# Outlier Incident

View the frequency of similar incidents to gain helpful context during incident triage

The Outlier Incident feature provides incident responders with immediate context on how often similar incidents have occurred on a specific service, helping them quickly determine whether an issue is familiar or new. This is particularly valuable for IT operations teams and DevOps engineers who need to identify patterns and irregularities to make informed decisions during response efforts. By categorizing incidents as frequent, rare, or anomalous, the feature streamlines the analysis process, allowing teams to focus on resolution and ultimately improve service reliability. 

> **AIOps / Signal Intelligence Feature:** This feature is included with the [PagerDuty AIOps](/ai-automation/aiops/overview) add-on, or included as Signal Intelligence in PD Reliability Platform plans. To sign up for a trial of PagerDuty AIOps features, read [PagerDuty AIOps Trials](/ai-automation/aiops/overview#pagerduty-aiops-trials).

> **AIOps Service Configuration:** Your service configuration must have AIOps enabled to use this feature. AIOps Service Configuration is in Limited General Availability — see [Configurable Service Settings](/incident-management/services/configurable-service-settings#manage-aiops) for more information and enablement steps.

> **Legacy Availability:** This feature is also available with [Legacy Event Intelligence](/ai-automation/aiops/legacy-event-intelligence).

## View Outlier Incident in the Web App

1. From the Incidents page or a service’s detail page, click your desired incident’s **Title** to see its detail page.
2. If an incident has been categorized as a frequent, rare or anomalous incident these details will appear below the incident title. 

![A screenshot of the PagerDuty web app UI indicating an incident with the "Anomaly" Outlier Incident label](/images/kb/0547e82c047bf468baaef272ef9e1527171d1841c70ce189193220d0ea989457-outlier-incident-overview.webp)
*Incident with "Anomaly" Outlier Incident label*

## Outlier Incident Labels

Outlier Incident uses data science techniques to dynamically map incidents to templates and determine how often each type of incident occurs on a service. The following labels are applied below the incident title on the incident's details page:

- **Frequent**: Incident types representing 20% or more of all incidents in the previous 30 days.
- **Rare**: Incident types representing 5% or less of all incidents in the previous 30 days.
- **Anomaly**: Incident types that have not occurred on the service in the previous 30 days. 

For the purpose of determining which of the labels above to use, incident data from the 30 days prior to an incident’s trigger date is used.