Analyze Analytics Rules Ingestion Delays Using KQL

Monitoring analytics rules ingestion delay is essential to maintain timely alerting and detection in security operations. Using KQL queries, it is possible to identify delays between data generation and ingestion in Microsoft Sentinel, helping teams to pinpoint bottlenecks and improve system responsiveness. This approach highlights ingestion time gaps for analytics rules and security incidents, which can impact alert accuracy and investigation speed.

Risk

Ingestion delays can cause critical security alerts to be postponed or missed, increasing the risk of late threat detection and incident response. When analytics rules process data with significant lag, security teams may not act quickly enough, exposing organizations to prolonged vulnerabilities or attacks that could have been mitigated sooner.

Query

Microsoft Sentinel

SentinelHealth
| extend IngestionTime = ingestion_time()
| extend Delay = ingestion_time() - TimeGenerated
| summarize max(Delay) by SentinelResourceName

SentinelHealth
| extend IngestionTime = ingestion_time()
| extend Delay = ingestion_time() - TimeGenerated
| summarize percentiles(Delay,50,100) by SentinelResourceName

SecurityIncident  
| extend IngestionTime = ingestion_time()  
| extend Delay = ingestion_time() - TimeGenerated  
| summarize max(Delay) by Title

The queries calculate ingestion delays by comparing the ingestion timestamp with the original event generation time. The first summarizes the maximum delay per Sentinel workspace, the second provides percentile-based delay distributions, and the third monitors delays related to security incidents.

References

• Handle ingestion delay in Microsoft Sentinel | Microsoft Learn
• Handling ingestion delay in Azure Sentinel scheduled alert rules – Microsoft Community Hub