AWS Certified Solutions Architect Associate SAA-C03 Practice Question
A tech startup hosts its web application on a fleet of Amazon EC2 instances behind an Application Load Balancer. They experience unpredictable spikes in user traffic and want to ensure that their application scales automatically to maintain performance during peak times. As a Solutions Architect, which metric would you recommend they use to trigger scaling actions to handle increased load effectively?
Use the available memory on the EC2 instances to trigger scaling actions.
Monitor the CPU utilization of the EC2 instances to trigger scaling actions.
Utilize the request count per target from the Application Load Balancer to trigger scaling actions.
Base scaling actions on the average network latency at the Application Load Balancer.
Utilizing the request count per target from the Application Load Balancer to trigger scaling actions is the most effective metric in this scenario. This metric directly reflects the incoming user load and helps ensure that the number of EC2 instances scales in proportion to the demand, maintaining application performance during traffic spikes. Monitoring CPU utilization or available memory on EC2 instances might not accurately capture the need for scaling because resource utilization can vary based on many factors and may not correlate directly with user traffic. Basing scaling actions on network latency at the load balancer is also less effective because latency can be affected by factors other than user load, such as network issues, and may not provide a timely trigger for scaling actions.
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Why is request count per target a better metric than CPU utilization for scaling?