What should a solutions architect do to maintain the desired performance across all instances in the group?
Use a simple scaling policy to dynamically scale the Auto Scaling group.
Use a target tracking policy to dynamically scale the Auto Scaling group.
Use an AWS Lambda function to update the desired Auto Scaling group capacity.
Use scheduled scaling actions to scale up and scale down the Auto Scaling group.
Explanations:
A simple scaling policy may not maintain the desired CPU utilization effectively, as it reacts to changes in metrics without targeting a specific utilization level.
A target tracking policy automatically adjusts the Auto Scaling group based on a specified CPU utilization target (40% in this case), ensuring optimal performance.
While using an AWS Lambda function to update the desired capacity can provide flexibility, it does not dynamically adjust based on real-time CPU utilization, making it less effective for maintaining performance.
Scheduled scaling actions are based on predetermined times and do not respond to actual usage patterns, which can lead to either underutilization or overutilization during varying load conditions.
I figure that the answer is:
Use a target tracking policy to dynamically scale the Auto Scaling group.