The answer is to change the statistic to p95 while keeping the threshold at 5 seconds. This is correct because the p95 (95th percentile) statistic filters out the impact of outlier requests—like the small number taking over 30 seconds—that skew the average, giving you a metric that represents the response time experienced by the vast majority of users. On the AWS Certified SysOps Administrator Associate SOA-C02 exam, this scenario tests your understanding of how to avoid false alarms by using percentile statistics in CloudWatch, a common trap being to assume that raising the threshold or increasing evaluation periods is the only fix. The key insight is that percentiles, not averages, reveal true performance degradation for most users. Memory tip: think “p95 for the 95% crowd” — it cuts the outliers and keeps the signal.
SOA-C02 Monitoring, Logging, and Remediation Practice Question
This SOA-C02 practice question tests your understanding of monitoring, logging, and remediation. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
A company runs a critical web application on Amazon EC2 instances in an Auto Scaling group across three Availability Zones. The application uses an Application Load Balancer (ALB) for traffic distribution. The SysOps administrator has configured a CloudWatch alarm to monitor the ALB's `TargetResponseTime` metric, with a threshold of 5 seconds. The alarm triggers when the average response time exceeds 5 seconds for 2 consecutive periods. Recently, the alarm has been triggering frequently during peak hours, but the application team reports that the response time is acceptable and the application is performing normally. The administrator investigates and finds that a small number of requests are taking a very long time (over 30 seconds), skewing the average. The administrator needs to reduce the number of false alarms while still being alerted if the overall application performance degrades. Which course of action should the administrator take?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Change the statistic to p95 and keep the threshold at 5 seconds
The correct answer is A because using the p95 (95th percentile) statistic instead of the average filters out the impact of the small number of outlier requests that take over 30 seconds. The p95 metric shows the response time below which 95% of requests fall, providing a more accurate representation of typical application performance. This reduces false alarms from skewed averages while still alerting if the majority of users experience degraded response times exceeding 5 seconds.
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.
✓
Change the statistic to p95 and keep the threshold at 5 seconds
Why this is correct
p95 excludes the top 5% slowest requests, so it reflects the experience of the majority.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the threshold to 30 seconds
Why it's wrong here
A 30-second threshold would only catch the slowest requests, missing moderate degradation.
✗
Decrease the period to 60 seconds and lower the threshold to 3 seconds
Why it's wrong here
Shorter period and lower threshold increase sensitivity, causing more false alarms.
✗
Increase the evaluation periods to 5 consecutive periods
Why it's wrong here
This would require more consecutive breaches, but the alarm would still be triggered by outliers if they occur in multiple periods.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may think increasing the threshold or evaluation periods is the solution, but they fail to recognize that the average metric is inherently sensitive to outliers, and the correct fix is to change the statistic to a percentile like p95 or p99.
Detailed technical explanation
How to think about this question
The p95 statistic is calculated by sorting all response time data points in a given period and identifying the value below which 95% of the data falls; this is more robust to outliers than the mean. In CloudWatch, percentile metrics are available for ALB `TargetResponseTime` and can be configured directly in the alarm, allowing administrators to monitor the experience of the vast majority of users. This approach is commonly used in production environments to balance sensitivity to real degradation with immunity to rare, long-running requests.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Monitoring, Logging, and Remediation — This question tests Monitoring, Logging, and Remediation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Change the statistic to p95 and keep the threshold at 5 seconds — The correct answer is A because using the p95 (95th percentile) statistic instead of the average filters out the impact of the small number of outlier requests that take over 30 seconds. The p95 metric shows the response time below which 95% of requests fall, providing a more accurate representation of typical application performance. This reduces false alarms from skewed averages while still alerting if the majority of users experience degraded response times exceeding 5 seconds.
What should I do if I get this SOA-C02 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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Question Discussion
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