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Real-time analysis of multidimensional time series data to identify an operational anomaly

机译:多维时间序列数据的实时分析识别操作异常

摘要

A device may receive data for a plurality of metrics from a set of server resources associated with hosting an application. The plurality of metrics may be related to a performance of the set of server resources. The data may be time series data. The device may normalize the data for the plurality of metrics across a set of points in time to form normalized data. The device may determine a score for the performance of the set of server resources associated with hosting the application at a particular point in time based on the normalized data. The score may be used to determine whether an anomaly is present in the performance of the set of server resources at the particular point in time. The device may perform an action to facilitate improvement of the performance of the set of server resources based on the score satisfying a threshold.
机译:设备可以从与托管应用相关联的一组服务器资源接收多个度量的数据。多个度量可以与该组服务器资源的性能有关。数据可以是时间序列数据。该设备可以跨一组时间点跨越多个度量的数据来形成归一化数据。该设备可以确定与基于归一化数据在时间的特定时间点托管应用程序的服务器资源集的分数。该分数可用于确定是否存在在特定时间点的服务器资源集的性能中存在的异常。该设备可以执行动作,以便于基于满足阈值的得分来促进改进服务器资源集的性能。

著录项

  • 公开/公告号US10944692B2

    专利类型

  • 公开/公告日2021-03-09

    原文格式PDF

  • 申请/专利权人 CAPITAL ONE SERVICES LLC;

    申请/专利号US201916245966

  • 发明设计人 KUMAR ANAND;AARON HOENIG;AMIT PANDEY;

    申请日2019-01-11

  • 分类号H04L12/26;H04L12/911;G06F17/18;G06F11/34;G06F5/01;H04L12/927;

  • 国家 US

  • 入库时间 2022-08-24 17:34:03

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