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Net Optics Phantom HD Goes Virtual with Version 2.0

Net Optics announced Phantom HD Virtual 2.0, a leap forward in the handling of virtual traffic of interest across the entire cloud infrastructure.

The new Phantom HD advance makes Net Optics the first company to virtualize tool-agnostic monitoring and access solutions for remote rapid deployments in virtualized data center and cloud computing environments.

Virtualization and consolidation call for particularly high levels of network integrity because in a virtual landscape, applications and administrative functions share common resources. The consequences of a failed, hacked or mismanaged element can extend to countless applications and users. Only with total visibility to monitor both the physical and virtual arenas can a company realize virtualization’s many benefits.

The Phantom HD 2.0:

- Extends monitoring and access across LAN/WAN/Cloud infrastructures and inter-VM traffic at high wire speeds, helping customers overcome barriers to total traffic visibility and achieve true computing mobility and inspection throughout locations, datacenters and devices in virtualized deployments.

- Is offered both as a virtual and physical appliance.

- Performs MPLS stripping, VN-Tag Stripping and Cisco FabricPath Stripping.

- Optimizes terminating and de-capsulating of the “tunnels” that transport traffic of interest from virtual networks to the instrumentation layer and can also encapsulate raw traffic of interest that needs to be transported to a remote location for inspection or storage.

- Permits the aggregation of Phantom Virtualization Taps, Net Optics Network Taps and the devices of other vendors.

- Is part of the Phantom Solution, which eases the virtualization transition by converging physical and virtual monitoring infrastructures.

With data centers virtualizing at a blistering pace, the monitoring infrastructure often struggles to keep up. Phantom HD 2.0 streamlines the processes of virtualization — needing no physical, wired connection between the monitoring and access layers and instrumentation layers. In the past, total monitoring and access capability demanded expensive physical hardware and installation on the data center floor (“boots on the ground”). But Phantom HD Virtual 2.0 appliance now offers these comprehensive capabilities as software that can be delivered, installed and configured remotely.

The new Phantom HD 2.0 high-throughput appliance allows switching layer and instrumentation layer devices such as high-end routers to perform the sophisticated functions they were designed for—rather than being wastefully employed on routine GRE de-capsulation tasks.

Also, users bridging virtual traffic to physical monitoring tools needn’t wrestle with the drawbacks of SPAN Ports or Promiscuous Mode on Virtual Switches.

Customers can gain the full benefit of their investment in these expensive products; in fact, virtualizing the Phantom HD can eliminate the purchase of costly new tools overall, holding down CAPEX, training and operations costs.

The Latest

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 ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Net Optics Phantom HD Goes Virtual with Version 2.0

Net Optics announced Phantom HD Virtual 2.0, a leap forward in the handling of virtual traffic of interest across the entire cloud infrastructure.

The new Phantom HD advance makes Net Optics the first company to virtualize tool-agnostic monitoring and access solutions for remote rapid deployments in virtualized data center and cloud computing environments.

Virtualization and consolidation call for particularly high levels of network integrity because in a virtual landscape, applications and administrative functions share common resources. The consequences of a failed, hacked or mismanaged element can extend to countless applications and users. Only with total visibility to monitor both the physical and virtual arenas can a company realize virtualization’s many benefits.

The Phantom HD 2.0:

- Extends monitoring and access across LAN/WAN/Cloud infrastructures and inter-VM traffic at high wire speeds, helping customers overcome barriers to total traffic visibility and achieve true computing mobility and inspection throughout locations, datacenters and devices in virtualized deployments.

- Is offered both as a virtual and physical appliance.

- Performs MPLS stripping, VN-Tag Stripping and Cisco FabricPath Stripping.

- Optimizes terminating and de-capsulating of the “tunnels” that transport traffic of interest from virtual networks to the instrumentation layer and can also encapsulate raw traffic of interest that needs to be transported to a remote location for inspection or storage.

- Permits the aggregation of Phantom Virtualization Taps, Net Optics Network Taps and the devices of other vendors.

- Is part of the Phantom Solution, which eases the virtualization transition by converging physical and virtual monitoring infrastructures.

With data centers virtualizing at a blistering pace, the monitoring infrastructure often struggles to keep up. Phantom HD 2.0 streamlines the processes of virtualization — needing no physical, wired connection between the monitoring and access layers and instrumentation layers. In the past, total monitoring and access capability demanded expensive physical hardware and installation on the data center floor (“boots on the ground”). But Phantom HD Virtual 2.0 appliance now offers these comprehensive capabilities as software that can be delivered, installed and configured remotely.

The new Phantom HD 2.0 high-throughput appliance allows switching layer and instrumentation layer devices such as high-end routers to perform the sophisticated functions they were designed for—rather than being wastefully employed on routine GRE de-capsulation tasks.

Also, users bridging virtual traffic to physical monitoring tools needn’t wrestle with the drawbacks of SPAN Ports or Promiscuous Mode on Virtual Switches.

Customers can gain the full benefit of their investment in these expensive products; in fact, virtualizing the Phantom HD can eliminate the purchase of costly new tools overall, holding down CAPEX, training and operations costs.

The Latest

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 ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...