Improve Auto Scaling Responsiveness for Traffic Spikes
A company runs a web application on Amazon EC2 instances behind an Application Load Balancer (ALB). They have configured an Auto Scaling group with a dynamic scaling policy based on CPU utilization. During a traffic spike, the Auto Scaling group launches new instances, but users report slow response times. What should the company do to improve the scaling responsiveness?
Quick Answer
The answer is to implement scheduled scaling actions to add capacity before known peak times. This is correct because scheduled scaling proactively adjusts the desired capacity of the Auto Scaling group based on predictable traffic patterns, such as daily business hours or marketing events, which directly addresses the need to improve Auto Scaling responsiveness for traffic spikes without waiting for dynamic thresholds to be breached. On the AWS Certified Solutions Architect Professional SAP-C02 exam, this scenario tests your understanding of the difference between reactive and proactive scaling strategies; a common trap is to assume that simply lowering the CPU utilization threshold or switching to step scaling will solve latency during sudden spikes, but those are still reactive measures that suffer from the inherent lag of instance launch times. Remember the memory tip: “Predict the peak, schedule the fleet”—if you know the spike is coming, don’t wait for the alarm, use scheduled actions to pre-warm capacity.
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
✓
Implement scheduled scaling actions to add capacity before known peak times.
Scheduled scaling can proactively add capacity before known peak times, preventing slow response times during traffic spikes. Option A is incorrect because decreasing the CPU utilization threshold would cause the Auto Scaling group to scale out sooner, which could help with responsiveness but may lead to over-provisioning and increased costs; however, it does not address the slow response times during a spike that has already started. Option B is incorrect because increasing the cooldown period delays subsequent scaling actions, making the system less responsive during a spike. Option D is incorrect because step scaling with a higher step adjustment is still a reactive measure; it does not add capacity before the spike and may cause abrupt scaling that could overshoot.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Decrease the CPU utilization threshold for scale-out.
Why it's wrong here
Lowering threshold would cause more frequent scaling but still reactive.
- ✗
Increase the cooldown period for the Auto Scaling group.
Why it's wrong here
Increasing cooldown delays scaling, making it slower to respond.
- ✓
Implement scheduled scaling actions to add capacity before known peak times.
Why this is correct
Scheduled scaling proactively adds capacity based on expected traffic.
- ✗
Change the scaling policy to step scaling with a higher step adjustment.
Why it's wrong here
Step scaling is reactive, not proactive.
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Same concept, more angles
1 more way 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 development team deploys a web application on Amazon EC2 instances behind an Application Load Balancer. The application experiences intermittent 503 errors. A Solutions Architect notices that the errors coincide with high CPU utilization on the EC2 instances. What is the MOST effective way to improve the application's availability?
easy- A.Increase the idle timeout setting on the Application Load Balancer.
- B.Decrease the health check interval on the Application Load Balancer.
- ✓ C.Configure an Auto Scaling group for the EC2 instances with a scaling policy based on average CPU utilization.
- D.Use larger EC2 instance types to handle the load.
Why C: An Auto Scaling group with a scaling policy based on average CPU utilization dynamically adds or removes EC2 instances to handle load spikes, reducing 503 errors. Option A is wrong because increasing the idle timeout on the ALB does not address high CPU utilization on the instances. Option B is wrong because decreasing the health check interval may cause premature instance replacement without resolving the underlying capacity issue. Option D is wrong because using larger instance types may help but does not provide dynamic scaling and may be less cost-effective; it does not automatically adjust to fluctuating demand.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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