Skip to main content

Arista Introduces Universal Network Observability

Arista Networks 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.

“Bringing together multiple network domains with full application visibility and troubleshooting will streamline network operations and improve uptime and reliability. Disparate operating systems and lack of consistent data models across networks have made delivering systems with this degree of visibility previously impossible,” stated Zeus Kerravala, Principal Analyst at ZK Research. “Moreover, in an era characterized by stringent regulatory compliance, cybersecurity and observability throughout the enterprise is no longer optional but rather an essential imperative.”

CV UNO delivers 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.

“Our customers have been demanding a composite system that provides seamless observability across network domains, prevents human errors, rapidly identifies root cause issues, and aids network engineers and operators to troubleshoot application performance issues,” stated Douglas Gourlay, VP and GM, Cloud Networking Software. “Arista’s Universal Network Observability, built upon Arista EOS® and CloudVision platforms, fulfills this critical client need.”

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.

Arista’s CV UNO has been in active customer trials with general availability as a premium option on CloudVision scheduled for Q2 2024.

The Latest

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Arista Introduces Universal Network Observability

Arista Networks 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.

“Bringing together multiple network domains with full application visibility and troubleshooting will streamline network operations and improve uptime and reliability. Disparate operating systems and lack of consistent data models across networks have made delivering systems with this degree of visibility previously impossible,” stated Zeus Kerravala, Principal Analyst at ZK Research. “Moreover, in an era characterized by stringent regulatory compliance, cybersecurity and observability throughout the enterprise is no longer optional but rather an essential imperative.”

CV UNO delivers 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.

“Our customers have been demanding a composite system that provides seamless observability across network domains, prevents human errors, rapidly identifies root cause issues, and aids network engineers and operators to troubleshoot application performance issues,” stated Douglas Gourlay, VP and GM, Cloud Networking Software. “Arista’s Universal Network Observability, built upon Arista EOS® and CloudVision platforms, fulfills this critical client need.”

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.

Arista’s CV UNO has been in active customer trials with general availability as a premium option on CloudVision scheduled for Q2 2024.

The Latest

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...