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.
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