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Ixia Introduces Packet Capture Module

Ixia introduced its Packet Capture Module (PCM), the newest addition to its Visibility Architecture, which provides network engineers with the ability to capture and quickly analyze packets associated with service outages and establish root cause.

Designed to take advantage of the single plane of glass user interface (UI), the packet capture and decode capabilities enable users to troubleshoot performance, security and availability problems. This combination results in a faster mean time to resolution (MTTR) when problems occur.

The PCM is a 48 x 10GE interface card designed for Ixia’s NTO 7300 network packet broker. The PCM enables users to capture traffic manually or to specify a trigger event for network recording, and its circular buffering window automatically retains a configurable amount of packets that both precede and follow any trigger point. The captured files are then stored on the chassis and can be opened on the user’s PC using a third party decoder, or securely transferred to an external location. The UI also offers a built-in decoder allowing users to quickly view and recognize network problems and events without exiting Ixia’s user interface.

“Users expect more from their network every day. Being able to identify and resolve network availability problems is critical to ensuring user quality of experience,” said Scott Register, Senior Director of Product Management for Ixia. “Ixia’s new Packet Capture Module provides network engineers with the ability to quickly capture and evaluate symptomatic traffic for a faster mean time to resolution.”

Key Features:

- Packet capture capability at full 40 GbE line rate with built-in decode functionality.

- Total storage capacity of up to 84GB.

- Individual capture capacity of up to 14 GB.

- Sliding sampling window is buffered to capture pre-event information.

- Onboard and off-board PCAP storage options.

- Feature enabled by drag and drop in the NTO GUI

- Role-based access to packet capture is automatically assigned.

- Packet captures can be initiated manually, via API, or event triggered.

- Extensive list of trigger fields including MAC address, VLAN, Ethernet type, IP address, MPLS label, IP Protocol, TCP control and Layer 4 port.

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Ixia Introduces Packet Capture Module

Ixia introduced its Packet Capture Module (PCM), the newest addition to its Visibility Architecture, which provides network engineers with the ability to capture and quickly analyze packets associated with service outages and establish root cause.

Designed to take advantage of the single plane of glass user interface (UI), the packet capture and decode capabilities enable users to troubleshoot performance, security and availability problems. This combination results in a faster mean time to resolution (MTTR) when problems occur.

The PCM is a 48 x 10GE interface card designed for Ixia’s NTO 7300 network packet broker. The PCM enables users to capture traffic manually or to specify a trigger event for network recording, and its circular buffering window automatically retains a configurable amount of packets that both precede and follow any trigger point. The captured files are then stored on the chassis and can be opened on the user’s PC using a third party decoder, or securely transferred to an external location. The UI also offers a built-in decoder allowing users to quickly view and recognize network problems and events without exiting Ixia’s user interface.

“Users expect more from their network every day. Being able to identify and resolve network availability problems is critical to ensuring user quality of experience,” said Scott Register, Senior Director of Product Management for Ixia. “Ixia’s new Packet Capture Module provides network engineers with the ability to quickly capture and evaluate symptomatic traffic for a faster mean time to resolution.”

Key Features:

- Packet capture capability at full 40 GbE line rate with built-in decode functionality.

- Total storage capacity of up to 84GB.

- Individual capture capacity of up to 14 GB.

- Sliding sampling window is buffered to capture pre-event information.

- Onboard and off-board PCAP storage options.

- Feature enabled by drag and drop in the NTO GUI

- Role-based access to packet capture is automatically assigned.

- Packet captures can be initiated manually, via API, or event triggered.

- Extensive list of trigger fields including MAC address, VLAN, Ethernet type, IP address, MPLS label, IP Protocol, TCP control and Layer 4 port.

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 ...