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Question 165 - SAP-C01 discussion

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A company is operating a large customer service call center, and stores and processes call recordings with a custom application. Approximately 2% of the call recordings are transcribed by an offshore team for quality assurance purposes. These recordings take up to 72 hours to be transcribed. The recordings are stored on an NFS share before they are archived to an offsite location after 90 days. The company uses Linux servers for processing the call recordings and managing the transcription queue. There is also a web application for the quality assurance staff to review and score call recordings. The company plans to migrate the system to AWS to reduce storage costs and the time required to transcribe calls. Which set of actions should be taken to meet the company’s objectives?

A.
Upload the call recordings to Amazon S3 from the call center. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days. Use an AWS Lambda trigger to transcribe the call recordings with Amazon Transcribe.Use Amazon S3, Amazon API Gateway, and Lambda to host the review and scoring application.
Answers
A.
Upload the call recordings to Amazon S3 from the call center. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days. Use an AWS Lambda trigger to transcribe the call recordings with Amazon Transcribe.Use Amazon S3, Amazon API Gateway, and Lambda to host the review and scoring application.
B.
Upload the call recordings to Amazon S3 from the call center. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days. Use an AWS Lambda trigger to transcribe the call recordings with Amazon Mechanical Turk. Use Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer to host the review and scoring application.
Answers
B.
Upload the call recordings to Amazon S3 from the call center. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days. Use an AWS Lambda trigger to transcribe the call recordings with Amazon Mechanical Turk. Use Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer to host the review and scoring application.
C.
Use Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer to host the review and scoring application. Upload the call recordings to this application from the call center and store them on an Amazon EFS mount point. Use AWS Backup to archive the call recordings after 90 days. Transcribe the call recordings with Amazon Transcribe.
Answers
C.
Use Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer to host the review and scoring application. Upload the call recordings to this application from the call center and store them on an Amazon EFS mount point. Use AWS Backup to archive the call recordings after 90 days. Transcribe the call recordings with Amazon Transcribe.
D.
Upload the call recordings to Amazon S3 from the call center and put the object key in an Amazon SQS queue. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days. Use Amazon EC2 instances in an Auto Scaling group to send the recordings to Amazon Mechanical Turk for transcription. Use the number of objects in the queue as the scaling metric. Use Amazon S3, Amazon API Gateway, and AWS Lambda to host the review and scoring application.
Answers
D.
Upload the call recordings to Amazon S3 from the call center and put the object key in an Amazon SQS queue. Set up an S3 lifecycle policy to move the call recordings to Amazon S3 Glacier after 90 days. Use Amazon EC2 instances in an Auto Scaling group to send the recordings to Amazon Mechanical Turk for transcription. Use the number of objects in the queue as the scaling metric. Use Amazon S3, Amazon API Gateway, and AWS Lambda to host the review and scoring application.
Suggested answer: A
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asked 16/09/2024
Andrey Scherbakov
39 questions
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