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Gigamon Extends Analytics of Empirix IntelliSight

Gigamon has teamed with Empirix to extend the analytical capabilities of the Empirix IntelliSight customer experience and performance management platform.

The combination of the Gigamon Visibility Fabric with the IntelliSight platform enables Empirix service providers to improve customer experience with data-intense applications such as video, voice and machine-to-machine (M2M) communications. This advanced solution combines the advanced traffic intelligence of the Gigamon platform with IntelliSight to transform volumes of data into real-time understanding of user experiences, which allows service providers to raise service levels and increase profitability.

“As content grows ever richer and real-time applications proliferate, especially in the enterprise and unified communications space, they generate higher volumes of network traffic that challenges service providers to maintain and improve performance levels,” said Franco Messori, Chief Strategy Officer at Empirix. “The more traffic a service analytic solution has to process, the longer it takes to do its essential work of identifying trends that could lead to customer impacting issues. Gigamon’s data filtering and aggregation functionality, in conjunction with the ability to dynamically change configurations, directly complements IntelliSight’s capabilities. Together, the solutions enable service providers to see their networks from their customers’ perspectives, which is key to customer acquisition and retention.”

Empirix IntelliSight can ingest vast quantities of data leveraging intelligent optimization to better understand customer experience, application and performance management, as well as enhance the ability to make strategic business decisions. Its advanced data visualization options enable users of all technical abilities to quickly derive meaning from mountains of data, enabling providers to anticipate and pinpoint in real time service quality and network systems issues that affect applications and customers.

“Carriers are constantly exploring new paths to monetization, and that journey begins with having clear insight into how their own infrastructure is being utilized by their subscribers,” said Shehzad Merchant, CTO at Gigamon. “As the carrier infrastructure evolves to a converged 4G/LTE infrastructure with new applications running over that infrastructure, Gigamon’s Visibility Fabric solutions provide pertinent, correlated, de-duplicated, and highly optimized traffic feeds to Empirix’s IntelliSight platform. This provides carriers with a deeper insight into their infrastructure, which in turn results in the ability to pinpoint issues and resolve problems faster in order to meet service level agreements while also offering the ability to create new and innovative premium services.”

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Gigamon Extends Analytics of Empirix IntelliSight

Gigamon has teamed with Empirix to extend the analytical capabilities of the Empirix IntelliSight customer experience and performance management platform.

The combination of the Gigamon Visibility Fabric with the IntelliSight platform enables Empirix service providers to improve customer experience with data-intense applications such as video, voice and machine-to-machine (M2M) communications. This advanced solution combines the advanced traffic intelligence of the Gigamon platform with IntelliSight to transform volumes of data into real-time understanding of user experiences, which allows service providers to raise service levels and increase profitability.

“As content grows ever richer and real-time applications proliferate, especially in the enterprise and unified communications space, they generate higher volumes of network traffic that challenges service providers to maintain and improve performance levels,” said Franco Messori, Chief Strategy Officer at Empirix. “The more traffic a service analytic solution has to process, the longer it takes to do its essential work of identifying trends that could lead to customer impacting issues. Gigamon’s data filtering and aggregation functionality, in conjunction with the ability to dynamically change configurations, directly complements IntelliSight’s capabilities. Together, the solutions enable service providers to see their networks from their customers’ perspectives, which is key to customer acquisition and retention.”

Empirix IntelliSight can ingest vast quantities of data leveraging intelligent optimization to better understand customer experience, application and performance management, as well as enhance the ability to make strategic business decisions. Its advanced data visualization options enable users of all technical abilities to quickly derive meaning from mountains of data, enabling providers to anticipate and pinpoint in real time service quality and network systems issues that affect applications and customers.

“Carriers are constantly exploring new paths to monetization, and that journey begins with having clear insight into how their own infrastructure is being utilized by their subscribers,” said Shehzad Merchant, CTO at Gigamon. “As the carrier infrastructure evolves to a converged 4G/LTE infrastructure with new applications running over that infrastructure, Gigamon’s Visibility Fabric solutions provide pertinent, correlated, de-duplicated, and highly optimized traffic feeds to Empirix’s IntelliSight platform. This provides carriers with a deeper insight into their infrastructure, which in turn results in the ability to pinpoint issues and resolve problems faster in order to meet service level agreements while also offering the ability to create new and innovative premium services.”

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In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.