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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.

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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.

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According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

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From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...