AWS Certified Solutions Architect Professional · Free Practice Question Hard

Question 11

A company developed a pilot application by using AWS Elastic Beanstalk and Java. To save costs during development, the company's development team deployed the application into a single-instance environment. Recent tests indicate that the application consumes more CPU than expected. CPU utilization is regularly greater than 85%, which causes some performance bottlenecks. A solutions architect must mitigate the performance issues before the company launches the application to production. Which solution will meet these requirements with the LEAST operational overhead?
  • A Modify the existing environment’s capacity configuration to use a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the average CPU utilization is over 85% for 5 minutes.
  • B Create a second Elastic Beanstalk environment. Apply the traffic-splitting deployment policy. Specify a percentage of incoming traffic to direct to the new environment in the average CPU utilization is over 85% for 5 minutes.
  • C Create a new Elastic Beanstalk application. Select a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the maximum CPU utilization is over 85% for 5 minutes.
  • D Select the Rebuild environment action with the load balancing option. Select an Availability Zones. Add a scale-out rule that will run if the sum CPU utilization is over 85% for 5 minutes.
Reveal correct answer

Correct answer: C

Explanation

To address the performance issues caused by high CPU utilization in the pilot application developed using AWS Elastic Beanstalk and Java, the solutions architect should modify the existing environment’s capacity configuration to use a load-balanced environment type. This involves selecting all Availability Zones and adding a scale-out rule that triggers if the average CPU utilization exceeds 85% for 5 minutes. This solution meets the requirements with the least operational overhead.

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