- A
Cloud Logging
Why wrong: Cloud Logging is used for log management and analysis, not for profiling CPU and memory usage.
- B
Cloud Debugger
Why wrong: Cloud Debugger allows you to inspect the state of an application in production without stopping it, but it is not a profiling tool.
- C
Cloud Profiler
Cloud Profiler continuously collects and analyzes CPU and memory usage at the function level, making it ideal for identifying performance bottlenecks.
- D
Cloud Trace
Cloud Trace provides distributed tracing to analyze request latency and identify performance issues in microservices architectures.
- E
Cloud Monitoring
Why wrong: Cloud Monitoring provides infrastructure-level metrics like VM CPU and memory, but does not profile application code.
Question 498 of 999
PCD Cloud Profiler 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. A key principle to apply: cloud Profiler. 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 profile their application's CPU and memory usage to identify performance bottlenecks. Which TWO Google Cloud services should they use?
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
✓
Cloud Profiler
The two Google Cloud services that a developer should use to profile application CPU and memory usage and identify performance bottlenecks are Cloud Profiler and Cloud Trace. Cloud Profiler (Option C) continuously gathers and analyzes call stacks and resource consumption across your application, pinpointing functions that consume the most CPU and memory. Cloud Trace (Option D) provides distributed tracing to analyze request latency and identify performance bottlenecks in microservices architectures. Together, they offer a comprehensive view of application performance, with Profiler focusing on resource-intensive code paths and Trace focusing on request-level delays.
Key principle: Cloud Profiler
Answer analysis
Option-by-option breakdown
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 used for log management and analysis, not for profiling CPU and memory usage.
- ✗
Cloud Debugger
Why it's wrong here
Cloud Debugger allows you to inspect the state of an application in production without stopping it, but it is not a profiling tool.
- ✓
Cloud Profiler
Why this is correct
Cloud Profiler continuously collects and analyzes CPU and memory usage at the function level, making it ideal for identifying performance bottlenecks.
Related concept
Cloud Profiler
- ✓
Cloud Trace
Why this is correct
Cloud Trace provides distributed tracing to analyze request latency and identify performance issues in microservices architectures.
Related concept
Cloud Profiler
- ✗
Cloud Monitoring
Why it's wrong here
Cloud Monitoring provides infrastructure-level metrics like VM CPU and memory, but does not profile application code.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common trap is confusing Cloud Monitoring (which shows VM-level CPU/memory metrics) with Cloud Profiler (application-level function-by-function profiling), leading candidates to select Cloud Monitoring instead of Cloud Profiler. Additionally, candidates may overlook Cloud Trace because it is associated with latency rather than direct CPU/memory profiling, but it is essential for identifying performance bottlenecks in distributed applications.
Detailed technical explanation
How to think about this question
Cloud Profiler uses statistical sampling of call stacks at a configurable rate (e.g., 10 samples per second) to build a flame graph that visualizes resource consumption by function. Under the hood, it leverages the `pprof` format and can profile applications written in Java, Go, Node.js, Python, and Ruby, automatically deducing the source code locations of hot spots. In a real-world scenario, a developer might discover that a seemingly innocuous string concatenation in a loop is causing 40% of CPU usage, which would be invisible in Cloud Monitoring's VM-level metrics.
KKey Concepts to Remember
- Cloud Profiler
- Cloud Trace
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
Cloud Profiler
Real-world example
How this comes up in practice
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. Cloud Profiler 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
Got this wrong? Here's your next step.
Review cloud Profiler, then practise related PCD questions on the same topic to reinforce the concept.
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Managing application performance monitoring — study guide chapter
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FAQ
Questions learners often ask
What does this PCD question test?
Managing application performance monitoring — This question tests Managing application performance monitoring — Cloud Profiler.
What is the correct answer to this question?
The correct answer is: Cloud Profiler — The two Google Cloud services that a developer should use to profile application CPU and memory usage and identify performance bottlenecks are Cloud Profiler and Cloud Trace. Cloud Profiler (Option C) continuously gathers and analyzes call stacks and resource consumption across your application, pinpointing functions that consume the most CPU and memory. Cloud Trace (Option D) provides distributed tracing to analyze request latency and identify performance bottlenecks in microservices architectures. Together, they offer a comprehensive view of application performance, with Profiler focusing on resource-intensive code paths and Trace focusing on request-level delays.
What should I do if I get this PCD question wrong?
Review cloud Profiler, then practise related PCD questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Cloud Profiler
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Last reviewed: Jun 25, 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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