Juniper Networks, Inc.

Kush Shah

Jisheng Wang

Robert J Friday

Jacob Thomas

Xiaoying Wu

Jing Cheng

Yedunandan Siddalingappa-Vitalapur

Randall Wayne Frei

Sujai Hajela

Abhiram Madhugiri Shamsundar

Sunalini Sankhavaram

Amin Toghi Eshghi

Sudheer Matta

Jordan Batch

Huan Thien-Vu

Techniques are described by which a network management system (NMS) is configured to provide identification of root cause failure through the detection of network scope failures. For example, the NMS comprises one or more processors; and a memory comprising instructions that when executed by the one or more processors cause the one or more processors to: generate a hierarchical attribution graph comprising attributes representing different network scopes at different hierarchical levels; receive network event data, wherein the network event data is indicative of operational behavior of the network, including one or more of successful events or one or more failure events associated with one or more client devices; and apply a machine learning model to the network event data and to a particular network scope in the hierarchical attribution graph to detect whether the particular network scope has failure.

Identifying root cause of failures through detection of network scope failures

This disclosure describes a network management system (NMS) configured to determine a particular network device of a plurality of network devices based on a first user input in a conversational assistant. The one or more processors are further configured to identify a set of actionable insights for the particular network device based on network data received from the plurality of network devices and determine a set of views of a dashboard based at least on the set of actionable insights, wherein each view of the set of views displays a portion of the network data received from the plurality of network devices. The one or more processors are further configured to select a view of the set of views of the dashboard based on a second user input in the conversational assistant and cause the dashboard to display the selected view.

Conversational assistant for obtaining network information

The network management system (NMS) assesses behavior data such as Ethernet error, speed flapping, cold restart, and/or cloud disconnect collected from a respective one of access points (APs) or other wired client-side devices at an edge of a wired network, and determines whether features of the behavior data are indicative of a bad cable issue at a particular port of a particular network device of the wired network to which the respective AP is connected via a cable. The particular network device may be a third-party network device from which the NMS does not receive behavior data. In the case of a bad cable issue being detected, the NMS outputs a bad cable notification including identification information of the particular port and the particular network device. The NMS enables client-side only, behavior-based bad cable detection at network devices that avoids network traffic disruptions caused by conventional cable tests.

Physical layer issue detection based on client-side behavior assessments

A network management system (NMS) is described that provides a granular troubleshooting workflow at an application session level using an application session-specific topology from a client device to a cloud-based application server. During an application session of a cloud-based application, a client device running the application exchanges data through one or more access point (AP) devices, one or more switches at a wired network edge, and one or more network nodes, e.g., switches, routers, and/or gateway devices, to reach a cloud-based application server. For a particular application session, the NMS generates a topology based on network data received from a subset of network devices, e.g., client devices, AP devices, switches, routers, and/or gateways, that were involved in the particular application session over a duration of the particular application session. In this way, the NMS enables backward-looking troubleshooting of the particular application session.

Application session-specific network topology generation for troubleshooting the application session

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Santa Clara, CA, United States of America

Kush Shah