AIP-C01 practice question 4 of 15

A global healthcare company is deploying a GenAI application on Amazon Bedrock to produce treatment recommendations. Regulations vary for each…

A global healthcare company is deploying a GenAI application on Amazon Bedrock to produce treatment recommendations. Regulations vary for each country where the company operates. Some countries require the company to retain all model inputs and outputs for 2 years. Other countries require the company to submit data for local audits only. Medical providers require consistent medical terminology across all locations. However, the treatment recommendations that the model produces must adapt to local patient demographics. The solution must also integrate with existing electronic health record (EHR) systems. The application must support up to 10,000 healthcare provider queries every day with sub-second response times. The company must be able to review the application before deployments and approve of prompt changes. The application must produce comprehensive logs for prompts, responses, and user context. Which solution will meet these requirements?

Answer options

A: Use AWS CloudTrail to log API calls. Create standard prompts in Amazon Bedrock Prompt Management that include variables for patient demographics. Implement IAM policies to ensure that only approves users can access prompts.

B: Use Amazon CloudWatch Logs to collect detailed model invocation logs. Store the logs in Amazon S3. Create parameterized prompts in Amazon Bedrock Prompt Management that include variables for treatment options. Enable prompt versioning and set up an approval workflow. Correct answer

C: Create AWS Lambda functions to dynamically generate prompts that enforce clinical language requirements. Use Amazon CloudWatch Logs to track model invocations. Use Amazon SQS queues to implement a prompt approval workflow.

D: Store prompt templates in Amazon S3. Use S3 Object Lock to implement version control. Use Amazon EventBridge to track model invocations. Use AWS Config to monitor changes to prompt templates.

Correct Answer:

B. Use Amazon CloudWatch Logs to collect detailed model invocation logs. Store the logs in Amazon S3. Create parameterized prompts in Amazon Bedrock Prompt Management that include variables for treatment options. Enable prompt versioning and set up an approval workflow.

Explanation

This solution comprehensively addresses all requirements using purpose-built AWS services. Amazon Bedrock's model invocation logging feature can be configured to send detailed logs, including prompts and responses, to Amazon CloudWatch Logs. These logs can then be archived to Amazon S3 to meet the 2-year retention requirement. Amazon Bedrock Prompt Management is designed for creating, managing, and versioning prompts. Using parameterized prompts allows for consistent terminology while variables adapt to local patient demographics. The versioning feature, combined with an organizational process, directly supports the need for an approval workflow before deploying prompt changes, ensuring governance and control.

Why Incorrect

A. AWS CloudTrail logs API management events (e.g., CreatePrompt), not the actual content of prompts and responses, failing the comprehensive logging requirement.
C. Using AWS Lambda for prompt generation and SQS for an approval workflow is overly complex and less manageable than the dedicated Bedrock Prompt Management service.
D. This approach uses services inappropriately. S3 Object Lock is for WORM compliance, not for managing prompt versions, and Bedrock Prompt Management is the superior, purpose-built tool.

References

1. Model Invocation Logging: The Amazon Bedrock User Guide explains how to log model invocations, including prompts and responses, to either Amazon CloudWatch Logs or Amazon S3. This directly supports the logging, auditing, and retention requirements.

Source: AWS Documentation, Amazon Bedrock User Guide, section "Monitor Amazon Bedrock," subsection "Log model invocations."

2. Prompt Management and Versioning: The Amazon Bedrock User Guide details the use of prompt libraries for managing and reusing prompts. It describes creating placeholders (variables) for dynamic content and managing different versions of a prompt, which is essential for the approval workflow and adapting to demographics.

Source: AWS Documentation, Amazon Bedrock User Guide, section "Prompts," subsection "Manage prompts in a library."

3. Long-term Log Retention: The Amazon CloudWatch Logs User Guide describes the process of exporting log data to Amazon S3. This is a standard pattern for cost-effective, long-term retention and archival, fulfilling the 2-year requirement.

Source: AWS Documentation, Amazon CloudWatch Logs User Guide, section "Working with log groups and log streams," subsection "Export log data to Amazon S3."

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