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Monitoring, Logging, and Remediation →hardMultiple ChoiceObjective-mapped

Quick Answer

The correct answer is to create a metric filter in CloudWatch Logs to extract error codes and total requests, then build two custom metrics and an alarm using a math expression for the error rate. This approach directly addresses the need for monitoring application 5xx errors from the application logs, because the issue is application-specific rather than load balancer-level. By filtering the log stream for 5xx status codes and total request counts, you can calculate a precise error rate (error count divided by total requests) and trigger an alarm when it exceeds 0.05 over a 5-minute period. On the AWS Certified SysOps Administrator Associate SOA-C02 exam, this scenario tests your understanding of CloudWatch Logs metric filters versus pre-built ALB metrics—a common trap is choosing the ALB’s HTTPCode_ELB_5XX metric, which only reflects load balancer errors, not application-level 5xx responses. Remember the memory tip: “Logs for app errors, ALB for network errors”—if the logs are already flowing, a metric filter is your direct line to custom error rate monitoring.

SOA-C02 Monitoring, Logging, and Remediation Practice Question

This SOA-C02 practice question tests your understanding of monitoring, logging, and remediation. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 a fleet of EC2 instances behind an Application Load Balancer (ALB). The instances are in an Auto Scaling group. The operations team uses CloudWatch alarms to monitor the application's health. Recently, they noticed that the application's error rate has increased sporadically, but the CPU utilization and memory usage remain normal. The team suspects that the issue is related to a specific HTTP endpoint returning 5xx errors. They want to set up monitoring that will alert them when the error rate exceeds 5% of total requests over a 5-minute period. The application logs are already sent to CloudWatch Logs. Which combination of steps should the SysOps administrator take to meet this requirement?

Question 1hardmultiple choice

Read the full NAT/PAT explanation →

A
Create a metric filter in CloudWatch Logs to extract error codes and total requests from the application logs. Create two custom metrics: one for error count and one for total requests. Then create a CloudWatch alarm using a math expression that calculates error rate (error count / total requests) and triggers when >0.05 for 5 minutes.
This directly uses the application logs to compute error rate.
B
Enable AWS X-Ray on the application to trace requests and identify error patterns. Create a CloudWatch alarm on the X-Ray error rate metric.
Why wrong: X-Ray is for tracing, not for counting error rates from logs; it requires code instrumentation.
C
Install the CloudWatch agent on the EC2 instances to collect application-level metrics. Configure the agent to emit a custom metric for error rate. Then create an alarm on that metric.
Why wrong: The application logs are already sent to CloudWatch Logs; installing an agent is redundant and not leveraging existing logs.
D
Enable detailed monitoring on the ALB and create a CloudWatch alarm on the HTTPCode_ELB_5XX metric with a threshold of 5% of the request count. Use the ALB's RequestCount metric to compute the percentage.
Why wrong: The ALB's 5XX metric includes all backend errors, but the issue is application-specific; also, it requires computing percentage with math expressions.

Full breakdown with real-world context →

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 a metric filter in CloudWatch Logs to extract error codes and total requests from the application logs. Create two custom metrics: one for error count and one for total requests. Then create a CloudWatch alarm using a math expression that calculates error rate (error count / total requests) and triggers when >0.05 for 5 minutes.

Option A is correct because it creates a metric filter on the log group to count errors and total requests, then an alarm on the error rate. Option B is wrong because it uses the ALB's HTTPCode_ELB_5XX metric, but the issue is application-specific, not ALB-level. Option C is wrong because it relies on the CloudWatch agent to generate metrics, which is not already set up. Option D is wrong because it uses AWS X-Ray, which is for tracing, not for error rate monitoring from logs.

Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✓
Create a metric filter in CloudWatch Logs to extract error codes and total requests from the application logs. Create two custom metrics: one for error count and one for total requests. Then create a CloudWatch alarm using a math expression that calculates error rate (error count / total requests) and triggers when >0.05 for 5 minutes.
Why this is correct
This directly uses the application logs to compute error rate.
Related concept
Static NAT maps one inside address to one outside address.
✗
Enable AWS X-Ray on the application to trace requests and identify error patterns. Create a CloudWatch alarm on the X-Ray error rate metric.
Why it's wrong here
X-Ray is for tracing, not for counting error rates from logs; it requires code instrumentation.
✗
Install the CloudWatch agent on the EC2 instances to collect application-level metrics. Configure the agent to emit a custom metric for error rate. Then create an alarm on that metric.
Why it's wrong here
The application logs are already sent to CloudWatch Logs; installing an agent is redundant and not leveraging existing logs.
✗
Enable detailed monitoring on the ALB and create a CloudWatch alarm on the HTTPCode_ELB_5XX metric with a threshold of 5% of the request count. Use the ALB's RequestCount metric to compute the percentage.
Why it's wrong here
The ALB's 5XX metric includes all backend errors, but the issue is application-specific; also, it requires computing percentage with math expressions.

Common exam traps

Common exam trap: NAT rules depend on direction and matching traffic

NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.

Detailed technical explanation

How to think about this question

NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.

KKey Concepts to Remember

Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.

TExam Day Tips

Identify inside and outside interfaces first.
Check whether the scenario needs static NAT, dynamic NAT or PAT.
Do not confuse NAT matching ACLs with normal packet-filtering intent.

Key takeaway

NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.

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.

Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related SOA-C02 NAT questions on configuration and troubleshooting.

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FAQ

Questions learners often ask

What does this SOA-C02 question test?

Monitoring, Logging, and Remediation — This question tests Monitoring, Logging, and Remediation — Static NAT maps one inside address to one outside address..

What is the correct answer to this question?

The correct answer is: Create a metric filter in CloudWatch Logs to extract error codes and total requests from the application logs. Create two custom metrics: one for error count and one for total requests. Then create a CloudWatch alarm using a math expression that calculates error rate (error count / total requests) and triggers when >0.05 for 5 minutes. — Option A is correct because it creates a metric filter on the log group to count errors and total requests, then an alarm on the error rate. Option B is wrong because it uses the ALB's HTTPCode_ELB_5XX metric, but the issue is application-specific, not ALB-level. Option C is wrong because it relies on the CloudWatch agent to generate metrics, which is not already set up. Option D is wrong because it uses AWS X-Ray, which is for tracing, not for error rate monitoring from logs.

What should I do if I get this SOA-C02 question wrong?

What is the key concept behind this question?

Static NAT maps one inside address to one outside address.

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