SAA-C03 Design High-Performing Architectures Practice Question
A startup runs a stateless web application on a fleet of Amazon EC2 instances in an Auto Scaling group behind an Application Load Balancer. Traffic is steady during business hours, but the team has configured the scaling policy with a target tracking metric of average CPU utilization at 50 percent. Users report intermittent 5xx errors during sudden traffic surges. Which change will most directly improve the application's ability to absorb rapid traffic increases?
⚠ Common exam trap
The trap here is assuming that any Auto Scaling policy will react quickly enough, when scheduled scaling cannot respond to unplanned spikes and a higher CPU target actually delays scale-out.
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
✓
Add a step scaling policy that reacts to Amazon CloudWatch alarms on request count per target and adds capacity in larger increments as the breach grows.
Sudden traffic surges require capacity that reacts to demand quickly and in proportion to the breach. Step scaling with CloudWatch alarms adds instances in larger, tiered increments as the metric worsens, shortening the period where the fleet is undersized. Scheduled scaling fits predictable peaks, and raising the CPU target or tuning deregistration affects cost or scale-in, not surge response.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Enable connection draining on the Application Load Balancer with a long deregistration delay so that in-flight requests complete before instances are removed.
Why it's wrong here
Connection draining improves availability during scale-in by letting in-flight requests finish, but it does nothing to add capacity during a surge. The reported 5xx errors occur during rapid increases, so a scale-in control cannot solve the underlying shortage of healthy targets.
- ✓
Add a step scaling policy that reacts to Amazon CloudWatch alarms on request count per target and adds capacity in larger increments as the breach grows.
Why this is correct
Step scaling responds to CloudWatch alarms with tiered adjustments, so it can add many instances quickly when a metric breaches an upper threshold. This reacts to actual demand rather than a fixed schedule and scales faster than a single target tracking adjustment, which directly reduces the window where capacity lags behind a sudden surge.
- ✗
Switch the Auto Scaling group to a scheduled scaling policy that adds instances at fixed times each morning based on historical traffic patterns.
Why it's wrong here
Scheduled scaling is well suited to predictable daily peaks, but the scenario describes sudden surges that are not tied to a fixed time. A schedule cannot react to an unexpected spike that occurs outside the configured windows, so it would not address the intermittent 5xx errors caused by rapid increases.
- ✗
Increase the target tracking value for average CPU utilization from 50 percent to 80 percent so that existing instances are used more fully before scaling out.
Why it's wrong here
Raising the target utilization tells the group to tolerate higher CPU before adding capacity, which delays scale-out and would worsen 5xx errors during surges. The metric change optimizes cost, not responsiveness, and leaves the fundamental lag between demand and added capacity unchanged.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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