A company is planning to use Amazon SageMaker to make classification ratings that are based on images. The company has 6 衣 of training data that is stored on an Amazon FSx for NetApp ONTAP system…

Question

Options

• AMount the FSx for ONTAP file system as a volume to the SageMaker Instance.
• BCreate an Amazon S3 bucket. Use Mountpoint for Amazon S3 to link the S3 bucket to the FSx for
• CCreate a catalog connection from SageMaker Data Wrangler to the FSx for ONTAP file system.
• DCreate a direct connection from SageMaker Data Wrangler to the FSx for ONTAP file system.

• A
  70% (42)
• B
  5% (3)
• C
  17% (10)
• D
  8% (5)

Explanation

Option A is correct because SageMaker training jobs support mounting FSx for NetApp ONTAP file systems as input channels when the SVM resides in the same VPC - this gives the training instance direct, low-latency access to the 6 TB of image data without copying it elsewhere.

Option B is wrong because it introduces an unnecessary S3 intermediary; copying 6 TB to S3 adds cost, latency, and complexity when a direct mount already works. Mountpoint for S3 is also a tool for accessing S3 as a file system, not for bridging S3 to FSx.

Options C and D are both wrong because SageMaker Data Wrangler is a data preparation UI tool (for feature engineering, data cleaning, etc.) - it does not offer catalog or direct connections to FSx for ONTAP file systems, and it is not the right service for feeding raw training data into a model.

Memory tip: "Same VPC = direct mount." Whenever SageMaker and a storage system (FSx, EFS) share a VPC, the exam answer is almost always the direct mount - no S3 middleman, no wrong tool (Data Wrangler).

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