A company has 6 ■■ of labeled training data stored on an Amazon FSx for NetApp ONTAP SVM in the same VPC as Amazon SageMaker. An ML engineer must make that training data accessible to SageMaker training jobs. Which option meets this requirement?

Mounting the FSx for ONTAP file system directly onto the SageMaker instance allows SageMaker training jobs to access the data as if it were local storage. This is a common and efficient method for SageMaker to utilize file-based datasets within the same VPC. Creating an S3 bucket and using Mountpoint for Amazon S3 to link it to FSx for ONTAP is an indirect and unnecessary step; the data is already on a file system accessible within the VPC. SageMaker Data Wrangler is a data preparation tool, not a direct data source connector for training jobs in this context. It's designed for interactive data preparation, not for directly providing file system access to training jobs. Establishing a direct connection from SageMaker Data Wrangler to FSx for ONTAP is not a standard or supported method for training job data access.