How to Access FSx for ONTAP Training Data in SageMaker?

Answer Correct answer: A — Mount the FSx for NetApp ONTAP file system as a volume to the SageMaker instance in the same VPC so training code can read the 6 TB image dataset over NFS.

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?

  1. Mount the FSx for ONTAP file system as a volume to the SageMaker Instance. Correct Answer
  2. Create an Amazon S3 bucket. Use Mountpoint for Amazon S3 to link the S3 bucket to the FSx for ONTAP file system.
  3. Create a catalog connection from SageMaker Data Wrangler to the FSx for ONTAP file system.
  4. Create a direct connection from SageMaker Data Wrangler to the FSx for ONTAP file system.

Community Insight

The question tests how SageMaker gains file-level access to FSx for NetApp ONTAP data; the trap is assuming a Data Wrangler connection or an S3 Mountpoint link replaces a direct NFS mount for training.

Amazon FSx for NetApp ONTAP volumes can be mounted directly to a SageMaker instance in the same VPC, giving ML code NFS access to 6 TB of image training data without copying it into Amazon S3. The correct answer is A because the mount option is the one that actually makes the FSx data available to SageMaker compute.

A common wrong pick is D, assuming SageMaker Data Wrangler can create a direct connection to FSx for ONTAP and that this alone makes the data available to training models. Data Wrangler is a preparation tool, not a training-data mount.

Community Discussion (4 comments)

86a3fbe 👍 1 Selected: D
I think the answer is D. For the option A, FSx for NetApp ONTAP is not listed as built-in support option for SageMaker Training‘s FileSystemDataSource based on its documentation: https://docs.aws.amazon.com/sagemaker/latest/dg/model-access-training-data.html.
pablo_ 👍 1
correct D: Native Data Wrangler → FSx ONTAP → S3 → SageMaker Training Integration incorrect A: Mounts notebook only; does not share SageMaker Training data; ONTAP is not supported as a FileSystemDataSource
rinip86277 👍 1 Selected: A
The direct mount approach (Option A) is the standard and most efficient way to access FSx for ONTAP data from SageMaker instances.
Saransundar 👍 6 Selected: A
https://docs.netapp.com/us-en/netapp-solutions/ai/mlops_fsxn_sagemaker_integration_training.html#introduction Option A would work since you can mount FSx for ONTAP directly to SageMaker, enabling fast access to the 6 TB data in the same VPC without extra steps

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Expert Analysis

Why the Answer Is Correct

Amazon FSx for NetApp ONTAP presents NFS-accessible volumes, and because the SVM resides in the same VPC as the SageMaker environment, a SageMaker notebook or Studio instance can mount that file system as a volume. This gives the ML code on that instance file-level access to the 6 TB image dataset without first copying it into Amazon S3 or routing it through a data-preparation service. Among the listed choices, only the mount option actually exposes the FSx for ONTAP data as a file system to SageMaker compute. The same-VPC detail is the signal that an NFS mount is the intended access path.

Why the Other Options Are Wrong

Option B is backwards: Mountpoint for Amazon S3 mounts an S3 bucket on a compute host, and it does not link an S3 bucket to FSx for ONTAP or expose the ONTAP volume. Options C and D both use SageMaker Data Wrangler, which is a data exploration and preparation tool; a catalog or direct connection there is not a training-data mount for SageMaker models and would still require an export or import step to S3. The distinction between "catalog connection" and "direct connection" does not change that Data Wrangler is the wrong layer for making the FSx volume available to training code. Also, FSx for ONTAP is not one of SageMaker Training's native FileSystemDataSource types, so a Data Wrangler connection is not a substitute for the direct instance mount.

Community Comment Notes

Saransundar links NetApp's SageMaker training integration guide and argues that mounting FSx for ONTAP directly to SageMaker works in the same VPC without extra steps. 86a3fbe and pablo_ push back that FSx for ONTAP is not a built-in SageMaker Training FileSystemDataSource and prefer Data Wrangler; that limitation is real, but it does not turn Data Wrangler into a training-volume mount, and the question asks about access to data in the SageMaker environment. rinip86277 describes the direct mount as the standard, efficient route. The split in comments reflects the trap: the native training data-source list is narrower than the ways you can attach FSx for ONTAP to a SageMaker instance.

Official Reference

Exam Strategy

Look for the same-VPC clue: it enables an NFS mount from SageMaker to FSx for ONTAP. Eliminate options that only connect Data Wrangler or misuse Mountpoint for Amazon S3, because they do not expose the FSx volume as training data to SageMaker compute.

Frequently Asked Questions

Why can't SageMaker Training use FSx for ONTAP as a FileSystemDataSource?

SageMaker Training natively supports Amazon EFS and FSx for Lustre as file-system data sources; FSx for ONTAP is accessed by mounting it to a SageMaker instance in the same VPC instead.

Why is a Data Wrangler catalog connection not enough for training data?

Data Wrangler is a data preparation tool; a catalog or direct connection lets analysts explore FSx for ONTAP data but does not mount the volume for SageMaker training code.

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