UPDATED 08:00 EDT / APRIL 11 2023

APPS

PagerDuty launches AIOps solution to reduce noise for incident response

Observability firm PagerDuty Inc. today announced it’s launching its AIOps solution into general availability to provide greater incident automation capabilities to DevOps and information technology teams by reducing noise and labor.

Developers, information technology teams and site reliability engineers are often faced with the insurmountable task of monitoring apps and infrastructure in order to stay ahead of issues that might crop up. When an incident happens, they are the first responders who receive the alert and get bombarded with a wave of information that can be overwhelming to sort through.

Even with the number of monitoring tools that exist in the industry that provide early detection of issues, developers and operations still face the issue of determining the root cause of issues and what exactly they should be paying attention to. That’s where PagerDuty AIOps steps in, by using machine learning to help excise the noise and allow for more rapid triage.

“PagerDuty AIOps enables global event orchestration, and we don’t stop there — by providing automation at every step in the incident management lifecycle, reducing noise and toil for not only dev teams but also centralized ITOps teams,” said Sean Scott, PagerDuty’s chief product development officer.

According to the company’s own internal metrics, on average customers who participated in the early access release of the AIOps solution reduced noise by 87% and deployed event automation nine times faster in comparison to their previous setups. Customers also reported that they did so with fewer drawn-out incident response times and lower ongoing maintenance costs.

The PagerDuty AIOps solution includes a suite of tools that provides event correlation capabilities, noise compression and triage context capability to make it easier to cut through data and see what’s actually happening during an incident. It does this with what PagerDuty calls “Global Event Orchestration,” a decision engine that allows engineers to trigger automation that will self-heal systems based on events that span across services.

It also combines end-to-end automation capabilities such as event ingestion and auto-remediation so it’s not necessary to monitor the system at all times, especially for minor incidents that can be solved with simple scripts.

For events that cannot be repaired through automation, the AIOps solution can automate diagnosis, by using machine learning to examine historical events that had previously been solved and surface them again to the appropriate people along with the appropriate context to understand what happened.

For the back end, there is a visibility console that allows operation teams a holistic view and a single source of truth when monitoring the entire platform. As a result, everyone from DevOps, IT teams and site reliability engineers can stay on the same page.

“We’ve been using PagerDuty’s Global Event Orchestration as part of the early availability program, and the results have been strong,” said Kiril Yurovnik, technical lead at fraud prevention company Riskified. “Riskified has been able to scale noise reduction, especially from nonproduction environments, saving our team valuable time to spend innovating on what’s next.”

PagerDuty users don’t have to change their processes to take advantage of the new AIOps solution, it works with the tools they already have on hand. PagerDuty has more than 700 native integrations, including Azure, JIRA, Jenkins, Splunk, DataDog, ServiceNow and Salesforce. The platform can also be extended with application programming interfaces for access to more tools.

Image: PagerDuty

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