MLS-C01 Question #41: Real Exam Question with Answer & Explanation

Question

A Machine Learning Specialist is using an Amazon SageMaker notebook instance in a private subnet of a corporate VPC. The ML Specialist has important data stored on the Amazon SageMaker notebook instance's Amazon EBS volume, and needs to take a snapshot of that EBS volume. However, the ML Specialist cannot find the Amazon SageMaker notebook instance's EBS volume or Amazon EC2 instance within the VPC. Why is the ML Specialist not seeing the instance visible in the VPC?

Options

• AAmazon SageMaker notebook instances are based on the EC2 instances within the customer
• BAmazon SageMaker notebook instances are based on the Amazon ECS service within customer
• CAmazon SageMaker notebook instances are based on EC2 instances running within AWS service
• DAmazon SageMaker notebook instances are based on AWS ECS instances running within AWS

Explanation

{"question_number": 7, "question_summary": "Why a SageMaker notebook instance is not visible in the customer's VPC", "correct_answer": "C", "explanation": "Amazon SageMaker notebook instances run on EC2 instances that exist within AWS-managed service accounts, not within the customer's own AWS account or VPC. When you configure a notebook instance to connect to a customer VPC, AWS injects an Elastic Network Interface (ENI) into the customer's VPC subnet - this ENI is visible - but the underlying EC2 host machine itself resides in AWS's infrastructure and is not visible to the customer. This is why the ML Specialist cannot find the EC2 instance or EBS volume in their VPC console. To take an EBS snapshot, the correct path is through the SageMaker console or API (e.g., creating a lifecycle configuration to automate backups), not directly through the EC2 console.", "generated_by": "claude-sonnet", "llm_judge_score": 4}

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