Federated microburst detection
    81.
    发明授权

    公开(公告)号:US10972388B2

    公开(公告)日:2021-04-06

    申请号:US15359511

    申请日:2016-11-22

    Abstract: An example method includes a sensor detecting multiple packets of a flow during a specified total time period (e.g., a reporting time period). The total time period can be subdivided into multiple time periods. The sensor can analyze the detected packets to determine an amount of network utilization for each of the time periods. The sensor can then generate a flow summary based on the network utilization and the flow and send the flow summary to an analytics engine. Multiple other sensors can do similarly for their respective packets and flows. The analytics engine can receive the flow summaries from the various sensors and determine a correspondence between flow with high network utilization at a specific time period and a node or nodes. These nodes that experienced multiple flows with high network utilization for a certain period of time can be identified as experiencing a microburst.

    Predicting application and network performance

    公开(公告)号:US10708152B2

    公开(公告)日:2020-07-07

    申请号:US15467788

    申请日:2017-03-23

    Abstract: An application and network analytics platform can capture comprehensive telemetry from servers and network devices operating within a network. The platform can discover flows running through the network, applications generating the flows, servers hosting the applications, computing resources provisioned and consumed by the applications, and network topology, among other insights. The platform can generate various models relating one set of application and network performance metrics to another. For example, the platform can model application latency as a function of computing resources provisioned to and/or actually used by the application, its host's total resources, and/or the distance of its host relative to other elements of the network. The platform can change the model by moving, removing, or adding elements to predict how the change affects application and network performance. In some situations, the platform can automatically act on predictions to improve application and network performance.

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