mediumMultiple ChoiceObjective-mapped
Cloud Trace for Distributed Tracing
Your application running on Google Kubernetes Engine (GKE) is experiencing intermittent latency spikes. You have enabled Cloud Monitoring and Cloud Logging. Which approach would be MOST effective to identify the root cause?
Quick Answer
The answer is Cloud Trace, because it is the only tool that provides distributed tracing to identify slow service calls across your GKE microservices. While Cloud Monitoring and Cloud Logging offer aggregate metrics and raw logs, they lack the granular, request-level visibility needed to pinpoint intermittent latency spikes. Cloud Trace captures individual spans for each request, allowing you to trace the exact path through services and isolate high-latency operations like a slow database query or a flaky external API call. On the Google Professional Cloud Developer exam, this question tests your understanding that distributed tracing is essential for diagnosing transient performance issues that don’t appear in averages or logs. A common trap is choosing Cloud Monitoring for its dashboards, but remember: metrics show the *what*, not the *where*. For a memory tip, think “Trace the race”—when a request is slow, follow its spans to find the lagging service.
⚠ Common exam trap
The PCD exam often tests the distinction between aggregate monitoring (metrics, logs) and distributed tracing, trapping candidates who assume that high CPU/memory or error logs are the only indicators of performance issues, when in fact intermittent latency spikes are best diagnosed with trace-level data that shows the exact request path and timing.
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 Cloud Trace to analyze distributed tracing data for slow requests.
Cloud Trace is the most effective tool for identifying intermittent latency spikes because it provides end-to-end distributed tracing, allowing you to pinpoint which specific service or request path is causing the delay. Unlike aggregate metrics or logs, Cloud Trace captures individual request spans and can reveal high-latency operations, such as slow database queries or external API calls, that occur only under certain conditions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the number of replicas or switch to a larger machine type.
Why it's wrong here
This is a reactive scaling action, not a diagnostic approach.
- ✓
Use Cloud Trace to analyze distributed tracing data for slow requests.
Why this is correct
Tracing reveals per-request latencies and bottlenecks.
- ✗
Examine CPU and memory utilization metrics in Cloud Monitoring for the GKE cluster.
Why it's wrong here
Metrics show aggregate resource usage, not request-level latency causes.
- ✗
Review recent Cloud Logging entries for error messages.
Why it's wrong here
Logs may show errors but not the root cause of intermittent latency.
Go deeper
Related to this question
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Same concept, more angles
1 more way this is tested on PCD
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A team is investigating increased latency in a web application deployed on Google Kubernetes Engine (GKE). They want to identify which specific service calls are slow. Which Google Cloud tool should they use?
medium- ✓ A.Cloud Trace
- B.Cloud Monitoring dashboards
- C.Cloud Profiler
- D.Cloud Logging
Why A: Cloud Trace is the correct tool because it provides end-to-end latency tracking for requests in distributed systems, including GKE. It captures detailed spans for each service call, allowing the team to pinpoint which specific microservice or API call is causing the increased latency. This aligns directly with the need to identify slow service calls in a web application.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.