PROFESSIONAL-CLOUD-DEVOPS-ENGINEER Question #59: Real Exam Question with Answer & Explanation

Question

You are creating Cloud Logging sinks to export log entries from Cloud Logging to BigQuery for future analysis. Your organization has a Google Cloud folder named Dev that contains development projects and a folder named Prod that contains production projects. Log entries for development projects must be exported to dev_dataset, and log entries for production projects must be exported to prod_dataset. You need to minimize the number of log sinks created, and you want to ensure that the log sinks apply to future projects. What should you do?

Options

• ACreate a single aggregated log sink at the organization level.
• BCreate a log sink in each project.
• CCreate two aggregated log sinks at the organization level, and filter by project ID.
• DCreate an aggregated log sink in the Dev and Prod folders.

Explanation

To minimize the number of log sinks and ensure future projects are covered while directing Dev logs to dev_dataset and Prod logs to prod_dataset, create an aggregated log sink in both the Dev and Prod folders.

Common mistakes.

• A. A single aggregated log sink at the organization level cannot direct logs to two separate BigQuery datasets (dev_dataset and prod_dataset) based on their folder origin simultaneously.
• B. Creating a log sink in each project would not minimize the number of sinks and would require manual configuration for every new project, failing to apply to future projects automatically.
• C. Creating two aggregated log sinks at the organization level and filtering by project ID is technically feasible but is generally more complex and less robust than using folder-level aggregated sinks, which inherently leverage the existing resource hierarchy for scope without needing manual filter maintenance based on project naming conventions.

Concept tested. Cloud Logging aggregated sinks and hierarchical log export

Reference. https://cloud.google.com/logging/docs/export/aggregated_sinks

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