Question:
A company is migrating a document processing workload to AWS. The company has updated many applications to natively use the Amazon S3 API to store, retrieve, and modify documents that a processing server generates at a rate of approximately 5 documents every second. After the document processing is finished, customers can download the documents directly from Amazon S3. During the migration, the company discovered that it could not immediately update the processing server that generates many documents to support the S3 API. The server runs on Linux and requires fast local access to the files that the server generates and modifies. When the server finishes processing, the files must be available to the public for download within 30 minutes. Which solution will meet these requirements with the LEAST amount of effort? A. Migrate the application to an AWS Lambda function. Use the AWS SDK for Java to generate, modify, and access the files that the company stores directly in Amazon S3. B. Set up an Amazon S3 File Gateway and configure a file share that is linked to the document store. Mount the file share on an Amazon EC2 instance by using NFS. When changes occur in Amazon S3, initiate a RefreshCache API call to update the S3 File Gateway. C. Configure Amazon FSx for Lustre with an import and export policy. Link the new file system to an S3 bucket. Install the Lustre client and mount the document store to an Amazon EC2 instance by using NFS. D. Configure AWS DataSync to connect to an Amazon EC2 instance. Configure a task to synchronize the generated files to and from Amazon S3.
Author: Jorge SoroceAnswer:
Set up an Amazon S3 File Gateway and configure a file share that is linked to the document store. Mount the file share on an Amazon EC2 instance by using NFS. When changes occur in Amazon S3, initiate a RefreshCache API call to update the S3 File Gateway.
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