- A
Use AWS Compute Optimizer to get recommendations for instance type and size changes.
AWS Compute Optimizer analyzes historical metrics (such as CPU and memory utilization) and recommends instance type and size changes to improve cost-effectiveness while targeting performance. Given sustained low CPU and no sustained memory pressure, this is the most direct first step to identify a smaller/fewer-overprovisioned instance configuration that can maintain performance.
- B
Increase the instance size to reduce the risk of performance regression.
Why wrong: If average CPU is already very low (12%) and there is no sustained memory pressure, increasing the instance size would likely increase cost without providing needed performance benefits. This directly contradicts the evidence of underutilization.
- C
Switch to Spot Instances immediately to reduce cost regardless of utilization.
Why wrong: Switching to Spot could reduce cost, but the question’s evidence indicates a sizing/overprovisioning issue (low utilization). The best first step is to address the primary inefficiency—right sizing—before switching purchase models. Spot also introduces the possibility of interruptions, which is unnecessary if the workload can be optimized through sizing alone.
- D
Disable detailed monitoring to lower CloudWatch charges.
Why wrong: Reducing monitoring cost is usually a minor optimization compared with compute savings. Also, detailed monitoring might still be needed to make accurate rightsizing decisions. The main cost driver indicated by the metrics is idle/overprovisioned compute, which requires sizing analysis rather than lowering monitoring granularity.
Quick Answer
The answer is to use AWS Compute Optimizer for right-sizing EC2 instances. This is correct because Compute Optimizer leverages machine learning to analyze historical CloudWatch metrics, including CPU utilization, memory pressure, and I/O patterns, to generate specific recommendations for instance type and size changes. In this scenario, with average CPU utilization at only 12% and no sustained memory pressure, Compute Optimizer will identify that the current instance is over-provisioned and suggest a smaller, more cost-effective instance that still meets performance needs. On the SAA-C03 exam, this question tests your understanding of cost optimization strategies and the specific tool designed for right-sizing—a common trap is to jump to manual instance changes or reserved instances without first analyzing utilization data. Remember, Compute Optimizer is the first step for any right-sizing decision because it provides data-driven, actionable recommendations. Memory tip: "Compute Optimizer cuts the cost by crunching the metrics first."
SAA-C03 Design Cost-Optimized Architectures Practice Question
This SAA-C03 practice question tests your understanding of design cost-optimized architectures. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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.
An EC2 workload runs in one region on a single instance type. For the last month, CloudWatch metrics show average CPU utilization of 12% and no sustained memory pressure. The team wants to reduce cost while maintaining the current performance level. What is the best first step?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Clue:
"first"Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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 AWS Compute Optimizer to get recommendations for instance type and size changes.
AWS Compute Optimizer analyzes historical utilization metrics (CPU, memory, I/O) and provides actionable recommendations for right-sizing instances. Given the average CPU utilization of only 12% and no memory pressure, Compute Optimizer will likely recommend a smaller instance type or family that matches the workload's actual resource needs, reducing cost without affecting performance.
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 AWS Compute Optimizer to get recommendations for instance type and size changes.
Why this is correct
AWS Compute Optimizer analyzes historical metrics (such as CPU and memory utilization) and recommends instance type and size changes to improve cost-effectiveness while targeting performance. Given sustained low CPU and no sustained memory pressure, this is the most direct first step to identify a smaller/fewer-overprovisioned instance configuration that can maintain performance.
Clue confirmation
The clue words "best", "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the instance size to reduce the risk of performance regression.
Why it's wrong here
If average CPU is already very low (12%) and there is no sustained memory pressure, increasing the instance size would likely increase cost without providing needed performance benefits. This directly contradicts the evidence of underutilization.
- ✗
Switch to Spot Instances immediately to reduce cost regardless of utilization.
Why it's wrong here
Switching to Spot could reduce cost, but the question’s evidence indicates a sizing/overprovisioning issue (low utilization). The best first step is to address the primary inefficiency—right sizing—before switching purchase models. Spot also introduces the possibility of interruptions, which is unnecessary if the workload can be optimized through sizing alone.
- ✗
Disable detailed monitoring to lower CloudWatch charges.
Why it's wrong here
Reducing monitoring cost is usually a minor optimization compared with compute savings. Also, detailed monitoring might still be needed to make accurate rightsizing decisions. The main cost driver indicated by the metrics is idle/overprovisioned compute, which requires sizing analysis rather than lowering monitoring granularity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may think increasing instance size (Option B) is a safe 'performance buffer' move, but the question explicitly asks to reduce cost while maintaining current performance, making right-sizing via Compute Optimizer the logical first step.
Detailed technical explanation
How to think about this question
AWS Compute Optimizer uses machine learning to analyze CloudWatch metrics (CPU, memory, network throughput) over a lookback period of up to 93 days. It compares observed utilization against the performance characteristics of over 400 instance types, factoring in burstable vs. non-burstable families, and provides savings estimates (e.g., 't3.medium' instead of 't3.large'). For workloads with sustained low CPU, it often recommends moving to a smaller size or a different family (e.g., from 'm5.large' to 't3.medium') that can handle the same load at lower hourly cost.
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 Cost-Optimized Architectures — This question tests Design Cost-Optimized Architectures — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use AWS Compute Optimizer to get recommendations for instance type and size changes. — AWS Compute Optimizer analyzes historical utilization metrics (CPU, memory, I/O) and provides actionable recommendations for right-sizing instances. Given the average CPU utilization of only 12% and no memory pressure, Compute Optimizer will likely recommend a smaller instance type or family that matches the workload's actual resource needs, reducing cost without affecting performance.
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.
Are there clue words in this question I should notice?
Yes — watch for: "best", "first". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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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