Net Optics announced the general availability of two significant advances.
Phantom Virtualization Tap Version 3.0 for ESXi 5.x:
- Extends kernel level monitoring to ESXi 5.0 and 5.1
- Enables intelligent, continuous monitoring through deep VMware vCenter integration
- Offers intuitive, click-through deployment and administration with a newly designed GUI and management console
Phantom HD Version 3.0:
- Enables high-density, high-throughput network monitoring in environments using advanced tunneling protocols
- Performs traffic deduplication to ensure that tools inspect only a single copy of each relevant session
- Decapsulates and strips protocols to allow optimal tool utilization—both physical and virtual
Phantom Virtualization Tap Version 3.0 offers kernel-level monitoring for vSphere 5.x. This capability offers efficient, non-disruptive, VMware-certified software for monitoring traffic in virtual environments.
This solution is a major resource for customers running VMware ESXi 5.x who require visibility into East-West traffic between virtual servers.
Phantom 3.0 addresses the growing “black hole,” which keeps inter-VM and cross-blade traffic invisible to network monitoring tools, leaving the network vulnerable to threats, non-compliance, loss of availability and impaired performance.
The Phantom Virtualization Tap aggregates traffic from multiple VMs and delivers raw network data to monitoring tools.
“Our latest version strengthens control of the virtual environment substantially, helping customers stay secure and audit reliably for compliance,” says Ran Nahmias, Net Optics Senior Director, Virtualization & Cloud Solutions. “This open community Tap is v-switch and tool agnostic. It reinforces and extends the value of our customers’ physical tool investments while requiring no changes and creating no single point of failure.”
Phantom HD 3.0 incorporates advanced new functionality, performing packet management, tunnel decapsulation and network traffic management, all on a single device that addresses not only virtualized/converged environments but physical environments as well.
Phantom HD 3.0 aggregates inter-VM traffic that has been tunneled out of ESX hosts encapsulated in sophisticated new protocols. The drawback to those protocols is that they often make traffic invisible to monitoring tools—laying the network open to threats and intrusion. The purpose-built Phantom HD appliance swiftly decapsulates that traffic and sends it on in raw form to the tools, which can now perform their vital security functions unimpeded.
Phantom HD 3.0 also resolves a persistent concern of customers whose networks are virtualizing or whose architecture employs complex tunneling technologies—namely removal of duplicate traffic captured in various areas of the network. Phantom HD 3.0 deduplicates and reduces the costly “packet payload overhead” placed on these tools, optimizing their performance and value.
“This solution eliminates feeding customer tools duplicate captures by “de-duping” the traffic,” says Nahmias. “Now the tools are able to process only a single copy of that traffic of interest—optimizing and preserving a customer’s network and tooling resources.”
Both Phantom Virtualization Tap 3.0 and Phantom HD 3.0 are available now. Phantom HD ships as a physical or virtual appliance, deployable in all areas of the hybrid data center.
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 ...