Google PCA Practice Question: Analysing and Optimising Technical and Business Processes
Your company uses Cloud Monitoring to track the performance of a microservices application. The SRE team wants to define an SLO for the latency of a critical API. They need to measure the proportion of requests that complete within 200 ms over a rolling 30-day window. Which approach should they use to implement this SLO?
⚠ Common exam trap
A common mix-up: candidates confuse uptime checks with latency SLOs; uptime checks measure availability from external probes, not the latency distribution of actual user requests.
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 Monitoring's SLO monitoring feature to define a latency SLO with a distribution cut based on a histogram metric.
Cloud Monitoring's SLO monitoring is designed for defining and tracking SLOs. Using a distribution cut on a histogram metric allows precise measurement of the proportion of requests within the latency threshold over a rolling period. It also provides error budget and alerting, which are essential for SRE practices.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure a log-based metric that counts requests with latency under 200 ms, then create an alert if the count drops.
Why it's wrong here
A log-based metric can count requests meeting a condition, but it does not automatically compute the ratio of good requests to total requests over a rolling window, nor does it provide error budget tracking. While it can be part of a solution, it lacks the integrated SLO features of Cloud Monitoring. This approach is more manual and error-prone.
- ✓
Use Cloud Monitoring's SLO monitoring feature to define a latency SLO with a distribution cut based on a histogram metric.
Why this is correct
Cloud Monitoring's SLO monitoring allows you to define service level objectives based on metrics. For latency, you can use a distribution cut on a histogram metric to specify the threshold (200 ms) and calculate the ratio of good requests to total requests over a rolling window. This provides automated tracking, error budget calculation, and alerting.
- ✗
Set up an uptime check that measures the API response time and alerts if it exceeds 200 ms.
Why it's wrong here
Uptime checks are designed to monitor availability from external locations, not to measure the latency distribution of actual user requests. They can detect if the API is reachable and measure response time from specific probes, but they do not capture the proportion of all requests within a latency threshold. This approach does not fulfill the SLO requirement.
- ✗
Create a custom metric that logs each request latency, then use a dashboard to manually calculate the percentage within 200 ms.
Why it's wrong here
While custom metrics can capture latency, manually calculating the percentage from a dashboard is not a formal SLO and lacks alerting and error budget tracking. This approach does not provide automated monitoring or reporting against the SLO, making it unsuitable for SRE practices. It also introduces manual effort and potential errors.
Go deeper
Related to this question
Learn chapter
Security Best Practices and Compliance
Key term
Error budget
An error budget is the maximum amount of acceptable downtime or failure a system can experience within a specified period while still meeting its Service Level Objective (SLO).
Key term
SLO
A Service Level Objective is a measurable target for a specific aspect of a service's performance or reliability that a team commits to meeting over a defined period.
About these practice questions
This PCA question is part of Courseiva's 807-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PCA 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 PCA exam.