Velocent Systems and Ixia announced a partnership that will bring together the companies' technologies to help customers accurately monitor mobile networks of any size.
The combined technologies from Velocent Systems and Ixia capture and analyze network traffic in a scalable solution.
“Through this strategic partnership with Ixia, our customers will have access to utmost scalability and accuracy, features that are becoming ever more critical in today’s fast-growing market,” said Jagadeesh Dantuluri, VP of Marketing and PLM, Velocent Systems. “The Ixia Net Tool Optimizer (NTO) and GTP Session Controller (GSC) will provide complete network access for OneVu, offering scalability up to 320 Gigabits per second (Gbps).”
The Ixia NTO will passively direct out-of-band network traffic from multiple access points (SPAN ports or TAPs) in the network to Velocent CEA LexaVu monitoring systems for analysis. Traffic will be aggregated from all needed access points in the network to provide comprehensive visibility. In addition, the Ixia GSC correlates all GTP sessions enabling monitoring solutions to scale more efficiently by offloading the aggregation and correlation of subscriber data from monitoring systems.
The joint solution also offers the following features:
- Full network visibility – Provides operators with unique visibility into data traffic across an increasingly complex environment in which voice evolves onto data and machine-to-machine (M2M) communications continue to proliferate.
- Simplified deployment – Provides a simplified methodology for addressing the complexity of end-to-end network monitoring, as well as management of visibility systems through a central architecture and advanced traffic aggregation and filtering capabilities.
- Easy, affordable scalability – Delivers a cost effective solution to scale network visibility as data, voice and video bandwidths continue to rise.
“Ixia’s network visibility solutions complement Velocent’s OneVu CEA by extending access to all needed mobile network traffic. The joint solution provides complete visibility into network traffic in a highly scalable, easy-to-deploy system,” said Roark Pollock, VP of Network Visibility Solutions Marketing, Ixia.
“As the capacities of individual Mobile Core Gateway nodes are increasing into hundreds of Gbps, network operators can depend on Velocent’s CEA solution to help with customer experience management (CEM), Big Data and VoLTE, scaling from hundreds of Gbps on the low-end up to Terabits per second (Tbps),” said Dantuluri.
The joint Ixia-Velocent solution is immediately available to mobile operators.
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 ...