Câu 19: AWS Certified Generative AI Developer - Professional AIP-C01

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: python 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?

1. A. Increase the number of model units (MUs) in the provisioned throughput configuration.
2. B. Replace the model ID parameter with the ARN of the provisioned model that the CreateProvisionedModelThroughput API returns. — đáp án hiện tại
3. C. Add exponential backoff retry logic to handle throttling exceptions during peak hours.
4. D. Modify the application to use the InvokeModelWithResponseStream API instead of the InvokeModel API.