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Zorluk: OrtaMonitoring, Logging, and Observability Integration

A retail platform operates microservices across multiple Google Kubernetes Engine (GKE) clusters and Cloud Run services deployed in multiple Google Cloud projects. The operations team needs to centralize administrative audit logs and application error logs into a single BigQuery dataset for compliance auditing, while minimizing Cloud Logging ingestion costs by excluding high-volume verbose debug logs before they are written to log buckets. Which TWO actions should the cloud architect recommend to meet these requirements?

  1. Configure an aggregated Log Router sink at the Organization level with an inclusion filter targeting the centralized BigQuery dataset for audit logs and error severities.Cevap
  2. Add log exclusion filters to the log buckets across projects to drop log entries with severity level DEBUG prior to ingestion into the _Default log bucket.Cevap
  3. C
    Configure a global log exclusion filter on the organization sink that excludes log entries matching severity >= ERROR to reduce storage costs.
  4. D
    Grant the Owner primitive IAM role to the Logging service account across all projects to ensure sink creation and log writing permissions.
  5. E
    Rely strictly on project-level IAM viewer roles to secure log data without establishing VPC Service Controls perimeter boundaries.

Cevap

The team should configure an aggregated Log Router sink at the organization level targeting BigQuery for centralized audit and error logging, and apply exclusion filters on log buckets to drop DEBUG level logs prior to ingestion.
To centralize logging across an organization, an aggregated Log Router sink at the organization level automatically collects audit and operational logs from all projects into a BigQuery dataset. To minimize Cloud Logging ingestion expenses without sacrificing visibility into failures, exclusion filters should be configured on log buckets to drop low-value, high-volume DEBUG logs prior to storage.

Adım Adım Çözüm

1
Establish central log aggregation
Aggregated Log Router sink routes audit logs and errors across all projects to BigQuery.
Organization-level sinks automatically aggregate logs from all present and future child projects without requiring individual sink configuration in every project.
2
Optimize Cloud Logging ingestion costs
Exclusion filters drop high-volume DEBUG logs before log storage ingestion.
Exclusion filters evaluate incoming log entries and prevent excluded log entries from incurring storage and ingestion charges in log buckets.

Anahtar Kavram

Organization-level aggregated log router sinks combined with log exclusion filters enable centralized compliance logging and cost-optimized log storage.
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Monitoring, Logging, and Observability Integration

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