Arista Networks, Inc. announced a new network observability software offering merging network infrastructure performance and data from compute and server systems-of-record to deliver keen insights into application and workload performance across data center, campus, and wide area networks. Arista?s CloudVision®Universal Network Observability? (CV UNO?) system, available as a premium feature license on Arista CloudVision, enables the automation of network, systems, and application/workload visibility, coupled with AI-driven proactive analysis and prescriptive recommendations, which significantly reduces human error, accelerates issue resolution for unforeseen events, and provides precise root cause analysis of network events and their impact on application delivery.

CV UNO delivers unique systems-level capabilities to reduce enterprise risk, allow rapid fault detection and correction, and simplify cross-functional coordination, hastening time-to-recovery whether the root cause was network, platform, systems, or application-related. Key benefits include: Workload Application and Infrastructure Discovery: CV UNO automatically discovers applications, hosts, and workloads across various platforms and IT systems of record and inventory management systems. This holistic data, coupled with CloudVision?s deep view of the networking state within Arista Network Data Lake (NetDL?), CV UNO, presents a composite picture of the entire network and application environment. Additionally, it builds an application-to-network graph that is continuously refreshed and stored in time series to show a historical record of the environment?s evolution and state at any point in time.

Proactive Risk Analysis: With real-time application-to-network graphing, CV UNO enables proactive risk analysis as part of the change management workflow, cross-referencing, and impact analysis of network issues and anomalies. Potentially disruptive network changes can be assessed for their impact before being deployed into production and mission-critical networks. Realtime Network Change Impact Analysis: CV UNO also delivers deep analysis and machine learning to this composite dataset within NetDL that can determine when network provisioning or state changes have affected business and critical applications.

When a network change disrupts an application?s performance, CV UNO automatically identifies what change impacted which application or workload and empowers the network engineering and operations teams to remediate the issue quickly. Host or Application Change Impact Analysis: In the case where a host or virtualization issue is impacting application performance and the network remains unchanged, CV UNO, without deploying any host-based agents, is also able to quickly direct the operator or engineer to the accurate root cause of the issue, thereby reducing the resolution time and cross-functional coordination for the operations team. Topology-Aware Determination: By aggregating a holistic view across all infrastructure systems, virtualization machines, systems of record, and network flow and state data, CV UNO can accurately determine the root cause of application performance issues, avoiding the common finger-pointing associated with legacy approaches.

CV UNO consists of the following components: CV UNO Sensor collects, normalizes, and curates flow/SNMP data from various sources like VMware vCenter, DANZ Monitoring Fabric, and third-party network devices and forwards them to NetDL. CV UNO, enabled via a premium feature license, integrates into and enhances CloudVision?s operational and network telemetry capabilities by leveraging Machine Intelligence-based Analysis on data stored in NetDL to infer topology-aware correlations across events, changes, and anomalies, thereby accelerating root cause analysis and expediting issue resolution. CV UNO Recorder Node (optional) adds packet capture, query, and packet replay capabilities to support intrusion detection, incident response, and forensic use cases.

CV UNO Service Node (optional) enables advanced packet processing functions, like end-to-end application latency analysis and DPI-based Application Identification and classification. CV UNO Analytics Node (optional) enables distributed context-aware traffic analysis and machine learning capabilities for large-scale optimization.