Skip to main content

Ipanema Announces Research Collaboration with BT

Ipanema Technologies announced a research collaboration with BT to examine Network Functions Virtualization (NFV).

The approach sees researchers at BT’s internationally recognized Adastral Park campus collaborating with counterparts from Ipanema Technologies to examine the potential of the company’s virtual ip|engines. The objective of the research is to demonstrate the ability of Ipanema’s technology to provide virtualized WAN optimization and application performance functionality, removing the need for distributed network devices.

The initial focus of the research has been on key areas of application performance management such as: connectivity, Quality of Service (QoS), acceleration, and reporting. Dr Tim Whitley, MD of Research & Innovation for BT said: “NFV has real potential as a technology, which is why we have a wider program in place to determine exactly which network functions can be virtualized. Effectively managing and controlling application performance remains absolutely critical to BT’s enterprise customers, so we welcome the opportunity to explore the future uses of virtual ip|engines from Ipanema.”

Paul Cobos, VP Global Partners, Ipanema Technologies commented: “We appreciate that the nature of networks and the methods of computing are changing rapidly. Virtualizing our technology has the potential to deliver numerous benefits to our customers, including: reduced expense, quicker deployment, reduced power consumption, hardware independence, and even greater scalability. We are delighted to be working with BT on this research project.”

BT and Ipanema Technologies have an existing commercial relationship that sees Ipanema’s ip|engine devices deployed in BT customer branch and data centre locations. This managed service, branded BT Connect Optimisation, underpins BT Global Services’ Application Performance Management service offer. Working closely together the two companies enable BT’s enterprise customers to guarantee the performance of their critical IT applications (such as ERP, CRM and Unified Communications applications). Ultimately this approach ensures applications work as needed, which significantly improves business productivity and the end-user experience.

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 ...

Ipanema Announces Research Collaboration with BT

Ipanema Technologies announced a research collaboration with BT to examine Network Functions Virtualization (NFV).

The approach sees researchers at BT’s internationally recognized Adastral Park campus collaborating with counterparts from Ipanema Technologies to examine the potential of the company’s virtual ip|engines. The objective of the research is to demonstrate the ability of Ipanema’s technology to provide virtualized WAN optimization and application performance functionality, removing the need for distributed network devices.

The initial focus of the research has been on key areas of application performance management such as: connectivity, Quality of Service (QoS), acceleration, and reporting. Dr Tim Whitley, MD of Research & Innovation for BT said: “NFV has real potential as a technology, which is why we have a wider program in place to determine exactly which network functions can be virtualized. Effectively managing and controlling application performance remains absolutely critical to BT’s enterprise customers, so we welcome the opportunity to explore the future uses of virtual ip|engines from Ipanema.”

Paul Cobos, VP Global Partners, Ipanema Technologies commented: “We appreciate that the nature of networks and the methods of computing are changing rapidly. Virtualizing our technology has the potential to deliver numerous benefits to our customers, including: reduced expense, quicker deployment, reduced power consumption, hardware independence, and even greater scalability. We are delighted to be working with BT on this research project.”

BT and Ipanema Technologies have an existing commercial relationship that sees Ipanema’s ip|engine devices deployed in BT customer branch and data centre locations. This managed service, branded BT Connect Optimisation, underpins BT Global Services’ Application Performance Management service offer. Working closely together the two companies enable BT’s enterprise customers to guarantee the performance of their critical IT applications (such as ERP, CRM and Unified Communications applications). Ultimately this approach ensures applications work as needed, which significantly improves business productivity and the end-user experience.

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 ...