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Real-time adaptive operations performance management system using event clusters and trained models

机译:使用事件簇和训练模型的实时自适应运营绩效管理系统

摘要

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.
机译:实施例涉及管理操作。如果提供了操作事件,则事件簇可以与一个或多个操作事件关联,从而可以基于操作事件的特征将操作事件与事件簇关联。包括解决方案度量标准,根本原因分析,注释和其他补救信息的度量标准可以与事件群集相关联。然后,可以采用建模引擎来基于操作事件,事件簇和分辨率度量来训练模型,从而可以训练训练后的模型以根据实时操作事件来关联和预测分辨率度量。如果可以提供实时操作事件,则可以使用训练后的模型来预测与实时操作事件相关的分辨率指标。如果模型性能下降到超出精度要求的程度,则可以将新的观察值添加到训练集中,然后对模型进行重新训练。

著录项

  • 公开/公告号US9811795B1

    专利类型

  • 公开/公告日2017-11-07

    原文格式PDF

  • 申请/专利权人 PAGERDUTY INC.;

    申请/专利号US201715443961

  • 申请日2017-02-27

  • 分类号G06F17;G06Q10/06;G06N99;G06N5/04;

  • 国家 US

  • 入库时间 2022-08-21 13:43:34

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