This PCDOE practice question tests your understanding of optimizing service performance. 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 team is running a stateful application on Compute Engine VMs. They notice that the application performance degrades over time as the disk fills up. They want to proactively alert before performance degrades. Which metric should they monitor?
Disk usage percentage
Monitors disk capacity, enabling early alerts.
Disk read/write latency
Why wrong: Latency increases after disk is nearly full, but it's a symptom, not a proactive indicator.
Network sent bytes
Why wrong: Network traffic is unrelated to disk usage.
CPU utilization
Why wrong: CPU doesn't indicate disk fullness.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Disk usage percentage
Disk usage percentage is the correct metric because the application performance degrades as the disk fills up, which is a capacity issue. Monitoring disk usage percentage allows the team to set an alert threshold (e.g., 80% or 90%) to proactively take action (e.g., clean up logs or resize disks) before the disk becomes full and causes performance degradation. This directly addresses the root cause described in the scenario.
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.
Disk usage percentage
Why this is correct
Monitors disk capacity, enabling early alerts.
Related concept
Read the scenario before looking for a memorised answer.
Disk read/write latency
Why it's wrong here
Latency increases after disk is nearly full, but it's a symptom, not a proactive indicator.
Network sent bytes
Why it's wrong here
Network traffic is unrelated to disk usage.
CPU utilization
Why it's wrong here
CPU doesn't indicate disk fullness.
Common exam traps
The trap here is that candidates may confuse a capacity metric (disk usage percentage) with a performance metric (disk latency), assuming latency is the best indicator of degradation, but the question explicitly ties the degradation to the disk filling up, making capacity the direct cause to monitor.
Detailed technical explanation
Under the hood, as a disk approaches 100% usage, the filesystem may become fragmented, and the OS may struggle to allocate new blocks, leading to increased I/O wait times and potential application stalls. In a real-world scenario, a stateful application like a database might stop writing transactions or crash if the disk is full, so monitoring disk usage percentage with a proactive alert (e.g., at 85%) allows time to implement cleanup scripts or auto-scaling of persistent disks before the application fails.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Optimizing service performance — This question tests Optimizing service performance — Read the scenario before looking for a memorised answer..
The correct answer is: Disk usage percentage — Disk usage percentage is the correct metric because the application performance degrades as the disk fills up, which is a capacity issue. Monitoring disk usage percentage allows the team to set an alert threshold (e.g., 80% or 90%) to proactively take action (e.g., clean up logs or resize disks) before the disk becomes full and causes performance degradation. This directly addresses the root cause described in the scenario.
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 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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