Which solution meets these requirements?
Set up AWS Auto Scaling to scale out the ECS service when there are timeouts on the ALB. Set up AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.
Set up AWS Auto Scaling to scale out the ECS service when the ALB CPU utilization is too high. Setup AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.
Set up AWS Auto Scaling to scale out the ECS service when the service’s CPU utilization is too high. Set up AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.
Set up AWS Auto Scaling to scale out the ECS service when the ALB target group CPU utilization is too high. Set up AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.
Explanations:
Scaling based on ALB timeouts is not a good indicator of resource issues. Auto Scaling for the ECS service should be based on CPU or memory utilization metrics, not on timeouts.
Scaling based on ALB CPU utilization is incorrect. The CPU utilization of the ALB itself doesn’t directly indicate whether the ECS service or instances need scaling.
Scaling based on ECS service CPU utilization is appropriate. The ECS service should scale out when CPU utilization is too high. Additionally, scaling the ECS cluster based on resource reservation (CPU or memory) is a valid approach.
ALB target group CPU utilization is not the right metric for scaling ECS services. ECS scaling should be based on the service’s or container instance’s CPU or memory utilization.
I chart that the answer is:
Set up AWS Auto Scaling to scale out the ECS service when the service’s CPU utilization is too high. Set up AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.