Alerts & Correlation ingests alerts from 464 sources and applies intelligent deduplication, correlation, and noise reduction. The correlation engine groups related alerts into incidents so your team sees one actionable notification instead of 50 redundant ones. Escalation policies ensure the right person is notified at the right time. The result: 94% fewer alert notifications with zero missed incidents.
When 50 monitoring tools fire 200 alerts about the same database outage, your team should get one notification, not 200. The deduplication engine identifies alerts that refer to the same underlying issue using signal fingerprinting, temporal correlation, and service dependency analysis. Deduplicated alerts are grouped into a single incident and routed to the team that owns the affected service.
The Correlation Engine analyzes alerts across all 464 sources to identify causal relationships. When a Kubernetes pod restart triggers a cascade of downstream alerts, API timeouts, queue backlog, elevated error rates, the engine identifies the pod restart as the root cause and presents the entire chain as a single correlated incident. This eliminates the need for engineers to manually piece together related alerts from different tools.
Escalation policies define who gets notified, when, and through which channel. Configure multi-level escalation ladders with time-based triggers: if the primary on-call doesn't acknowledge within 5 minutes, escalate to the secondary. If unresolved after 30 minutes, notify the team lead. Policies support Slack, PagerDuty, email, SMS, and phone call channels. Override policies for specific services, severities, or time windows.
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