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Planning and Configuring a Cloud SolutionmediumMultiple ChoiceObjective-mapped

Google ACE Planning and Configuring a Cloud Solution Practice Question

A company wants to run a batch job that processes files from a Cloud Storage bucket and writes results to BigQuery. The job runs once daily and can take up to 30 minutes. Which compute option is the most cost-effective and requires the least operational overhead?

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 Run jobs

Cloud Functions is event-driven, but for scheduled batch jobs, Cloud Run or Compute Engine are better. However, Cloud Run offers serverless execution with per-second billing and scales down to zero. It is cost-effective for short-lived jobs and requires minimal operational overhead.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • GKE Autopilot cluster

    Why it's wrong here

    GKE Autopilot removes node management, but you still must create a cluster and define Kubernetes resources such as Deployments, Jobs, and ConfigMaps. For a daily 30-minute batch job, the overhead of cluster maintenance, RBAC, networking, and upgrade cycles is unnecessary, and the control plane and Autopilot premium costs are incurred even when no workloads run, making it less cost-effective than a serverless batch service.

  • Cloud Functions (2nd gen)

    Why it's wrong here

    Cloud Functions is fundamentally event-driven and not a job orchestration service; although 2nd gen supports up to a 60-minute timeout and can be triggered via Pub/Sub, you must manage retry policies, dead-letter queues, and concurrency yourself. A scheduled batch that processes files is better served by a purpose-built job runner that can execute a container to completion, rather than forcing a single-function invocation to handle stateful processing.

  • Cloud Run jobs

    Why this is correct

    Cloud Run jobs directly execute a containerized batch process to completion, scaling to zero immediately after the job finishes, so you pay only for the duration of execution (per-second billing). It supports long-running jobs (up to 24 hours), can be scheduled via Cloud Scheduler, and provides automatic retries, environment configuration, and VPC connectivity without managing servers or clusters. This makes it the most operationally simple and cost-effective option for a daily 30-minute file processing job.

  • Compute Engine with a preemptible VM

    Why it's wrong here

    Preemptible VMs are up to 60% cheaper but can be reclaimed by Compute Engine at any time, so a file-processing batch may be interrupted mid-run, requiring manual restart and idempotent reprocessing logic. You are responsible for provisioning, OS patching, startup/shutdown scripts, and ensuring the VM shuts down when idle; otherwise you'll be billed for extra uptime, making it an unreliable and operationally heavy choice for a scheduled batch.

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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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.