Cisco Technology, Inc.

Jigar Dinesh Parekh

Vinay Prabhu

Sarah Adelaide Evans

Suraj Rangaswamy

Laxmikantha Reddy Ponnuru

Satyajit Das

Ashish Shendure

Pranav Narasimmaraj

Vandhana Somaskanthan

Neha Malhotra

Renuka Mohan Channapatna

Huayu Fu

Prithvi Sharan

Parth Sanjiv Doshi

In one embodiment, a method includes determining, by a network node, that a first plurality of tunnel interfaces resides in a core region of a network and determining, by the network node, that a second plurality of tunnel interfaces resides in an access region of the network. The method also includes configuring, by the network node, a first tunnel interface as a core regional fallback path for the core region of the network and configuring, by the network node, a second tunnel interface as an access regional fallback path for the access region of the network.

Ultimate regional fallback path for hierarchical SD-WAN

Systems, methods, and computer-readable media for scaling a source network. A system may be configured to receive a network configuration for a source network, wherein the source network comprising a plurality of nodes, receive and a scale target for a scaled network, and identify, based on the scale target, one or more selected nodes in the plurality of nodes in the source network for implementing in the scaled network. The system may further be configured to reconfigure data plane parameters and control plane parameters for each node in the one or more selected nodes.

Network scale emulator

Systems, methods, and computer-readable media for designing network performance and configuration include determining one or more use cases for a network to be provisioned, based on at least one or more business verticals related to a customer of the network. A data plane scale is determined from the use cases and an initial data plane scale generated using a linear regression on one or more data plane parameters. The data plane parameters include a platform type, feature set, packet size, or software version of the network. A control plane scale is determined from the use cases and an initial control plane scale generated using a linear regression on one or more control plane parameters of the network. The control plane parameters include a platform type, feature set, or software version of the network. The network is provisioned for the data plane scale and the control plane scale.

Tool for network performance design and configuration

Systems, methods, and computer-readable media for predicting policy changes in a network environment through a data serialization language. Running configurations of one or more network devices in a network environment can be collected. Further, a master device template of a new policy for the network environment can be generated through a data serialization language based on the running configurations of the one or more network devices. The master device template can include a directory-based tree structure of a simulated implementation of the new policy in the network environment. Policy changes in the network environment for the new policy can be predicted before implementing the new policy in the network environment based on simulated packet traversal through the directory-based tree structure of the simulated implementation of the policy in the network environment.

Live network sandboxing on a centralized management system

Growing community of inventors

Fremont, CA, United States of America

Jigar Dinesh Parekh