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Question:A machine learning (ML) team is building an application that uses data that is in...

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Question:

A machine learning (ML) team is building an application that uses data that is in an Amazon S3 bucket. The ML team needs a storage solution for its model training workflow on AWS. The ML team requires high-performance storage that supports frequent access to training datasets. The storage solution must integrate natively with Amazon S3. Which solution will meet these requirements with the LEAST operational overhead?

Options:

A.

Use Amazon Elastic Block Store (Amazon EBS) volumes to provide high-performance storage. Use AWS DataSync to migrate data from the S3 bucket to EBS volumes.

B.

Use Amazon EC2 ML instances to provide high-performance storage. Store training data on Amazon EBS volumes. Use the S3 Copy API to copy data from the S3 bucket to EBS volumes.

C.

Use Amazon FSx for Lustre to provide high-performance storage. Store training datasets in Amazon S3 Standard storage.

D.

Use Amazon EMR to provide high-performance storage. Store training datasets in Amazon S3 Glacier Instant Retrieval storage.

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