- A
Use scheduled scaling to raise desired capacity before the known newsletter window and lower it afterward.
Scheduled scaling eliminates unnecessary baseline capacity during predictable low-demand periods and ensures extra instances are ready before the spike.
- B
Reduce the instance size to the smallest tested type that still meets peak load.
Right-sizing lowers per-instance cost while preserving performance, as long as the smaller type still passes the real load test.
- C
Keep the current oversized instances to avoid any scaling activity.
Why wrong: This preserves idle capacity and directly conflicts with the goal of reducing cost in a workload with predictable demand patterns.
- D
Replace the Auto Scaling group with Spot Instances only.
Why wrong: Spot Instances can be interrupted, which is risky for a customer-facing web tier that must remain available during newsletter traffic spikes.
- E
Disable ALB health checks to save a small amount of traffic.
Why wrong: Health checks are essential for availability and replacement behavior; removing them does not meaningfully optimize cost and harms resilience.
Quick Answer
The answer is to reduce the instance size to the smallest tested type that still meets peak load and implement scheduled scaling for the predictable traffic spikes. This combination is correct because the spike occurs every weekday at 13:00, making it a textbook case for scheduled scaling, which proactively adjusts capacity before the load arrives rather than reacting to it. By right-sizing the instances, you eliminate the waste of running oversized hardware during the 82% of the week when CPU averages only 18%, while scheduled scaling ensures the smaller fleet can instantly handle the newsletter-driven surge without relying on dynamic policies that might lag. On the SAA-C03 exam, this scenario tests your ability to distinguish between predictive (scheduled) and reactive (dynamic) scaling, with a common trap being to choose dynamic scaling for a pattern that is actually fixed and predictable. Remember the memory tip: if the traffic clock ticks, use scheduled scaling to pick the right instance mix.
SAA-C03 Design Secure Architectures Practice Question
This SAA-C03 practice question tests your understanding of design secure architectures. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
The web tier of an online scheduling app runs on an Auto Scaling group behind an ALB. Traffic spikes every weekday at 13:00 when a corporate newsletter is sent. CloudWatch shows CPU averages 18% outside that window, and the current fleet uses larger instances than the load test requires. The application is stateless and can scale out in a few minutes. Which two changes should the architect recommend? Select two.
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
Use scheduled scaling to raise desired capacity before the known newsletter window and lower it afterward.
Option A is correct because the traffic spike is predictable (every weekday at 13:00), making scheduled scaling the most cost-effective and reliable approach. Scheduled scaling allows you to increase the desired capacity of the Auto Scaling group before the newsletter window and decrease it afterward, ensuring the application can handle the load without relying on dynamic scaling policies that might lag behind the sudden spike. This avoids over-provisioning during non-peak hours while guaranteeing capacity exactly when needed.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 scheduled scaling to raise desired capacity before the known newsletter window and lower it afterward.
Why this is correct
Scheduled scaling eliminates unnecessary baseline capacity during predictable low-demand periods and ensures extra instances are ready before the spike.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Reduce the instance size to the smallest tested type that still meets peak load.
Why this is correct
Right-sizing lowers per-instance cost while preserving performance, as long as the smaller type still passes the real load test.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Keep the current oversized instances to avoid any scaling activity.
Why it's wrong here
This preserves idle capacity and directly conflicts with the goal of reducing cost in a workload with predictable demand patterns.
- ✗
Replace the Auto Scaling group with Spot Instances only.
Why it's wrong here
Spot Instances can be interrupted, which is risky for a customer-facing web tier that must remain available during newsletter traffic spikes.
- ✗
Disable ALB health checks to save a small amount of traffic.
Why it's wrong here
Health checks are essential for availability and replacement behavior; removing them does not meaningfully optimize cost and harms resilience.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume dynamic scaling (e.g., step scaling or target tracking) is always the best choice, but for predictable, recurring traffic patterns, scheduled scaling is more efficient because it proactively adds capacity before the load arrives, avoiding the latency of scaling in response to metrics.
Detailed technical explanation
How to think about this question
Scheduled scaling works by creating recurring actions that modify the Auto Scaling group's desired capacity at specific times, using cron-like expressions (e.g., '0 13 * * 1-5' for weekdays at 13:00 UTC). Under the hood, the Auto Scaling service adjusts the desired capacity before the scheduled time to allow instances to warm up, ensuring they are ready to serve traffic when the spike hits. In real-world scenarios, combining scheduled scaling with dynamic scaling (e.g., target tracking) provides a safety net if the spike is larger than expected.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this SAA-C03 question test?
Design Secure Architectures — This question tests Design Secure Architectures — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use scheduled scaling to raise desired capacity before the known newsletter window and lower it afterward. — Option A is correct because the traffic spike is predictable (every weekday at 13:00), making scheduled scaling the most cost-effective and reliable approach. Scheduled scaling allows you to increase the desired capacity of the Auto Scaling group before the newsletter window and decrease it afterward, ensuring the application can handle the load without relying on dynamic scaling policies that might lag behind the sudden spike. This avoids over-provisioning during non-peak hours while guaranteeing capacity exactly when needed.
What should I do if I get this SAA-C03 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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