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Arista Introduces DANZ Monitoring Fabric

Arista Networks announced a network observability software, DANZ Monitoring Fabric (DMF), on Arista switching platforms for enterprise-wide traffic visibility and contextual insights.

This new offering enables mission-critical monitoring for enterprise-wide traffic while improving efficiencies and reduced opex through the adoption of modern cloud networking principles.

Arista is introducing a new generation of network observability – to bring cloud networking principles, data analytics and contextual insights. By integrating its Data Analyzer with acquired Big Switch’s monitoring fabric software, Arista is introducing DMF software for enterprise-wide network observability.

The DMF offering is based upon Arista’s popular switching platforms with optional advanced nodes including:

- Service Node software for packet processing, optimization and flow generation

- Analytics Node software for deep context-aware traffic analysis and machine learning

- Recorder Node software for full packet capture, query and replay with built-in application identification

Arista DMF is optimized for pervasive observability based on cloud networking principles using scale-out leaf-spine, clustering architecture and API-first programmability model. The DMF console provides zero-touch workflows to streamline enterprise-wide deployment, thereby accelerating service activation. DMF’s multi-tenant capability enables NetOps, SecOps and DevOps teams to consume DMF as an IT service to reduce monitoring costs further.

Arista DMF delivers a fully integrated network time machine experience. DMF’s system-level approach delivers metadata and associated contexts to the Analytics Node cluster and packet capture to the Recorder Node cluster. This integrated one-click workflow across nodes allows operators to zero-in on anomalies that have occurred in the past by instantaneously retrieving historical network traffic. The DMF Analytic Node’s machine learning capability dynamically identifies anomalous network behaviors through auto-baselining. For tracing malicious activities, The DMF Recorder Node provides one-click traffic replay to designated security tools in order to recreate their spreading behavior.

With DMF’s support for Arista’s flagship 7280R3 platforms with 25G and 100G interfaces, Arista assures reliable observability solutions for mission-critical monitoring. DMF’s flexible fabric ensures security tools receive all relevant network traffic to detect and hunt threats. DMF integrates with Awake Security’s Network Detection and Response (NDR) -- Arista’s recent security acquisition -- to deliver traffic to various NDR ingests points, thus bringing zero-trust security to enterprises.

The Arista DMF Software is procured as a multi-year subscription license, with availability is as follows:

- DMF for 7050X3 (25G and 100G) platforms is shipping now

- DMF Service Node software supporting 40G, 160G and now 320G performance with scale-out clustering support, enabling multi-Terabit processing capacity, is shipping now

- Network Time Machine integrated workflows with DMF Analytics Node and DMF Recorder Node are shipping now

- DMF software support for 7280R3 (10G, 25G and 100G) platforms for mission-critical observability will be available starting Q1 2021

- DMF support for open networking platforms is shipping

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Arista Introduces DANZ Monitoring Fabric

Arista Networks announced a network observability software, DANZ Monitoring Fabric (DMF), on Arista switching platforms for enterprise-wide traffic visibility and contextual insights.

This new offering enables mission-critical monitoring for enterprise-wide traffic while improving efficiencies and reduced opex through the adoption of modern cloud networking principles.

Arista is introducing a new generation of network observability – to bring cloud networking principles, data analytics and contextual insights. By integrating its Data Analyzer with acquired Big Switch’s monitoring fabric software, Arista is introducing DMF software for enterprise-wide network observability.

The DMF offering is based upon Arista’s popular switching platforms with optional advanced nodes including:

- Service Node software for packet processing, optimization and flow generation

- Analytics Node software for deep context-aware traffic analysis and machine learning

- Recorder Node software for full packet capture, query and replay with built-in application identification

Arista DMF is optimized for pervasive observability based on cloud networking principles using scale-out leaf-spine, clustering architecture and API-first programmability model. The DMF console provides zero-touch workflows to streamline enterprise-wide deployment, thereby accelerating service activation. DMF’s multi-tenant capability enables NetOps, SecOps and DevOps teams to consume DMF as an IT service to reduce monitoring costs further.

Arista DMF delivers a fully integrated network time machine experience. DMF’s system-level approach delivers metadata and associated contexts to the Analytics Node cluster and packet capture to the Recorder Node cluster. This integrated one-click workflow across nodes allows operators to zero-in on anomalies that have occurred in the past by instantaneously retrieving historical network traffic. The DMF Analytic Node’s machine learning capability dynamically identifies anomalous network behaviors through auto-baselining. For tracing malicious activities, The DMF Recorder Node provides one-click traffic replay to designated security tools in order to recreate their spreading behavior.

With DMF’s support for Arista’s flagship 7280R3 platforms with 25G and 100G interfaces, Arista assures reliable observability solutions for mission-critical monitoring. DMF’s flexible fabric ensures security tools receive all relevant network traffic to detect and hunt threats. DMF integrates with Awake Security’s Network Detection and Response (NDR) -- Arista’s recent security acquisition -- to deliver traffic to various NDR ingests points, thus bringing zero-trust security to enterprises.

The Arista DMF Software is procured as a multi-year subscription license, with availability is as follows:

- DMF for 7050X3 (25G and 100G) platforms is shipping now

- DMF Service Node software supporting 40G, 160G and now 320G performance with scale-out clustering support, enabling multi-Terabit processing capacity, is shipping now

- Network Time Machine integrated workflows with DMF Analytics Node and DMF Recorder Node are shipping now

- DMF software support for 7280R3 (10G, 25G and 100G) platforms for mission-critical observability will be available starting Q1 2021

- DMF support for open networking platforms is shipping

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...