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Answer: Use Amazon Redshift Serverless to automatically process the analytics workload.
Option B is CORRECT because using Amazon Redshift Serverless allows the data engineer to automatically handle the analytics workload without the need to manually manage the infrastructure. Redshift Serverless automatically provisions the necessary resources to handle the workload and scales down when not in use, minimizing operational overhead and simplifying the overall process.
Author: Ritesh Yadav
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Question 44/60
A data engineer uses Amazon Redshift to run resource-intensive analytics processes once every month. Every month, the data engineer creates a new Redshift provisioned cluster.
The data engineer deletes the Redshift provisioned cluster after the analytics processes are complete every month. Before the data engineer deletes the cluster each month, the data engineer unloads backup data from the cluster to an Amazon S3 bucket.
The data engineer needs a solution to run the monthly analytics processes that does not require the data engineer to manage the infrastructure manually.
Which solution will meet these requirements with the LEAST operational overhead?
A
Use Amazon Step Functions to pause the Redshift cluster when the analytics processes are complete and to resume the cluster to run new processes every month.
B
Use Amazon Redshift Serverless to automatically process the analytics workload.
C
Use the AWS CLI to automatically process the analytics workload.
D
Use AWS CloudFormation templates to automatically process the analytics workload.
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