ON-DEMAND NETWORK INCIDENT GRAPH GENERATION
    2.
    发明公开

    公开(公告)号:US20240097966A1

    公开(公告)日:2024-03-21

    申请号:US18094378

    申请日:2023-01-08

    Applicant: VMware, Inc.

    CPC classification number: H04L41/0631 H04L41/0627 H04L43/045

    Abstract: Some embodiments provide a method for evaluating incidents within a network. The method receives notification of a first incident related to a first network entity and a second incident related to a second network entity. In response to the respective notifications of the first and second incidents, the method uses network monitoring data to generate a first component graph of a first portion of the network that includes the first network entity and a second component graph of a second portion of the network that includes the second network entity. The first and second component graphs respectively include first and second sets of network entities related to the first and second network entities according to the network monitoring data. The method uses the first and second component graphs to respectively identify root causes of the first and second incidents.

    Network functions support for serverless and granular computing environments

    公开(公告)号:US11190458B2

    公开(公告)日:2021-11-30

    申请号:US15814237

    申请日:2017-11-15

    Applicant: VMware, Inc.

    Abstract: The disclosure provides an approach for enabling network functions to be executed in serverless computing environments. One embodiment employs a per-packet architecture, in which the trigger for launching a serverless computing instance is receipt of a packet. In such a case, each received packet is packaged into a request to invoke network function(s) required to process the packet, and a serverless computing environment in turn executes the requested network function(s) as serverless computing instance(s) that process the packet and return a response. Another embodiment employs a per-flow architecture in which the trigger for launching a serverless computing instance is receipt of a packet belonging to a new traffic flow. In such a case, a coordinator identifies (or receives notification of) a received packet that belongs to a new sub-flow and launches a serverless computing instance to process packets of the sub-flow that are redirected to the serverless computing instance.

    CONTAINERIZED WORKLOAD SCHEDULING
    4.
    发明申请

    公开(公告)号:US20200341789A1

    公开(公告)日:2020-10-29

    申请号:US16394663

    申请日:2019-04-25

    Applicant: VMware, Inc.

    Abstract: A method for containerized workload scheduling can include monitoring network traffic between a first containerized workload deployed on a node in a virtual computing environment to determine affinities between the first containerized workload and other containerized workloads in the virtual computing environment. The method can further include scheduling, based, at least in part, on the determined affinities between the first containerized workload and the other containerized workloads, execution of a second containerized workload on the node on which the first containerized workload is deployed.

    NETWORK INCIDENT ROOT-CAUSE ANALYSIS
    5.
    发明公开

    公开(公告)号:US20240097970A1

    公开(公告)日:2024-03-21

    申请号:US18094379

    申请日:2023-01-08

    Applicant: VMware, Inc.

    CPC classification number: H04L41/065 H04L43/08

    Abstract: Some embodiments provide a method for identifying root causes of incidents within a network. The method receives a graph of a portion of the network related to a particular network entity for which an incident is reported. The graph specifies dependencies between neighboring network entities in the network. The method uses probabilistic analysis to determine, for each network entity of a set of network entities represented in the graph, whether adjusting a set of metrics of the entity affects one or more metrics of the particular network entity that have been diagnosed as indicative of a problem. The method reports a subset of the network entities with metrics that affect the one or more metrics of the particular network entity as potential root causes of the incident.

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