Topic 1 Question 72
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?
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.
Use Amazon Redshift Serverless to automatically process the analytics workload.
Use the AWS CLI to automatically process the analytics workload.
Use AWS CloudFormation templates to automatically process the analytics workload.
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- 正解だと思う選択肢: B
Fully Managed, Serverless: Redshift Serverless eliminates the need to manually create, manage, or delete clusters. It automatically scales resources based on the workload, reducing operational overhead significantly. Cost-Effective for Infrequent Workloads: Since the analytics processes run only once a month, Redshift Serverless's pay-per-use model is ideal for minimizing costs during downtime. Seamless S3 Integration: Redshift Serverless natively integrates with S3 for backup and restore operations, ensuring compatibility with the existing process.
👍 4Christina6662024/10/13 Selected Answer B: Options A, C and D still involve manual tasks like administering CloudFormation stacks, using AWS CLI commands, or configuring Step Function state machines.
By leveraging Redshift Serverless, the data engineer avoids all cluster and infrastructure administration effort. This has the least operational overhead to run the monthly
👍 3Felix_G2024/09/03- 正解だと思う選択肢: B
Use Amazon Redshift Serverless. This option allows the data engineer to focus on the analytics processes themselves without worrying about cluster provisioning, scaling, or management. It provides an on-demand, serverless solution that can handle variable workloads and is cost-effective for intermittent and irregular processing needs like those described.
👍 2rralucard_2024/08/02
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