Quick Answer
Cloud Trace is the correct choice because it is Google Cloud’s managed distributed tracing service designed specifically to capture and analyze API latency across microservices. When requests propagate through services in a GKE environment, Cloud Trace collects trace spans from each service, assembling them into end-to-end request timelines that reveal where delays occur. This directly addresses the need to monitor API latency between services, as it provides the granular, service-level latency breakdown that simple logging or metrics cannot offer. On the Google Professional Cloud Developer exam, this question tests your ability to distinguish between observability tools: Cloud Monitoring handles metrics and alerts, Cloud Logging stores logs, but only Cloud Trace provides distributed tracing for latency analysis. A common trap is choosing Cloud Monitoring because it includes dashboards, but remember that tracing requires span-level data across service boundaries. Memory tip: “Trace the latency trail” — if you need to follow a request hop-by-hop across microservices, think Cloud Trace.
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 deploys a microservices application on Google Kubernetes Engine (GKE). The operations team needs to monitor API latency between services. Which Google Cloud service should they use to trace requests across services?
Error Reporting
Why wrong: Error Reporting aggregates and tracks errors, not latency.
Cloud Logging
Why wrong: Cloud Logging is for storing and querying logs, not tracing requests.
Cloud Monitoring
Why wrong: Cloud Monitoring provides metrics and dashboards, not distributed tracing.
Cloud Trace
Cloud Trace provides distributed tracing to analyze latency across services.
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 Trace
Cloud Trace is the correct choice because it is a distributed tracing system designed to capture latency data as requests propagate through microservices. It provides end-to-end visibility by collecting trace spans from each service, allowing the operations team to identify bottlenecks and measure API latency between services in a GKE environment.
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.
Error Reporting
Why it's wrong here
Error Reporting aggregates and tracks errors, not latency.
Cloud Logging
Why it's wrong here
Cloud Logging is for storing and querying logs, not tracing requests.
Cloud Monitoring
Why it's wrong here
Cloud Monitoring provides metrics and dashboards, not distributed tracing.
Cloud Trace
Why this is correct
Cloud Trace provides distributed tracing to analyze latency across services.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
The trap here is that candidates confuse Cloud Monitoring (metrics) with Cloud Trace (distributed tracing), assuming that latency metrics alone can trace requests across services, but metrics lack the span-level context needed to follow a single request's path.
Detailed technical explanation
Cloud Trace uses the OpenTelemetry standard to instrument applications, collecting trace spans that include timestamps, service names, and metadata. Each span represents a unit of work, and traces are built by linking spans with a trace ID, enabling reconstruction of the full request flow. In a real-world scenario, if a user request times out, Cloud Trace can pinpoint whether the delay is in service A, a database call, or a downstream service, which is impossible with metrics or logs alone.
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
Managing application performance monitoring — This question tests Managing application performance monitoring — Read the scenario before looking for a memorised answer..
The correct answer is: Cloud Trace — Cloud Trace is the correct choice because it is a distributed tracing system designed to capture latency data as requests propagate through microservices. It provides end-to-end visibility by collecting trace spans from each service, allowing the operations team to identify bottlenecks and measure API latency between services in a GKE environment.
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 11, 2026
This PCD practice question is part of Courseiva's free Google Cloud 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 PCD exam.
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