOST likely cause and recommended solution?

⚠ Common exam trap

Many candidates confuse a throttling error with a model ID or prompt length issue, because the error message may not explicitly state 'throttling' and instead show a generic 'ServiceUnavailable' or 'TooManyRequests' response, leading them to incorrectly modify the model or prompt instead of implementing retry logic.

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

✓

The request rate exceeds the model's throughput limit; implement retries with exponential backoff

The error indicates a throttling exception from Amazon Bedrock, which occurs when the request rate exceeds the model's throughput limit. The recommended solution is to implement retries with exponential backoff to handle transient rate limits gracefully, as this aligns with AWS best practices for managing API call limits.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
The model ID is incorrect; use a different model
Why it's wrong here
The model ID is valid; the error is throttling, not invalid ID.
✗
The prompt is too long; reduce the number of tokens in the prompt
Why it's wrong here
The error mentions rate exceeded, not token length.
✓
The request rate exceeds the model's throughput limit; implement retries with exponential backoff
Why this is correct
Throttling is due to rate limits; exponential backoff handles it.
✗
Increase the max_tokens_to_sample value
Why it's wrong here
Increasing max tokens would not fix throttling; it may increase latency.

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AIF-C01 Applications of Foundation Models Practice Question

Exhibit

Why each option matters

Option-by-option breakdown

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