This alert has detected a high number of job executions in GCP BigQuery. The alert is activated when the job count exceeds 1000 jobs within a continuous period of 1 hour. Customization Guidance: Threshold: The default threshold is set at 1000 jobs per hour. Depending on your specific application needs and historical workload data, this threshold may need adjustment. Critical workloads or high-frequency job execution projects may require a lower threshold. Project and Job Type Specificity: Tailor alerts for different projects and job types based on their roles and criticality in your infrastructure. Projects handling critical data analysis or high-stakes operations may warrant more stringent monitoring. Notification Frequency: Consider the frequency of this alert to optimize the balance between responsiveness and noise. Adjust according to the criticality of the projects supported by the job executions. Action: Upon triggering of this alert, immediate actions include reviewing recent job logs, checking for unusual spikes in job submission, and ensuring that the job configurations are appropriate. Mitigating issues may involve adjusting job submission rates or addressing potential issues causing high job execution counts.

This alert has detected a high amount of data scanned by queries in GCP BigQuery. The alert is activated when the total data scanned exceeds 1 TB within a continuous period of 1 hour. Customization Guidance: Threshold: The default threshold is set at 1 TB of data scanned per hour. Depending on your specific application needs and historical data usage patterns, this threshold may need adjustment. For projects or queries that regularly handle large datasets, a higher threshold may be appropriate. Conversely, for critical or cost-sensitive applications, a lower threshold might be necessary to ensure timely intervention. Project and Query Specificity: Tailor alerts for different projects and query types based on their roles and importance in your infrastructure. Projects or queries involving significant data processing or high-stakes analysis may require stricter monitoring to prevent excessive data scanning and associated costs. Notification Frequency: Consider the frequency of this alert to strike a balance between responsiveness and avoiding excessive notifications. Adjust according to the criticality of the queries and projects involved. High-priority projects may need more frequent notifications to catch issues early. Action: Upon triggering of this alert, immediate actions include reviewing recent query logs to identify queries responsible for high data scanning. Check for inefficiencies or potential optimizations in query design that could reduce data scanned. Mitigating actions may involve adjusting query parameters, re-evaluating the necessity of scanning large datasets, or implementing more efficient query practices to manage and control costs effectively.