BigQuery Snapshots

Google Cloud Database
1

Dear Community members, I need your help!

I am trying to automate the notification of BigQuery snapshots failed, but having a problem with identifying which snapshots failed. Question regarding the recognition of snapshots failures - is there any specific table with snapshot loggings? I looked up the ‘loggings’ of GCP but it includes all the loggings of GCP.

Thank you so much for your help!

2

Yes, you can effectively identify failed BigQuery snapshots and automate notifications. Here’s an updated breakdown of the methods and implementation details:

1. Using Cloud Audit Logs

  • Directly filter for snapshot events in Cloud Audit Logs by focusing on table-related operations indicative of snapshot activities.
  • Use the following refined query as a guide:
resource.type="bigquery_resource" 
logName="projects/YOUR_PROJECT_ID/logs/bigquery.googleapis.com" 
severity="ERROR" 
(protoPayload.methodName="google.cloud.bigquery.v2.TableService.InsertTable" 
 OR protoPayload.methodName="google.cloud.bigquery.v2.TableService.DeleteTable")
  • Look for specific error messages within protoPayload.status.message to diagnose failure reasons.
  • Ensure you have the necessary permissions to view these logs.

2. Monitoring with Cloud Monitoring

  • Job Status Metrics: Monitor the “Job Completed” metric for BigQuery jobs, focusing on table-related operations.
  • Custom Metrics: Create custom metrics in Cloud Monitoring that count successful and failed snapshot operations for more granular tracking.

3. Querying INFORMATION_SCHEMA Views

  • Query for table and dataset management operations that indirectly relate to snapshots:
SELECT job_id, job_type, state, start_time, end_time, error_result 
FROM `project.dataset.INFORMATION_SCHEMA.JOBS_BY_PROJECT` 
WHERE state = 'FAILURE' 
  AND (operation_type = 'TABLE_EXPORT' 
       OR operation_type = 'TABLE_IMPORT')
  • Note: INFORMATION_SCHEMA is best for historical trend analysis, not real-time failure detection.

Automation and Notification

  • Cloud Functions: Trigger Cloud Functions based on filtered Cloud Audit Log entries or custom metric thresholds in Cloud Monitoring. Send notifications via email, Pub/Sub, Slack, etc.
  • Cloud Scheduler: Use Cloud Scheduler to periodically run tasks that query INFORMATION_SCHEMA views or analyze Cloud Monitoring metrics for proactive monitoring.

Important Notes

  • Cloud Audit Logs are your primary source for detailed snapshot operation tracking.
  • Combine real-time alerts with historical analysis for comprehensive monitoring.
  • Analyze the error_result field in INFORMATION_SCHEMA for initial failure insights.

Enhancements

  • Test Thoroughly: Continuously refine your setup to adapt to changes.
  • Categorize Errors: Classify errors by source to speed up troubleshooting.
3

Dear Staff,

thank you so much for your response! I appreciate it, will try to implement the suggested steps!