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Google ACE Practice Question: Monitor the CPU utilization of their Compute…
A company wants to monitor the CPU utilization of their Compute Engine instances and receive an alert if utilization exceeds 80% for 5 minutes. Which services should they combine?
⚠ Common exam trap
Google Cloud often tests the distinction between logging (Cloud Logging) and monitoring (Cloud Monitoring) — the trap here is that candidates confuse log-based metrics with native system metrics, assuming Cloud Logging can evaluate CPU thresholds when it can only parse log entries, not numeric time-series data.
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 and Cloud Pub/Sub.
Cloud Monitoring collects CPU utilization metrics from Compute Engine instances and can evaluate them against a threshold-based alerting policy. When the condition (CPU > 80% for 5 minutes) is met, the alert fires and sends a notification to a Cloud Pub/Sub topic, which can then trigger downstream actions such as sending emails or invoking serverless functions. This combination provides the metric ingestion, alert evaluation, and event-driven notification pipeline required for the use case.
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 Functions and Cloud Tasks.
Why it's wrong here
Cloud Functions and Cloud Tasks are serverless compute and task orchestration services, not observability tools. They do not collect, persist, or visualize time-series metrics such as CPU utilization from Compute Engine instances. Cloud Monitoring is the native GCP service that ingests metric data and evaluates alerting conditions; these compute services could only act on alerts after they are triggered, not monitor or alarm on the metric itself.
- ✗
Cloud Audit Logs and Cloud Storage.
Why it's wrong here
Cloud Audit Logs record administrative and data-access operations for compliance and security forensics, they never capture hardware utilization like CPU percentage. Cloud Storage is a durable object store designed for unstructured artifacts, not for real-time metric streaming or threshold-based alerting. Neither service exposes the CPU utilization dashboard or alerting features provided by Cloud Monitoring, so this pair cannot satisfy the monitoring requirement.
- ✓
Cloud Monitoring and Cloud Pub/Sub.
Why this is correct
Cloud Monitoring directly collects CPU utilization from Compute Engine via built-in hypervisor metrics or the Ops Agent, and supports alerting policies with conditions like CPU threshold violations. Cloud Pub/Sub acts as a fully managed notification channel that receives alert messages, enabling fan-out to multiple subscribers or triggering downstream automation. Together they deliver the metric-observation layer and a scalable event-delivery mechanism for alert notifications.
- ✗
Cloud Logging and Cloud Functions.
Why it's wrong here
Cloud Logging ingests discrete log entries from applications and services, but CPU utilization is a sampled numeric time-series metric, not a log line; Cloud Monitoring is the service that stores and alarms on such metrics. Cloud Functions can be triggered by HTTP calls, Pub/Sub messages, or log sinks, but it is not a monitoring service and does not aggregate utilization data. Choosing these would require custom log-based metric extraction rather than using the native Cloud Monitoring alerting path.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
Go deeper
Related to this question
Learn chapter
Google Cloud Platform Overview
Key term
Serverless
Serverless is a cloud computing model where the cloud provider manages the servers, and you only pay for the actual compute time your code uses, without having to worry about provisioning or maintaining infrastructure.
Key term
Compute Engine
Compute Engine is Google Cloud's Infrastructure-as-a-Service (IaaS) offering that lets you create and run virtual machines on Google's infrastructure.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This ACE 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 ACE exam.