Automatic, adaptive learning algorithms help you cut through the noise and get to the signal with no extra work. Responders get the exact machine and human context they need.
A flexible team and service-oriented model enables self-service intelligence and automation, supporting both central and distributed workflows in harmony.
Integrated event intelligence and incident response keeps everybody on the same page and drives fast resolution.
"We see Event Intelligence as a critical piece of our long-term strategy, moving more intelligence and automation into PagerDuty and increasing the number of alerts we can handle without human intervention. This has a large impact on helping us solve more problems and freeing up time for our resources."
Mike Makar, Sr. IT Manager, World Bank
Programmatically manage large volumes of event data from 300+ tools. Intelligently automate routing, suppression, notification, and other behaviors based on event data, issue severity, recurring schedules, support hours, and more. These capabilities are available both within our UI and using the Global Event Rules API.
Reduce the impact of unplanned work by giving adjacent teams incident visibility so they don’t duplicate efforts or interfere with each other. With Intelligent Triage, you are able to use Intelligent Alert Grouping and learnings from similar past and related incidents so teams can see other potentially related issues across the business, enabling teams to better collaborate in order to fix issues faster and more effectively.
Past Incidents add helpful context to help accurately triage an issue, which leads to shorter resolution time. You can see whether you or someone on your team was involved in a related incident, when these types of incidents happened, and discover what remediation steps were taken in the past.
With Related Incidents, you can better coordinate a holistic response when an issue spans multiple teams and services. Obtain real-time intelligence like how significant the incident is, what services and teams are affected, who is working on it, and how responders can be reached. This helps avoid teams working independently in silos, which often causes re-work, leading to more downtime.
Applied machine learning and rules-based approaches automatically group related issues across complex systems into a single incident, reducing noise while centralizing critical context to speed triage.
With alert grouping previews, service owners can better understand potential noise reduction and grouping behavior before activating Intelligent Alert Grouping on a particular service.
Prevent notification of non-actionable events while still retaining data for forensic analysis.