This GCDL practice question tests your understanding of scaling with google cloud operations. 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 developer is troubleshooting a slow response from a Cloud Run service. Which Google Cloud service can they use to trace requests across microservices?
Cloud Profiler
Why wrong: Profiler focuses on CPU and memory usage, not request traces.
Cloud Trace
Cloud Trace collects latency data from distributed systems.
Cloud Logging
Why wrong: Logging provides log entries but not trace context unless using Cloud Trace.
Cloud Debugger
Why wrong: Debugger captures snapshots of code, not request traces.
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 service because it is specifically designed for distributed tracing, collecting latency data from applications and displaying it in a trace timeline. It can trace requests as they propagate across multiple microservices, including Cloud Run services, by using trace context propagation headers (e.g., `X-Cloud-Trace-Context`). This allows the developer to identify bottlenecks and slow components in a request path.
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 Profiler
Why it's wrong here
Profiler focuses on CPU and memory usage, not request traces.
Cloud Trace
Why this is correct
Cloud Trace collects latency data from distributed systems.
Related concept
Read the scenario before looking for a memorised answer.
Cloud Logging
Why it's wrong here
Logging provides log entries but not trace context unless using Cloud Trace.
Cloud Debugger
Why it's wrong here
Debugger captures snapshots of code, not request traces.
Common exam traps
The trap here is that candidates often confuse Cloud Trace with Cloud Logging, thinking that log aggregation alone can reconstruct request paths, but Cloud Trace is the only service that provides distributed tracing with explicit span context propagation across microservices.
Detailed technical explanation
Under the hood, Cloud Trace uses the OpenTelemetry or Stackdriver Trace SDK to instrument applications, generating trace spans that capture timing and metadata for each operation. These spans are sent to the Cloud Trace API, which assembles them into a trace tree based on a shared trace ID and parent span IDs. In a real-world scenario, a Cloud Run service calling a Cloud SQL database and a downstream Cloud Run service would show each hop as a separate span, allowing the developer to pinpoint that the database query is the slowest segment.
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
Scaling with Google Cloud operations — This question tests Scaling with Google Cloud operations — Read the scenario before looking for a memorised answer..
The correct answer is: Cloud Trace — Cloud Trace is the correct service because it is specifically designed for distributed tracing, collecting latency data from applications and displaying it in a trace timeline. It can trace requests as they propagate across multiple microservices, including Cloud Run services, by using trace context propagation headers (e.g., `X-Cloud-Trace-Context`). This allows the developer to identify bottlenecks and slow components in a request path.
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
This GCDL 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 GCDL exam.
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