The answer is to use the load balancer's built-in 'request_count' metric. This is the most straightforward approach because Google Cloud HTTP(S) load balancers automatically expose this metric through Cloud Monitoring, providing the number of active requests per backend instance without requiring any custom instrumentation, agents, or code changes to your stateless application. On the Google Professional Cloud Developer exam, this question tests your understanding of managed observability features versus custom solutions—a common trap is overcomplicating the answer by suggesting Stackdriver agents or application-level logging when a native metric already exists. Remember that for stateless apps behind a load balancer, Google Cloud handles the heavy lifting; you just need to know which metric name to query. A helpful memory tip: think of "request_count" as the load balancer’s built-in headcount—it counts active requests per instance for you, no extra setup required.
PCD Managing application performance monitoring Practice Question
This PCD practice question tests your understanding of managing application performance monitoring. 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.
A company runs a stateless application on Compute Engine behind a load balancer. They want to monitor the number of active requests per instance without adding custom instrumentation. What is the most straightforward approach?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use the load balancer's built-in 'request_count' metric.
Option D is correct because the load balancer's built-in 'request_count' metric directly provides the number of active requests per instance without requiring any additional instrumentation or agents. This metric is automatically collected by Cloud Monitoring for Google Cloud HTTP(S) load balancers, making it the most straightforward approach for a stateless application on Compute Engine.
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.
✗
Configure the Cloud Monitoring agent to collect request metrics.
Install the Cloud Logging agent and parse access logs.
Why it's wrong here
Log-based approach is less efficient and not real-time.
✗
Deploy Prometheus and instrument the application.
Why it's wrong here
Overkill for simple request counting.
✓
Use the load balancer's built-in 'request_count' metric.
Why this is correct
This metric is available without additional agents.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between agent-based monitoring (Cloud Monitoring agent) and built-in managed service metrics (load balancer metrics), where candidates mistakenly assume an agent is required for any application-level metric, ignoring that Google Cloud's managed services automatically expose relevant metrics.
Detailed technical explanation
How to think about this question
The load balancer's 'request_count' metric is part of the `loadbalancing.googleapis.com` metric family, specifically the `https/request_count` metric for HTTP(S) load balancers, which counts requests at the load balancer level. For per-instance breakdown, you can use the `https/backend_request_count` metric filtered by `backend_instance_name` or `backend_instance_group`. This metric is collected by Google Cloud's telemetry infrastructure without any agent, leveraging Envoy proxy data for the load balancer's backend service.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
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.
Managing application performance monitoring — This question tests Managing application performance monitoring — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use the load balancer's built-in 'request_count' metric. — Option D is correct because the load balancer's built-in 'request_count' metric directly provides the number of active requests per instance without requiring any additional instrumentation or agents. This metric is automatically collected by Cloud Monitoring for Google Cloud HTTP(S) load balancers, making it the most straightforward approach for a stateless application on Compute Engine.
What should I do if I get this PCD 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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