Cognitive Campus

Arista Cognitive Cloud Networking for the Campus takes a simplified approach to addressing campus network challenges compared to the siloed complexity of legacy solutions. Based on the same open cloud networking principles used to build modern cloud datacenters, Arista’s Cognitive Cloud Networking leverages EOS^® and CloudVision^®, extending the Universal Cloud Network (UCN) architecture to the campus. Leveraging a consistent software-driven approach reduces complexity, leads to higher reliability and performance and streamlines automation, monitoring and security.

Featured Video: Arista Networks Introducing the Cognitive Campus

Arista’s Cognitive Cloud Networking for the Campus is based on three principles:

Universal Cloud Network - Offered as an alternative to brittle, proprietary solutions from legacy vendors, Arista UCN is an open, standards-based design focusing on software-driven control principles. Arista’s collapsed Spline™ architecture, utilizing its spine, POE leaf switches, and Wi-Fi platforms, consolidates campus layers into simpler topologies that reduce costs and improve reliability.

Cognitive Management Plane - There is a dire void in management plane consistency and a need for data-driven analytics in the campus, as in the data center. Arista believes that a common model can be applied across both, saving customers operational costs. The Cognitive Management Plane, based on Arista CloudVision is a data-driven repository for the automated actions across network analytics. Cognitive management applies artificial intelligence to identify the root cause of faults and to monitor user experperience.

Securing The Campus - Securing the Campus spline requires a holistic approach to network segmentation, device compliance and auditing, as well as service integration with Arista’s security partners. Arista delivers these capabilities through EOS and CloudVision. Arista campus leaf switches provide non sampled flow analytics to CloudVision and third party consumers of IPFIX. CloudVision provides graphical representation of who is talking to whom and other flow information to simplify visualization of campus workloads