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Question 441 - SAP-C02 discussion

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A data analytics company has an Amazon Redshift cluster that consists of several reserved nodes. The cluster is experiencing unexpected bursts of usage because a team of employees is compiling a deep audit analysis report. The queries to generate the report are complex read queries and are CPU intensive.

Business requirements dictate that the cluster must be able to service read and write queries at all times. A solutions architect must devise a solution that accommodates the bursts of usage.

Which solution meets these requirements MOST cost-effectively?

A.
Provision an Amazon EMR cluster. Offload the complex data processing tasks.
Answers
A.
Provision an Amazon EMR cluster. Offload the complex data processing tasks.
B.
Deploy an AWS Lambda function to add capacity to the Amazon Redshift cluster by using a classic resize operation when the cluster's CPU metrics in Amazon CloudWatch reach 80%.
Answers
B.
Deploy an AWS Lambda function to add capacity to the Amazon Redshift cluster by using a classic resize operation when the cluster's CPU metrics in Amazon CloudWatch reach 80%.
C.
Deploy an AWS Lambda function to add capacity to the Amazon Redshift cluster by using an elastic resize operation when the cluster's CPU metrics in Amazon CloudWatch reach 80%.
Answers
C.
Deploy an AWS Lambda function to add capacity to the Amazon Redshift cluster by using an elastic resize operation when the cluster's CPU metrics in Amazon CloudWatch reach 80%.
D.
Turn on the Concurrency Scaling feature for the Amazon Redshift cluster.
Answers
D.
Turn on the Concurrency Scaling feature for the Amazon Redshift cluster.
Suggested answer: C

Explanation:

The best solution is to deploy an AWS Lambda function to add capacity to the Amazon Redshift cluster by using an elastic resize operation when the cluster's CPU metrics in Amazon CloudWatch reach 80%. This solution will enable the cluster to scale up or down quickly by adding or removing nodes within minutes. This will improve the performance of the complex read queries and also reduce the cost by scaling down when the demand decreases. This solution is more cost-effective than using a classic resize operation, which takes longer and requires more downtime. It is also more suitable than using Amazon EMR, which is designed for big data processing rather than data warehousing.Reference:Amazon Redshift Documentation,Resizing clusters in Amazon Redshift, [Amazon EMR Documentation]

asked 16/09/2024
annalise ramdin
36 questions
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