mediumMultiple ChoiceObjective-mapped
Create a Cloud Monitoring Custom Dashboard for Multi-Service Overview
You need to create a dashboard in Cloud Monitoring that shows: (1) Cloud Run request count per second, (2) Cloud Run p99 latency, (3) GKE pod CPU utilization, and (4) Cloud SQL query duration — all on a single screen. Which Cloud Monitoring feature enables this multi-service overview?
Quick Answer
The answer is a Cloud Monitoring custom dashboard, which allows you to combine chart widgets for each metric across different services into a single screen. This is correct because Cloud Monitoring custom dashboards support heterogeneous metric queries using the Monitoring Query Language (MQL) or metric selectors, enabling you to pull Cloud Run request count per second, p99 latency, GKE pod CPU utilization, and Cloud SQL query duration into one unified view without needing separate tools or data exports. On the Google Associate Cloud Engineer exam, this question tests your understanding that custom dashboards are the native feature for aggregating multi-service metrics, often tripping candidates who mistakenly choose separate alerting policies or logs-based metrics. A common trap is assuming you need to export metrics to a third-party tool, but Cloud Monitoring’s built-in chart widgets handle it directly. Memory tip: think of a “custom dashboard” as your single-pane-of-glass command center—one screen, all services, no exports.
⚠ Common exam trap
Google Cloud often tests the distinction between monitoring (dashboards) and alerting (policies), and the trap here is assuming that alerting policies can serve as a dashboard or that logging tools can natively display numeric metrics without additional configuration.
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 a Cloud Monitoring custom dashboard with chart widgets for each metric across the different services.
Cloud Monitoring custom dashboards allow you to combine chart widgets from multiple monitored services (Cloud Run, GKE, Cloud SQL) into a single screen. This feature supports heterogeneous metric queries using the Monitoring Query Language (MQL) or metric selectors, enabling a unified view without needing separate tools or exports.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Create four separate alerting policies and pin them to a shared alerting page.
Why it's wrong here
Alerting policies trigger notifications when thresholds are breached — they don't create dashboards. Separate policies also don't create a unified single-screen view.
- ✓
Create a Cloud Monitoring custom dashboard with chart widgets for each metric across the different services.
Why this is correct
Custom dashboards support heterogeneous metric widgets from any GCP service. Each widget is independently configured, creating a unified operational view across Cloud Run, GKE, and Cloud SQL.
- ✗
Use BigQuery to query the metrics export and build a Looker Studio dashboard.
Why it's wrong here
While possible, exporting to BigQuery and using Looker Studio adds significant complexity for what Cloud Monitoring custom dashboards provide natively and in real-time.
- ✗
Use Cloud Logging to create a log-based dashboard with all four metrics.
Why it's wrong here
Log-based dashboards in Cloud Logging display log data, not metrics. Cross-service metric visualization requires Cloud Monitoring dashboards.
Go deeper
Related to this question
Learn chapter
Google Cloud Platform Overview
Key term
Pod
A pod is the smallest deployable unit in Kubernetes, containing one or more containers that share storage, network, and a specification for how to run.
Key term
Cloud Monitoring
Cloud monitoring is the process of observing, measuring, and managing an organization's cloud infrastructure and applications to ensure performance, availability, and security.
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Same concept, more angles
1 more way this is tested on ACE
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Match each Cloud Monitoring resource to its purpose.
medium- ✓ A.Workspace: A container that organizes all monitoring data and configurations for a project.
- ✓ B.Alerting Policy: A set of rules that define when to trigger an alert based on metric conditions.
- ✓ C.Notification Channel: A method for delivering alert notifications, such as email or SMS.
- ✓ D.Uptime Check: A test that checks the availability of a resource from multiple locations.
- E.Workspace: A mechanism to send notifications when an alert fires.
- F.Alerting Policy: A visual representation of metric data over time.
Why A: Cloud Monitoring resources serve distinct purposes: Workspace organizes monitoring data, Alerting Policies define alert conditions, Notification Channels specify delivery methods, and Uptime Checks verify resource availability. The distractors confuse these roles.
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.