Q36 — AWS SAA-C03 Ch.7

Question 36 of 65 | ← Chapter 7

Q466. A company runs an internal browser-based application. The application runs on Amazon EC2 instances behind an Application Load Balancer. The instances run in an Amazon EC2 Auto Scaling group across multiple Availability Zones. The Auto Scaling group scales up to 20 instances during work hours, but scales down to 2 instances overnight. Staff are complaining that the application is very slow when the day begins, although it runs well by mid-morning.How should the scaling be changed to address the staff complaints and keep costs to a minimum?

• A. Implement a scheduled action that sets the desired capacity to 20 shortly before the office opens. ✓
• B. Implement a step scaling action triggered at a lower CPU threshold, and decrease the cooldown period.
• C. Implement a target tracking action triggered at a lower CPU threshold, and decrease the cooldown period.
• D. Implement a scheduled action that sets the minimum and maximum capacity to 20 shortly before the office opens.

Correct Answer: A. Implement a scheduled action that sets the desired capacity to 20 shortly before the office opens.

Explanation

争议题，A 或者 CTo address the issue of the application being slow at the start of the workday while keeping costs to a minimum, we need to consider a scaling strategy that can preemptively handle the expected increase in load. Let's evaluate the options provided:A. Implement a scheduled action that sets the desired capacity to 20 shortly before the office opens.This option directly addresses the issue by ensuring that the required number of instances (20) are available before the start of the workday. This avoids the delay caused by the Auto Scaling group gradually scaling up during peak demand, which could be the reason for the initial slowness.B. Implement a step scaling action triggered at a lower CPU threshold, and decrease the cooldown period.Step scaling adjusts capacity based on the measured performance metrics like CPU utilization. While this can be effective, it is reactive rather than proactive. The application will still experience slowness until the CPU threshold is reached and scaling actions are triggered. Decreasing the cooldown period might cause over-scaling if the metrics fluctuate rapidly.C. Implement a target tracking action triggered at a lower CPU threshold, and decrease the cooldown period.Target tracking scaling adjusts capacity to maintain a specific target metric value, such as CPU utilization. Like step scaling, this is reactive and may not prevent initial slowness. Decreasing the cooldown period again poses the risk of over-reactive scaling.D. Implement a scheduled action that sets the minimum and maximum capacity to 20 shortly before the office opens.Setting both the minimum and maximum capacity to 20 ensures that the system can't scale down below 20 instances, but it also prevents any further scaling up if the load exceeds the capacity of 20 instances. This is less flexible and potentially risky if the load exceeds expectations.Considering the need to preemptively handle the expected load increase and the importance of keeping costs in check, option A is the most suitable. It ensures that the required number of instances are available before the demand spikes, addressing the slowness issue without the need for excessive reactive scaling, which could lead to higher costs if not managed properly.Answer: A. Implement a scheduled action that sets the desired capacity to 20 shortly before the office opens.