AWS Certified Machine Learning Engineer – Associate (MLA-C01) — Question 74

A company is planning to use Amazon SageMaker to make classification ratings that are based on images. The company has 6 ТВ of training data that is stored on an Amazon FSx for NetApp ONTAP system virtual machine (SVM). The SVM is in the same VPC as SageMaker.
An ML engineer must make the training data accessible for ML models that are in the SageMaker environment.
Which solution will meet these requirements?

Answer options

• A. Mount the FSx for ONTAP file system as a volume to the SageMaker Instance.
• B. Create an Amazon S3 bucket. Use Mountpoint for Amazon S3 to link the S3 bucket to the FSx for ONTAP file system.
• C. Create a catalog connection from SageMaker Data Wrangler to the FSx for ONTAP file system.
• D. Create a direct connection from SageMaker Data Wrangler to the FSx for ONTAP file system.

Correct answer: A

Explanation

The correct solution is to mount the FSx for ONTAP file system as a volume to the SageMaker Instance, which allows direct access to the training data within the SageMaker environment. Options B, C, and D do not provide the direct access needed for training models since they rely on additional connections or setups that do not directly integrate the file system with SageMaker.