Google PCA Practice Question: Analysing and Optimising Technical and Business Processes
A company operates a critical application on Google Cloud and wants to define a Service Level Objective (SLO) for its latency. They need to measure the proportion of requests that complete within 200 ms over a 28-day rolling window. They also want to alert when the error budget is being consumed too quickly. What should they use?
⚠ Common exam trap
The trap here is thinking that uptime checks or log-based metrics can serve as SLOs, but they lack the integrated error budget and burn rate alerting that Cloud Monitoring SLOs provide.
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 Monitoring SLOs with error budget burn rate alerts.
Cloud Monitoring SLOs allow you to define service level objectives based on metrics like latency, set a goal, and monitor error budgets. Burn rate alerts notify when the error budget is consumed faster than desired, enabling proactive response.
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 Trace with analysis reports and custom alerts.
Why it's wrong here
Cloud Trace is for distributed tracing and latency analysis, but it does not provide SLO management or error budget tracking. While it can help diagnose latency issues, it does not fulfill the requirement to define and monitor an SLO with burn rate alerts.
- ✓
Cloud Monitoring SLOs with error budget burn rate alerts.
Why this is correct
Cloud Monitoring allows you to define SLOs based on latency distributions, set a performance goal (e.g., 99% of requests under 200 ms), and create alerting policies based on error budget burn rates. This directly meets the requirement to measure the proportion and alert on rapid consumption.
- ✗
Cloud Logging with log-based metrics and custom dashboards.
Why it's wrong here
Log-based metrics can extract latency values from logs, but they do not natively compute SLOs or error budgets. You would need to build custom calculations and alerting, which is more complex and error-prone. Cloud Monitoring SLOs provide this out of the box.
- ✗
Cloud Monitoring with uptime checks and alerting policies based on latency thresholds.
Why it's wrong here
Uptime checks monitor availability, not latency SLOs. Alerting on latency thresholds can notify when latency is high, but it does not track error budget consumption or the proportion of requests meeting the SLO. This approach lacks the SLO-specific features needed.
Go deeper
Related to this question
Learn chapter
IAM Policies, Service Accounts, and Auditing
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
Key term
Alerting policy
An alerting policy is a set of rules that defines when to send notifications about a system condition that needs attention.
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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.