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A company is developing a solution to analyze images.

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A company is developing a solution to analyze images. The solution uses a 50 TB reference dataset and analyzes images up to 1 TB in size. The solution spreads requests across an Auto Scaling group of Amazon EC2 Linux instances in a VPC. The EC2 instances are attached to shared Amazon EBS io2 volumes in each Availability Zone. The EBS volumes store the reference dataset.

During testing, multiple parallel analyses led to numerous disk errors, which caused job failures. The company wants the solution to provide seamless data reading for all instances.

Which solution will meet these requirements MOST cost-effectively?

A.

Create a new EBS volume for each EC2 instance. Copy the data from the shared volume to the new EBS volume regularly. Update the application to reference the new EBS volume.

B.

Move all the reference data to an Amazon S3 bucket. Install Mountpoint for Amazon S3 on the EC2 instances. Create gateway endpoints for Amazon S3 in the VPC. Replace the EBS mount point with the S3 mount point.

C.

Move all the reference data to an Amazon S3 bucket. Create an Amazon S3 backed Multi-AZ Amazon EFS volume. Mount the EFS volume on the EC2 instances. Replace the EBS mount point with the EFS mount point.

D.

Upgrade the instances to local storage. Copy the data from the shared EBS volume to the local storage regularly. Update the application to reference the local storage.

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