This PCA practice question tests your understanding of ensure solution and operations reliability. 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 developer wants to monitor a custom application metric from their application running on GKE. What should they use?
Cloud Logging
Why wrong: Cloud Logging is for log data, not metrics.
Cloud Trace
Why wrong: Cloud Trace is for distributed tracing of requests.
Cloud Debugger
Why wrong: Cloud Debugger inspects running code state.
Cloud Monitoring custom metrics API
The custom metrics API allows ingesting and monitoring custom application metrics.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Cloud Monitoring custom metrics API
Cloud Monitoring custom metrics API (option D) is the correct choice because it allows a developer to push custom application-specific metrics (e.g., request latency, queue depth) from a GKE pod using the `custom.googleapis.com` metric domain. This integrates directly with Cloud Monitoring for alerting and dashboards, whereas Cloud Logging is for log data, not metrics.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Cloud Logging
Why it's wrong here
Cloud Logging is for log data, not metrics.
Cloud Trace
Why it's wrong here
Cloud Trace is for distributed tracing of requests.
Cloud Debugger
Why it's wrong here
Cloud Debugger inspects running code state.
Cloud Monitoring custom metrics API
Why this is correct
The custom metrics API allows ingesting and monitoring custom application metrics.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates confuse Cloud Logging (for logs) with Cloud Monitoring (for metrics), or assume that Cloud Trace can handle custom metrics because it deals with application performance data.
Detailed technical explanation
Under the hood, the Cloud Monitoring custom metrics API uses the `timeSeries.create` method to write metric data points to a custom metric descriptor. The developer must first create a metric descriptor via the API or gcloud command, then push data points with a Unix timestamp and value (e.g., gauge or cumulative). In a real-world scenario, a GKE application might use the OpenTelemetry SDK to export custom metrics to the Monitoring API, enabling autoscaling based on application-specific load.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Ensure solution and operations reliability — This question tests Ensure solution and operations reliability — Read the scenario before looking for a memorised answer..
The correct answer is: Cloud Monitoring custom metrics API — Cloud Monitoring custom metrics API (option D) is the correct choice because it allows a developer to push custom application-specific metrics (e.g., request latency, queue depth) from a GKE pod using the `custom.googleapis.com` metric domain. This integrates directly with Cloud Monitoring for alerting and dashboards, whereas Cloud Logging is for log data, not metrics.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 25, 2026
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