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Setting Up a Cloud Solution EnvironmentmediumMultiple ChoiceObjective-mapped

Google ACE Setting Up a Cloud Solution Environment Practice Question

A company wants to track and forecast GCP spending across different departments. They have already set up labels on resources to indicate the department. Which additional step should they take to analyze costs by department in BigQuery?

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

Enable billing export to BigQuery in the Cloud Billing console

Enabling billing export to BigQuery will stream billing data (including labels) into a BigQuery dataset, allowing custom queries and analysis.

Answer analysis

Option-by-option breakdown

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

  • Enable billing export to BigQuery in the Cloud Billing console

    Why this is correct

    Enabling billing export to BigQuery in the Cloud Billing console is the native, fully managed integration for this use case. It automatically creates a set of BigQuery tables (e.g., gcp_billing_export_resource_v1) that contain detailed line items including cost, usage, labels, and resource hierarchy, updated on an ongoing basis. This export requires no custom code and provides the historical, labelled data needed to track and forecast GCP spending across departments using standard SQL and BI tools.

  • Use the Cloud Billing API to programmatically fetch cost data and write it to BigQuery

    Why it's wrong here

    Using the Cloud Billing API directly to fetch data does not natively provide the detailed, labelled cost breakdown required for BigQuery analysis in this scenario. While the API offers programmatic access to billing data, integrating department labels for granular reporting would necessitate extensive custom parsing and data structuring. It is suitable for custom integrations, real-time cost queries, or automating specific billing tasks where a direct BigQuery export with labels is not the primary requirement.

  • Run a scheduled query in BigQuery that calls the Cloud Billing API

    Why it's wrong here

    A scheduled query in BigQuery cannot directly call the Cloud Billing API because BigQuery scheduled queries do not support invoking external APIs natively. Even if you tried to use the BigQuery `EXTERNAL_QUERY` function with a BigQuery Omni/connection, the Cloud Billing API is not a data source that can be queried like a database; it returns JSON responses that would require significant custom parsing and a Cloud Function or Dataflow orchestration pipeline. This approach adds unnecessary complexity and is not a recommended or supported pattern for loading billing data into BigQuery.

  • Create a Cloud Function that captures billing events and inserts them into BigQuery

    Why it's wrong here

    While a Cloud Function could be built to capture budget alerts or Pub/Sub billing events and insert them into BigQuery, that is not how detailed billing export works. Cloud Billing only emits budget threshold notifications as events, not the full inventory of usage and cost line items, so you would miss most of the granular data required for tracking/forecasting. Building such a function would require extra infrastructure to call the Cloud Billing API, handle pagination, and manage schema—making it both incomplete and more complex than the native export option.

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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.