Juniper Networks, Inc.

Lucent Technologies Inc.

Javier Antich

Chandrasekhar A

Jayanthi R

Jayabharat Boddu

David Tung

Nosherwan Minwalla

Guangyu Zhu

Matthew Jeremy Mellin

Ai He

Gregory Allan Sidebottom

Premchandar N

Harsha Lakshmikanth

Sri Sampath Mallipudi

Zhifei Fang

Nitin Kumar

Babu Singarayan

Patricio Giecco

Rahamath Sharif

Srikanth Subramanian

Hitesh Mali

Anshu Verma

Usama Anqud

Anand Beedi

Network management techniques are described. A controller device of this disclosure manages a device group of a network. The controller device includes processing circuitry in communication with the memory, the processing circuitry being configured to receive, using a programmable diagnosis service executed by the processing circuitry, a programming input, to form, using the programmable diagnosis service, based on the programming input, a resource definition graph that models interdependencies between a plurality of resources supported by the device group, to detect, using the programmable diagnosis service, an event affecting a first resource of the plurality of resources, and to identify, using the programmable diagnosis service, based on the interdependencies modeled in the resource definition graph formed based on the programming input, a root cause event that caused the event affecting the first resource, the root cause event occurring at a second resource of the plurality of resources.

Programmable diagnosis model for correlation of network events

A controller device manages a plurality of network devices. The controller device includes one or more processing units configured to receive an upgrade request; obtain a redundancy model indicating network device redundancies or service redundancies; determine, based on the upgrade request and the redundancy model, an update graph having nodes each representing one of the network devices or one of the services, the update graph also having at least one edge that connects two of the nodes and that indicates the network redundancy or the service redundancy; determine, based on the update graph including the at least one edge, an update schedule for performing an update of software for the network devices that ensures availability for the first network device or second network device or availability for the service; and update the software of each of the network devices according to the update schedule.

Intent-based, network-aware network device software-upgrade scheduling

Failure impact analysis (or 'impact analysis') is a process that involves identifying effects of a network event that are may or will results from the network event. In one example, this disclosure describes a method that includes generating, by a control system managing a resource group, a resource graph that models resource and event dependencies between a plurality of resources within the resource group; detecting, by the control system, a first event affecting a first resource of the plurality of resources, wherein the first event is a network event; and identifying, by the control system and based on the dependencies modeled by the resource graph, a second resource that is expected to be affected by the first event.

Failure impact analysis of network events

Management of network devices using network aware diagnosis techniques. An example method to monitor a network includes constructing, by a controller device that manages a plurality of network devices, a deployed graph model comprising a plurality of models representative of services operating on the network devices within the network. The method also includes receiving an alert, by the controller device, that a service operating on one of the network devices is experiencing a failure. Additionally, the method includes traversing, by the controller device, modeled dependencies within the deployed graph model to perform root cause analysis of the service that is experiencing the failure to determine a resource-level event causing the failure. The method includes. based on the traversing, providing, by the controller device, a report indicating the root cause of the failure.

Network model aware diagnosis of a network

A controller device manages a plurality of network devices. The controller device includes a memory configured to store a dependency model representing dependencies between resources provided by the network devices and a programmed merge strategy, and one or more processors implemented in circuitry and configured to: determine the resources provided by the network devices; determine relationships between the resources according to the programmed merge strategy; construct the dependency model using the determined relationships; determine that at least one of the resources has experienced a failure; and perform a root cause analysis using the dependency mathematical model to determine a root cause of the failure of the at least one of the resources.

Using a programmable resource dependency mathematical model to perform root cause analysis

In general, techniques are described for providing network device modeling in preconfigured network modeling environments. A device comprising a memory and a processor may be configured to perform the techniques. The processor may interface with a network device within the preconfigured network environment to iteratively adapt pre-defined configuration objects of the network device. The processor may conduct, for each iteration of the adaptation of the pre-defined configuration objects, a simulation to collect a simulation dataset representative of an operating state of the network device. The processor may generate, based on the operational data, a model representative of the network device that predicts, responsive to configuration parameters for the network device, an operating state of the network device. The memory may store the model.

Network device modeling in preconfigured network modeling environments

In general, techniques are described for automated network device model creation using randomized test beds. A device comprising a processor may be configured to perform the techniques. The processor may generate, based on simulation configuration files, configuration objects for performing a plurality of simulation iterations with respect to the network device operating within a test environment. Each of the simulation iterations may be configured to randomly assign parameters within the test environment. The driver may conduct, based on the configuration objects, each of the simulation iterations within the test environment to collect simulation datasets representative of operating states of the network device. The analytics module may perform machine learning with respect to each of the simulation datasets to generate a model that predicts, responsive to configuration parameters, an operating state of the network device when configured with the configuration parameters for the network device.

Automated network device model creation using randomized test beds

In general, techniques are described for providing diversity in simulation datasets during modeling. A device comprising a memory and a processor may be configured to perform the techniques. The memory may store simulation configuration files for conducting simulations of the network device within a test environment. The processor may conduct, based on the simulation configuration files, each of the simulations with respect to the network device to collect corresponding simulation datasets indicative of an operating state of the network device. The processor may determine a level of similarity between the simulation datasets, and select, responsive to a comparison of the level of similarity to a diversity threshold, a subset of the simulation datasets. The processor may generate, based on the selected subset of the simulation datasets, a model representative of the network device that predicts, responsive to configuration parameters for the network device, an operating state of the network device.

Providing diversity in simulation datasets during modeling of network devices

Automated configuration and data collection during modeling of network devices

The techniques describe a network device comprising one or more processors configured to: receive configuration data configuring a plurality of virtual network nodes, wherein the configuration data configures a virtual client node including a corresponding line card having a port connected to a first customer network device, and configures a virtual core node including a corresponding line card having a port connected to a core network; provision a layer-2 (L2) circuit that includes, as an access interface, an interface logically connecting the virtual client node and virtual core node, wherein the L2 circuit provides connectivity between the virtual client node and a remote virtual client node; and forward, via the L2 circuit, packets between the virtual client node and the remote virtual client node to realize a logical network between the first customer network device and a second customer network device connected to the remote virtual PE node.

Network as a service using virtual nodes

A controller device manages a plurality of network devices. The controller device is configured to receive, for a data structure, a configlet specifying a set of configuration changes to be applied to a resource of a plurality of resources of the plurality of network devices. A low level configuration for each respective owned resource of a set of owned resources of the plurality of resources includes a pointer indicating an owner for the respective owned resources. The one or more processing units are further configured to determine the set of configuration changes does not conflict in response to determining the low level configuration for the resource does not include a pointer indicating the owner for the resource is not the configlet and apply the set of configuration changes to the resource in response to determining the set of configuration changes does not conflict with the set of owned resources.

Programmable configlets through opaque intents in graph based intent controllers

A controller device manages a plurality of network devices. The controller device includes one or more processing units configured to receive an upgrade request; determine an upgrade graph having nodes each representing one of the network devices or a network service provided by the network, and also having one or more edges each connecting two of the nodes and representing a network redundancy or service dependency; compute and assign, an edge weight to each edge by combining results of at least one objective function, each of the at least one objective functions having a minimum objective or maximum objective for the network; partition the upgrade graph into a plurality of sub-groups based on the edge weights; determine an upgrade schedule; and upgrade software of each of the plurality of network devices according to the upgrade schedule.

Growing community of inventors

Valencia, Spain

Javier Antich