- A
Manually compute availability using external monitoring tools.
Why wrong: Manual methods are error-prone and do not integrate with Cloud Monitoring's built-in SLO tracking and reporting.
- B
Use the Cloud Monitoring SLO service with a request latency SLI.
Why wrong: Latency SLIs measure performance, not availability; they cannot be used to calculate uptime percentage.
- C
Create an uptime check and a log-based metric for errors. Use the SLI formula: (successful requests / total requests).
This leverages native Cloud Monitoring SLO capabilities, defining availability as the fraction of successful probes or requests, and automatically tracks the SLO over a rolling window.
- D
Use Cloud Trace to measure latency and create a custom metric.
Why wrong: Cloud Trace is for latency, not availability; an availability SLO requires measuring successful vs. total requests, not response times.
PCD Managing application performance monitoring 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. 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 company wants to create an SLO for their API with a target of 99.9% availability over a 30-day rolling window. They are using Cloud Monitoring. Which combination of resources and techniques 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
Create an uptime check and a log-based metric for errors. Use the SLI formula: (successful requests / total requests).
Option C is correct because it combines an uptime check (to measure total requests) with a log-based metric for errors (to count failed requests), allowing the SLI formula (successful requests / total requests) to compute availability. This approach directly aligns with the 99.9% availability target over a 30-day rolling window, using Cloud Monitoring's native capabilities without external tools or irrelevant latency metrics.
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.
- ✗
Manually compute availability using external monitoring tools.
Why it's wrong here
Manual methods are error-prone and do not integrate with Cloud Monitoring's built-in SLO tracking and reporting.
- ✗
Use the Cloud Monitoring SLO service with a request latency SLI.
Why it's wrong here
Latency SLIs measure performance, not availability; they cannot be used to calculate uptime percentage.
- ✓
Create an uptime check and a log-based metric for errors. Use the SLI formula: (successful requests / total requests).
Why this is correct
This leverages native Cloud Monitoring SLO capabilities, defining availability as the fraction of successful probes or requests, and automatically tracks the SLO over a rolling window.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use Cloud Trace to measure latency and create a custom metric.
Why it's wrong here
Cloud Trace is for latency, not availability; an availability SLO requires measuring successful vs. total requests, not response times.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between availability and latency SLIs, so the trap here is assuming that any monitoring metric (like latency) can be used for an availability SLO, when in fact availability requires a success/failure ratio, not a performance threshold.
Detailed technical explanation
How to think about this question
Under the hood, an uptime check in Cloud Monitoring sends periodic HTTP requests to the API endpoint and records the response status; a log-based metric can parse application logs for error codes (e.g., HTTP 5xx) to count failures. The SLI formula (successful requests / total requests) directly maps to availability, and the 30-day rolling window is a standard time window for SLO compliance, where Cloud Monitoring automatically recalculates the metric over the sliding period. In a real-world scenario, if the API has intermittent failures that don't affect uptime checks (e.g., internal errors not caught by health checks), the log-based metric captures those failures, ensuring accurate availability measurement.
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
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
Got this wrong? Here's your next step.
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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 — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create an uptime check and a log-based metric for errors. Use the SLI formula: (successful requests / total requests). — Option C is correct because it combines an uptime check (to measure total requests) with a log-based metric for errors (to count failed requests), allowing the SLI formula (successful requests / total requests) to compute availability. This approach directly aligns with the 99.9% availability target over a 30-day rolling window, using Cloud Monitoring's native capabilities without external tools or irrelevant latency metrics.
What should I do if I get this PCD 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.
About these practice questions
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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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