AIP-C01 Question #94: Real Exam Question with Answer & Explanation

Question

A financial services company uses an AI application to process financial documents by using Amazon Bedrock. During business hours, the application handles approximately 10,000 requests each hour, which requires consistent throughput. The company uses the CreateProvisionedModelThroughput API to purchase provisioned throughput. Amazon CloudWatch metrics show that the provisioned capacity is unused while on- demand requests are being throttled. The company finds the following code in the application: response = bedrock_runtime.invoke_model( modelId="anthropic.claude-v2", body=json.dumps(payload) ) The company needs the application to use the provisioned throughput and to resolve the throttling issues. Which solution will meet these requirements?

Options

• AIncrease the number of model units (MUs) in the provisioned throughput configuration.
• BReplace the model ID parameter with the ARN of the provisioned model that the
• CAdd exponential backoff retry logic to handle throttling exceptions during peak hours.
• DModify the application to use the invokeModelWithResponseStream API instead of the

Explanation

Option B is the correct solution because Amazon Bedrock provisioned throughput is only used when the application explicitly invokes the provisioned model ARN, not the base foundation model ID. In the provided code, the application is calling the standard model identifier (anthropic.claude-v2), which routes requests to on-demand capacity instead of the purchased provisioned throughput. When the CreateProvisionedModelThroughput API is used, Amazon Bedrock returns a provisioned model ARN that represents the reserved capacity. Applications must reference this ARN in the modelId parameter when invoking the model. If the base model ID is used instead, Bedrock treats the request as on-demand traffic, which explains why CloudWatch metrics show unused provisioned capacity alongside throttled on-demand requests.

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