An ML pipeline built with AWS Step Functions includes Lambda functions. An SQS queue provides model parameters to train models, and trained models are uploaded to S3. The developer wants to run and test the pipeline locally without making real SQS or S3 service calls. Which option meets this need?

The correct answer is to use AWS Step Functions Local and mock the service integrations. AWS Step Functions Local allows you to run and test your Step Functions state machines on your local machine. By mocking the SQS and S3 service integrations, you can simulate their behavior without making actual API calls, which is crucial for local development and testing. Using Amazon CodeGuru Profiler is incorrect because it's a profiling tool for performance analysis, not for local execution and mocking of service integrations. Using the AWS Step Functions Local Docker image is a good start, but it doesn't inherently mock the SQS and S3 integrations. You still need to configure the mocking separately. Using the AWS SAM CLI is incorrect because while it's excellent for locally testing individual Lambda functions and serverless applications, it doesn't provide a direct way to run and mock an entire Step Functions workflow with its integrated services.