SOA-C02 Monitoring, Logging, and Remediation Practice Question
A company runs a web application on Amazon EC2 instances behind an Application Load Balancer (ALB). The SysOps administrator notices that the application's response time is increasing during peak hours. The administrator wants to set up a CloudWatch dashboard that displays the average latency of requests across all instances and the number of healthy hosts. Which metrics should be used?
⚠ Common exam trap
Candidates often confuse 'UnhealthyHostCount' with 'HealthyHostCount' or mistakenly use instance-level metrics (like CPUUtilization) instead of ALB-level metrics, failing to recognize that the ALB's own metrics are the authoritative source for request latency and target health.
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 the ALB's 'TargetResponseTime' metric and the ALB's 'HealthyHostCount' metric.
The ALB's 'TargetResponseTime' metric measures the average time (in seconds) that requests are routed to targets, which directly reflects application latency. The ALB's 'HealthyHostCount' metric shows the number of healthy registered targets, which is the exact metric needed to monitor host health. Together, these two metrics provide the required visibility into average latency and healthy host count across all instances.
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 the ALB's 'TargetResponseTime' metric and the ALB's 'UnhealthyHostCount' metric.
Why it's wrong here
While TargetResponseTime is appropriate for latency, UnhealthyHostCount is the inverse of what you need: a decline in available capacity shows up as a drop in HealthyHostCount, not necessarily a rise in UnhealthyHostCount if the group size also changes. Use HealthyHostCount to observe the number of instances available to serve requests.
- ✓
Use the ALB's 'TargetResponseTime' metric and the ALB's 'HealthyHostCount' metric.
Why this is correct
TargetResponseTime is the ALB metric that tracks the time elapsed from when the load balancer receives a request to when it receives a response from a target. HealthyHostCount reports the number of healthy targets registered with the ALB. Together, a sustained increase in TargetResponseTime combined with a decreasing HealthyHostCount indicates that the application is degrading because fewer instances are available to handle traffic, making this the correct pair for a performance-based scaling alarm.
- ✗
Use the ALB's 'RequestCount' metric and the EC2 Auto Scaling group's 'GroupInServiceInstances' metric.
Why it's wrong here
RequestCount merely counts the total requests received by the ALB; it does not measure delay or response speed, so a rising count can be perfectly healthy if capacity is sufficient. GroupInServiceInstances shows how many Auto Scaling instances are in service, but without a latency metric you cannot correlate that number to poor performance. This pair lacks the latency signal necessary to trigger an alarm on degraded responsiveness.
- ✗
Use the ALB's 'Latency' metric and the EC2 instance's 'CPUUtilization' metric.
Why it's wrong here
The ALB does not expose a 'Latency' metric; that metric name belongs to the classic Elastic Load Balancer, while ALB uses 'TargetResponseTime' to measure request-to-response delay. CPUUtilization is an EC2 instance metric that tracks CPU usage, not the user-perceived latency, and it would need to be aggregated across all instances to represent fleet health. The combination is invalid because one metric does not exist for ALB and the other is a host-level metric rather than a load balancer metric.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SOA-C02 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SOA-C02 exam.