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PATTERN DISCOVERY FROM HIGH DIMENSIONAL TELEMETRY DATA USING MACHINE LEARNING IN A NETWORK ASSURANCE SERVICE

机译:网络保障服务中基于机器学习的高维遥测数据模式发现

摘要

In one embodiment, a network assurance service that monitors a plurality of networks subdivides telemetry data regarding devices located in the networks into subsets, wherein each subset is associated with a device type, time period, metric type, and network. The service summarizes each subset by computing distribution percentiles of metric values in the subset. The service identifies an outlier subset by comparing distribution percentiles that summarize the subsets. The service reports insight data regarding the outlier subset to a user interface. The service adjusts the subsets based in part on feedback regarding the insight data from the user interface.
机译:在一个实施例中,监视多个网络的网络保证服务将关于位于网络中的设备的遥测数据细分为子集,其中,每个子集与设备类型,时间段,度量类型和网络相关联。该服务通过计算子集中度量值的分布百分比来汇总每个子集。该服务通过比较汇总子集的分布百分比来标识异常子集。该服务向用户界面报告有关异常值子集的洞察数据。该服务部分地基于与来自用户界面的洞察数据有关的反馈来调整子集。

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