Question

Difficulty: MediumMonitoring, Logging, and Observability Integration

An enterprise organization needs to centralize operational and security audit logs across multiple Google Cloud projects into a designated security operations project. The solution must ensure secure, least-privilege log delivery to a central BigQuery dataset while excluding low-severity debug logs to control storage costs, without dropping high-severity operational events. Which TWO actions should you take to implement this architecture?

  1. Create an aggregated Log Router sink at the Google Cloud Organization level targeting the destination BigQuery dataset, using an inclusion filter for severity ERROR and audit logs.Answer
  2. Grant the unique writer identity service account generated by the Log Router sink the BigQuery Data Editor role on the target destination dataset.Answer
  3. C
    Configure a global log exclusion filter set to drop all cloudaudit.googleapis.com records across the organization to minimize ingestion bandwidth.
  4. D
    Assign the Owner primitive IAM role to the Log Router service account across all projects to ensure unrestricted write access.
  5. E
    Rely strictly on project IAM read permissions to prevent authorized analysts from copying dataset contents to external storage buckets.

Answer

Creating an aggregated Log Router sink at the organization level with an inclusion filter for required high-severity logs, and granting the sink's generated writer identity least-privilege write permissions (BigQuery Data Editor) on the central dataset.
Centralized observability across multiple projects is best achieved by establishing an aggregated Log Router sink at the Organization level with targeted log filters. The sink automatically receives a unique writer identity service account, which must be granted minimum required permissions (such as BigQuery Data Editor) on the destination dataset to adhere to security best practices.

Step-by-Step Solution

1
Define centralized log routing scope
Aggregated Log Router sink created at the organization level to capture logs across child projects.
Organization-level sinks automatically aggregate logs across all current and future projects in the resource hierarchy.
2
Configure filter and destination
Filter set to include severity ERROR and audit logs, targeting a central BigQuery dataset.
Filtering controls log ingestion volume and cost while ensuring critical operational events are preserved.
3
Grant writer identity permissions
Sink writer identity granted BigQuery Data Editor on the central dataset.
Log Router relies on a dedicated service account identity that requires explicit destination authorization under least privilege.

Key Concept

Centralized Log Router Sinks & Least-Privilege Log Export Architecture
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