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Implementing service monitoring strategieseasyMultiple ChoiceObjective-mapped

PCDOE Implementing service monitoring strategies Practice Question

A small startup uses Cloud Functions for their backend and wants to monitor function execution times and error rates. They have enabled Cloud Monitoring and are viewing metrics in the Cloud Console. They notice that the execution time metric for a particular function shows an average of 200ms, but occasionally there are spikes to 5 seconds, which correspond to user-reported slow responses. They want to be alerted when the function exceeds 1 second for any invocation. What is the simplest way to achieve this?

⚠ Common exam trap

Google Cloud often tests the distinction between built-in metrics and log-based metrics, and the trap here is that candidates overcomplicate by choosing log-based metrics (Option A) when a simpler built-in metric already satisfies the requirement.

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 the built-in Cloud Functions latency metric and create a metric threshold alert for the max value over 1 minute.

Cloud Functions automatically emits a built-in `execution_time` metric (measured in milliseconds) to Cloud Monitoring. By creating a metric threshold alert on the `max` value of this metric over a 1-minute window, you can trigger an alert whenever any single invocation exceeds 1 second, directly matching the requirement to be alerted per invocation spike.

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 a log-based metric for function duration and set a threshold alert.

    Why it's wrong here

    Log-based metrics require additional configuration and are not simpler than the built-in metric.

  • Configure a Cloud Monitoring uptime check for the function URL.

    Why it's wrong here

    Uptime checks test availability, not latency.

  • Use the built-in Cloud Functions latency metric and create a metric threshold alert for the max value over 1 minute.

    Why this is correct

    This directly uses the existing metric and alerts on the maximum value, catching spikes.

  • Use Cloud Error Reporting to capture slow responses.

    Why it's wrong here

    Error Reporting captures errors, not latency data.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This PCDOE 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 PCDOE exam.