Which solution will meet these requirements with the LEAST operational overhead?
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.
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.
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.
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.
Explanations:
Creating a new application and a load-balanced environment introduces more operational overhead due to the need to manage two separate applications.
While traffic-splitting can help manage load, it doesn’t directly address the CPU utilization issue and adds complexity by requiring management of multiple environments.
Modifying the existing environment to be load-balanced with a scale-out rule allows for efficient resource management and directly addresses the high CPU utilization, minimizing operational overhead.
Rebuilding the environment with load balancing does not necessarily solve the CPU issue effectively, and the option to check “sum CPU utilization” is less straightforward than “average,” leading to potential mismanag
I estimate that the answer is:
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.