SAA-C03 Design Cost-Optimized Architectures Practice Question
A digital agency runs a web application on a fleet of Amazon EC2 instances behind an Application Load Balancer. Traffic is steady and predictable during business hours but drops to near zero overnight and on weekends. The operations team wants to reduce compute costs without impacting availability during peak periods. They cannot modify the application code and must keep the same instance types. What should a solutions architect recommend?
⚠ Common exam trap
The trap here is assuming that a Reserved Instance or Savings Plan reduces cost for a workload that is idle half the time, when in fact commitments bill for the full term regardless of utilization.
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
✓
Create an Auto Scaling group with a scheduled scaling policy that scales the desired capacity up before business hours and down after hours.
The workload has a predictable daily and weekly pattern, so the most direct cost control is to align capacity with demand. A scheduled scaling policy changes desired capacity at known times, terminating instances when traffic is near zero and adding them back before the peak. This avoids paying for idle capacity while keeping the application available when users need it, and it requires no application changes.
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 burstable T3 instances and rely on CPU credits to absorb the peak traffic periods.
Why it's wrong here
Burstable instances earn CPU credits when idle and spend them during bursts, which can help with short spikes. However, the scenario describes a predictable daily and weekly pattern with a sustained busy period, not brief bursts. Relying on credits does not reduce the number of running instances during the idle periods, so the primary cost driver of paying for unused overnight and weekend capacity remains.
- ✗
Switch the fleet to Spot Instances and configure the Auto Scaling group to maintain the same desired capacity at all times.
Why it's wrong here
Spot Instances offer large discounts but can be reclaimed by AWS with a two-minute interruption notice, which is risky for a customer-facing application that must remain available. Keeping the desired capacity constant also fails to address the idle overnight and weekend periods, so the fleet would still run at full size when traffic is near zero, defeating the cost-reduction objective.
- ✗
Purchase a 1-year Standard Reserved Instance for each instance and leave the fleet running 24/7.
Why it's wrong here
Reserved Instances provide a discount in exchange for a commitment to a specific instance family and Region for the term, but they do not stop billing when the instances are idle. Because the workload drops to near zero overnight and on weekends, paying for continuous coverage wastes money on hours when no capacity is needed, so this does not achieve the goal of reducing compute costs for an intermittent workload.
- ✓
Create an Auto Scaling group with a scheduled scaling policy that scales the desired capacity up before business hours and down after hours.
Why this is correct
Scheduled scaling lets you increase or decrease the desired capacity of an Auto Scaling group based on a date and time, which matches a workload with a known, repeating peak pattern. Scaling in overnight and on weekends terminates unneeded instances, so you pay only for the capacity actually required, while scaling out before business hours preserves availability during peak traffic.
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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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