VISUALIZATION OF OUTLIERS IN A HIGHLY-SKEWED DISTRIBUTION OF TELEMETRY DATA

    公开(公告)号:US20220113888A1

    公开(公告)日:2022-04-14

    申请号:US17070484

    申请日:2020-10-14

    Applicant: NetApp, Inc.

    Abstract: Systems and methods for enhancing the representation of outliers in a distribution of telemetry data of a monitored system are provided. According to one embodiment, telemetry data of the monitored system may be continuously collected. Frequency values representing a frequency of occurrence of corresponding telemetry data of the collected telemetry data may be generated by aggregating the collected telemetry data. As the vast majority of telemetry data is expected to represent a normal operating state of the system and relatively few, if any, of the telemetry data (e.g., outliers) will be indicative of one or more events of significance, the resulting distribution of the frequency values is highly skewed. In order to facilitate visualization of the distribution that accentuates the outliers, display characteristics may be calculated for the frequency values by applying a visualization model based on a weighted combination of multiple data transformations to each of the frequency values.

    Visualization of outliers in a highly-skewed distribution of telemetry data

    公开(公告)号:US11609704B2

    公开(公告)日:2023-03-21

    申请号:US17070484

    申请日:2020-10-14

    Applicant: NetApp, Inc.

    Abstract: Systems and methods for enhancing the representation of outliers in a distribution of telemetry data of a monitored system are provided. According to one embodiment, telemetry data of the monitored system may be continuously collected. Frequency values representing a frequency of occurrence of corresponding telemetry data of the collected telemetry data may be generated by aggregating the collected telemetry data. As the vast majority of telemetry data is expected to represent a normal operating state of the system and relatively few, if any, of the telemetry data (e.g., outliers) will be indicative of one or more events of significance, the resulting distribution of the frequency values is highly skewed. In order to facilitate visualization of the distribution that accentuates the outliers, display characteristics may be calculated for the frequency values by applying a visualization model based on a weighted combination of multiple data transformations to each of the frequency values.

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