Explanation:
Correct Answer: B
Why Option B is Correct:
AWS Step Functions with Human Approval Step: AWS Step Functions provides built-in support for human approval workflows through the waitForTaskToken API. This allows the workflow to pause and wait for human intervention, which is exactly what's needed for human technician review of AI recommendations.
Built-in Human Review Capabilities: Step Functions has native integration with AWS services for human approval workflows, making it easier to implement and maintain compared to building a custom solution.
Audit Trail: The workflow can be designed to automatically store review decisions in a persistent data store (like Amazon DynamoDB or Amazon S3) as part of the workflow execution, ensuring all human review decisions are captured for audit purposes.
Scalability and Reliability: Step Functions provides managed state machines that are highly available and scalable, which is important for handling potentially large volumes of elevator maintenance recommendations.
Why Option A is Not Optimal:
Custom Solution Complexity: Building a custom workflow with Lambda functions and SQS queues requires more development effort and maintenance overhead.
Missing Built-in Human Approval: While it's possible to build human approval workflows with Lambda and SQS, it lacks the native human approval capabilities that Step Functions provides.
State Management: Managing workflow state across multiple Lambda functions and SQS queues is more complex and error-prone compared to using Step Functions' managed state machines.
Key Requirements Met by Option B:
Additional Considerations:
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An elevator service company has developed an AI assistant application by using Amazon Bedrock. The application generates elevator maintenance recommendations to support the company's elevator technicians. The company uses Amazon Kinesis Data Streams to collect the elevator sensor data.
New regulatory rules require that a human technician must review all AI-generated recommendations. The company needs to establish human oversight workflows to review and approve AI recommendations. The company must store all human technician review decisions for audit purposes.
Which solution will meet these requirements?
A
Create a custom approval workflow by using AWS Lambda functions and Amazon SQS queues for human review of AI recommendations. Store all review decisions in Amazon DynamoDB for audit purposes.
B
Create an AWS Step Functions workflow that has a human approval step that uses the waitForTaskToken API to pause execution. After a human technician completes a review, use an AWS