GCP Associate Cloud Engineer Practice Question

Your startup now runs hundreds of Compute Engine VMs spread across several projects. The finance team wants to build a BigQuery dashboard that shows the cost of each individual VM and enrich that data with any labels applied to the instances so they can allocate spend to internal teams. You decide to turn on Cloud Billing export to BigQuery for the billing account. Which export option will meet these reporting requirements while minimizing additional data processing?

Configure a detailed usage cost export to BigQuery so each row contains per-resource charges along with metadata such as labels.
Export Cloud Billing data to Cloud Storage as CSV files, then load them into BigQuery for analysis.
Rely on the Cloud Billing Reports page and download its monthly CSV exports for import into BigQuery.
Configure a standard usage cost export to BigQuery, which summarizes costs per project and resource type.

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Answer Description

To report costs at the level of each resource (for example, every VM) and include metadata such as resource-level labels, you must enable the detailed usage cost export. This export writes one row per resource-level usage record and automatically adds columns for project, resource name, labels, and other details. The standard usage cost export is aggregated at higher levels and omits per-resource and label information, so it cannot satisfy the requirement without significant post-processing. Exporting files to Cloud Storage or manually downloading reports would both require extra steps to ingest or normalize the data and still would not provide the necessary granularity.

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