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Ixia Introduces Application and Threat Intelligence Processor

Ixia introduced its Application and Threat Intelligence (ATI) Processor, which enhances the network, application and security insights IT organizations get from their existing monitoring tools.

This product provides Ixia’s Visibility Architecture with the ability to provide real-time information about users and applications in any format needed – raw packets, filtered packets or metadata. With the number of valid and malicious applications rapidly increasing, this unprecedented visibility intelligence helps IT organizations within large enterprises and service providers to identify, locate and track network applications – including proprietary, mobile and malicious traffic.

Ixia’s new ATI Processor for the NTO 7300 brings a new level of intelligence to the network packet broker. Distinct Application Fingerprints and a patent pending dynamic identification capability for unknown applications give network managers a complete view of their networks, including application success and failure tracking. By combining rich contextual information such as geo-location of application usage, handset or device type, operating system and browser type, the ATI Processor helps to identify suspicious activity such as unauthorized BYOD usage or business connections from untrusted locations.

Ixia customers can now leverage their monitoring tools in conjunction with the enhanced information provided by the ATI Processor to spot trends in application usage, user behavior and quality of service with more speed and accuracy. This unique insight can also resolve security concerns such as rapidly spotting Command and Control (CnC) traffic from infected systems and policy infractions from BYOD usage. Previously, IT administrators would have to piece together many independent streams of information in a tedious and error-prone process.

The ATI Processor is backed by the same ATI program that fuels Ixia’s test equipment, which includes more than 245 applications and 35,000 malicious attacks and combines frequent Application Fingerprint updates with support of user-defined applications. The specialized hardware employed in the ATI Processor optimizes visibility performance by offloading DPI and metadata extraction, improving tool performance and delivering richer insight into network usage, problems and trends. This functionality delivers greater overall value to our customers.

ATI Processor features include:

- Dynamic application intelligence capabilities to identify known, proprietary, and even unknown network applications.

- Enhanced insight including geo-location, handset type, operating system, browser and other key user data.

- Empirical data generation to identify bandwidth usage, trends and growth needs delivered via API or Ixia’s IxFlow extensions to NetFlow.

“The importance of understanding application performance, service quality and security integrity from the network perspective has been steadily rising in both enterprise and service provider settings,” said Jim Frey, EMA’s VP of Research, Network Management. “Such visibility is essential for timely assurance and protection of complex applications despite growing traffic volumes and increasing diversity in how end users and subscribers access applications and services. Options for DPI processing and identification at the packet access layer, such as Ixia’s new ATI Processor offering, means valuable flexibility for establishing and sustaining effective visibility."

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 ...

Ixia Introduces Application and Threat Intelligence Processor

Ixia introduced its Application and Threat Intelligence (ATI) Processor, which enhances the network, application and security insights IT organizations get from their existing monitoring tools.

This product provides Ixia’s Visibility Architecture with the ability to provide real-time information about users and applications in any format needed – raw packets, filtered packets or metadata. With the number of valid and malicious applications rapidly increasing, this unprecedented visibility intelligence helps IT organizations within large enterprises and service providers to identify, locate and track network applications – including proprietary, mobile and malicious traffic.

Ixia’s new ATI Processor for the NTO 7300 brings a new level of intelligence to the network packet broker. Distinct Application Fingerprints and a patent pending dynamic identification capability for unknown applications give network managers a complete view of their networks, including application success and failure tracking. By combining rich contextual information such as geo-location of application usage, handset or device type, operating system and browser type, the ATI Processor helps to identify suspicious activity such as unauthorized BYOD usage or business connections from untrusted locations.

Ixia customers can now leverage their monitoring tools in conjunction with the enhanced information provided by the ATI Processor to spot trends in application usage, user behavior and quality of service with more speed and accuracy. This unique insight can also resolve security concerns such as rapidly spotting Command and Control (CnC) traffic from infected systems and policy infractions from BYOD usage. Previously, IT administrators would have to piece together many independent streams of information in a tedious and error-prone process.

The ATI Processor is backed by the same ATI program that fuels Ixia’s test equipment, which includes more than 245 applications and 35,000 malicious attacks and combines frequent Application Fingerprint updates with support of user-defined applications. The specialized hardware employed in the ATI Processor optimizes visibility performance by offloading DPI and metadata extraction, improving tool performance and delivering richer insight into network usage, problems and trends. This functionality delivers greater overall value to our customers.

ATI Processor features include:

- Dynamic application intelligence capabilities to identify known, proprietary, and even unknown network applications.

- Enhanced insight including geo-location, handset type, operating system, browser and other key user data.

- Empirical data generation to identify bandwidth usage, trends and growth needs delivered via API or Ixia’s IxFlow extensions to NetFlow.

“The importance of understanding application performance, service quality and security integrity from the network perspective has been steadily rising in both enterprise and service provider settings,” said Jim Frey, EMA’s VP of Research, Network Management. “Such visibility is essential for timely assurance and protection of complex applications despite growing traffic volumes and increasing diversity in how end users and subscribers access applications and services. Options for DPI processing and identification at the packet access layer, such as Ixia’s new ATI Processor offering, means valuable flexibility for establishing and sustaining effective visibility."

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 ...