# US 2022/0036264 A1 · Real-time adaptive operations performance management system

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- Number: US 2022/0036264 A1
- Document ID: US20220036264A1
- Status: Published application
- Kind: A1
- Application number: 17/503,585
- Filed: 2021-10-18
- Published: 2022-02-03
- Earliest claimed: 2016-09-01
- Assignees: PagerDuty, Inc.
- Applicants: PagerDuty, Inc.
- Inventors: Justin David Kearns; Ophir Ronen; Laura Ann Zuchlewski
- Web page: https://patentgrep.com/patent/US20220036264A1

## CPC

- G06Q 10/0637: Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
- G06F 16/355: Creation or modification of classes or clusters
- G06N 20/00: Machine learning
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

Embodiments are directed to managing operations. If Operations events are provided, event clusters may be associated with one or more Operations events, such that the Operations events may be associated with the event clusters based on characteristics of the Operations events. Metrics including resolution metrics, root cause analysis, notes, and other remediation information may be associated with the event clusters. Then a modeling engine may be employed to train models based on the Operations events, the event clusters, and the resolution metrics, such that the trained model may be trained to correlate and predict the resolution metrics from real-time Operations events. If real-time Operations events may be provided, the trained models may be employed to predict the resolution metrics that are associated with the real-time Operations events. If model performance degrades beyond accuracy requirements, new observations may be added to the training set and the model re-trained.

## Claims

### Claim 1

A method for managing operations for organizations over a network using one or more network computers that include one or more processors that perform actions, comprising:
employing a plurality of provided Operations events to perform further actions, including:
providing, by the one or more processors, one or more event clusters that are associated with one or more Operations events;
associating, by the one or more processors, one or more resolution metrics with the one or more event clusters;
employing, by the one or more processors, a modeling engine to train one or more models based on the one or more Operations events, the one or more event clusters, and the one or more resolution metrics, wherein the one or more trained models are stored in a datastore; and
retrieving, by the one or more processors, the one or more trained models, from the datastore, that are used to identify the one or more resolution metrics that are associated with one or more real-time Operations events.