SAP-C02 Continuous Improvement for Existing Solutions Practice Question
A company runs a critical web application on EC2 instances behind an Application Load Balancer. The instances are in an Auto Scaling group with a dynamic scaling policy based on average CPU utilization. After a recent deployment, users report intermittent timeouts. CloudWatch metrics show CPU utilization spikes to 90% before scaling out, but the new instances take 5 minutes to become healthy. What is the MOST effective solution to reduce timeouts during traffic spikes?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Decrease the cooldown period and set a lower CPU utilization threshold for scale-out
By decreasing the cooldown period and lowering the CPU utilization threshold for scale-out, the Auto Scaling group reacts faster to rising CPU usage. The lower threshold triggers a scale-out action before CPU reaches 90%, and the reduced cooldown allows new instances to start sooner after the previous scaling activity. This addresses the 5-minute startup lag by ensuring new instances are launched earlier in the spike, reducing the window of timeouts. Option A (scheduled scaling) only helps for predictable spikes, not intermittent ones. Option B (pre-warming the load balancer) is not a standard AWS feature and does not reduce instance startup time. Option D (predictive scaling) still has the same startup delay and requires historical data.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a scheduled scaling policy to add instances before expected peak times
Why it's wrong here
Scheduled scaling is not reactive to unpredictable spikes.
- ✗
Pre-warm the load balancer to reduce latency
Why it's wrong here
Pre-warming is not a standard AWS feature and does not address EC2 startup time.
- ✓
Decrease the cooldown period and set a lower CPU utilization threshold for scale-out
Why this is correct
This triggers scale-out earlier and reduces the time to launch new instances.
- ✗
Switch to predictive scaling
Why it's wrong here
Predictive scaling still has the same startup delay for new instances.
Go deeper
Related to this question
About these practice questions
This SAP-C02 question is part of Courseiva's 1,660-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on SAP-C02
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company uses AWS Elastic Beanstalk to deploy a web application. The application experiences increased traffic, and the environment's Auto Scaling group is not scaling out quickly enough. What should a solutions architect do to improve the scaling response?
easy- A.Decrease the CPU utilization threshold for scale-out alarms.
- B.Increase the minimum number of instances in the Auto Scaling group.
- ✓ C.Reduce the cooldown period for the Auto Scaling group.
- D.Use a larger instance type to handle more traffic.
Why C: Reducing the cooldown period allows the Auto Scaling group to react faster to increased traffic, enabling quicker scale-out. Option A is incorrect because decreasing the CPU utilization threshold for scale-out alarms would cause the group to scale out at lower CPU levels, potentially scaling out sooner but not necessarily improving the speed of response. Option B is incorrect because increasing the minimum number of instances does not speed up scaling; it only ensures a higher baseline capacity. Option D is incorrect because using larger instance types handles more traffic per instance but does not improve the scaling response time.
Variation 2. A company runs a web application on AWS Elastic Beanstalk. The application experiences periodic traffic spikes that cause the environment to scale out. However, the scaling is slow, leading to increased latency during spikes. The operations team wants to improve the responsiveness of the Auto Scaling group. The application is stateless and runs on a single instance type. What should a solutions architect recommend?
easy- A.Configure the Auto Scaling group to use multiple instance types.
- B.Use scheduled scaling to add capacity before expected spikes.
- ✓ C.Decrease the Auto Scaling group's cooldown period.
- D.Change the instance type to a larger size.
Why C: Decrease the Auto Scaling group's cooldown period. Decreasing the cooldown period allows the Auto Scaling group to launch new instances more quickly after a scaling activity, reducing the time it takes to respond to traffic spikes. This directly improves responsiveness. Option A is incorrect because using multiple instance types does not speed up scaling decisions. Option B (scheduled scaling) is proactive but does not help with unexpected spikes. Option D (larger instance type) addresses capacity per instance but not the speed of scaling out.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SAP-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SAP-C02 exam.