- A
node/cpu/usage_time
Why wrong: Node-level metric, not per-container.
- B
container/cpu/throttled_time
Directly shows time spent throttled.
- C
container/memory/usage_bytes
Why wrong: Memory metric, not CPU.
- D
container/cpu/usage_time
CPU usage time helps identify if throttling is occurring.
- E
container/accelerator/duty_cycle
Why wrong: GPU metric, not CPU throttling.
Question 782 of 1,000
Identifying CPU Throttling in GKE with Cloud Monitoring Metrics
This PCDOE practice question tests your understanding of optimizing service performance. 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.
Which TWO metrics from Cloud Monitoring would best indicate that a GKE workload is experiencing CPU throttling due to a resource quota? (Choose 2)
Quick Answer
The answer is container/cpu/throttled_time and container/cpu/usage_time. The throttled_time metric directly captures the cumulative duration a container was denied CPU cycles because it exceeded its CFS quota, while usage_time reveals how much CPU the container actually consumed; when usage_time consistently approaches or hits the quota ceiling, throttling is the inevitable result. On the Google Professional Cloud DevOps Engineer exam, this pairing tests your ability to distinguish between metrics that measure resource consumption versus those that measure enforcement actions—a common trap is to pick only usage_time and miss the direct throttling signal. For memory, think of throttled_time as the “smoking gun” and usage_time as the “motive”: together they prove both the act and the cause of CPU throttling in GKE.
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
✓
container/cpu/throttled_time
Option B is correct because `container/cpu/throttled_time` directly measures the cumulative time a container's CPU usage was throttled due to exceeding its assigned CPU quota (CFS quota). Option D is correct because `container/cpu/usage_time` shows the actual CPU time used by the container; when compared against the quota limit, a high usage_time relative to the quota indicates that throttling is likely occurring. Together, these two metrics confirm both the occurrence and the cause of CPU throttling.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
node/cpu/usage_time
Why it's wrong here
Node-level metric, not per-container.
- ✓
container/cpu/throttled_time
Why this is correct
Directly shows time spent throttled.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
container/memory/usage_bytes
Why it's wrong here
Memory metric, not CPU.
- ✓
container/cpu/usage_time
Why this is correct
CPU usage time helps identify if throttling is occurring.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
container/accelerator/duty_cycle
Why it's wrong here
GPU metric, not CPU throttling.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between node-level and container-level metrics, and the trap here is that candidates may pick `node/cpu/usage_time` (Option A) thinking it reflects container throttling, when in fact it aggregates all pods on the node and cannot reveal per-container quota enforcement.
Detailed technical explanation
How to think about this question
Under the hood, GKE uses the Linux Completely Fair Scheduler (CFS) with quota enforcement via `cpu.cfs_quota_us` and `cpu.cfs_period_us`. When a container exceeds its quota, the kernel throttles it by pausing execution, and the `container/cpu/throttled_time` metric captures the cumulative duration of these pauses. In real-world scenarios, a sudden spike in `container/cpu/throttled_time` alongside a flat `container/cpu/usage_time` plateauing at the quota limit is a classic sign of quota-induced throttling, often mistaken for a node-level CPU bottleneck.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
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
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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. 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
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this PCDOE question test?
Optimizing service performance — This question tests Optimizing service performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: container/cpu/throttled_time — Option B is correct because `container/cpu/throttled_time` directly measures the cumulative time a container's CPU usage was throttled due to exceeding its assigned CPU quota (CFS quota). Option D is correct because `container/cpu/usage_time` shows the actual CPU time used by the container; when compared against the quota limit, a high usage_time relative to the quota indicates that throttling is likely occurring. Together, these two metrics confirm both the occurrence and the cause of CPU throttling.
What should I do if I get this PCDOE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This PCDOE 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 PCDOE exam.
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