Webinar Sept 12, 2024 - 10AM PT / 1PM ET
The Observability Series
Session 1: Introducing CloudVision Universal Network Observability
At Arista, observability goes beyond traditional network monitoring. CloudVisionⓇ Universal Network ObservabilityTM(CV UNOTM) together with DANZ Monitoring Fabric (DMF) empowers network administrators to gain pervasive visibility with integrated network, application state and performance awareness. CV UNO leverages AI/ML on the integrated application and network data, enabling them to pinpoint the root-cause of issues with simplicity and agility, helping to reduce Mean Time To Resolution (MTTR).
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About the webinar
Session 1: Introducing CloudVision Universal Network Observability
September 12, 2024 - 10AM PT / 1PM ET
Networking teams often struggle with application-related issues due to limited visibility beyond the network boundary. Arista Networks has developed CloudVision Universal Network Observability (CV UNO) to address this. Building on Arista's NetDL foundation, CV UNO enhances application visibility for network operators by integrating data from network infrastructure, compute, and server systems, providing application-aware network performance management.
CV UNO builds on Arista’s existing network infrastructure capabilities, offering insights into applications (from vCenter) and third-party devices (routers). It uses machine learning to deliver more accurate insights and faster issue resolution. By incorporating telemetry and flow data from diverse systems and integrating with other Arista products, CV UNO enhances network operations, improves uptime, and enriches the overall user experience.
In our first of a new series in Network Observability, this Arista Netbuilders session will introduce CloudVision Universal Network Observability (CV UNO) with demos on how Arista CloudVision UNO can be leveraged by network operators to reduce mean time to innocence and also correlate application issues to any network events (change controls, packet drops) or even server related issues.