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ExtraHop Unveils Healthcare Edition

ExtraHop Networks announced the ExtraHop Healthcare Edition, an IT Operations Analytics (ITOA) solution with the ability to provide heterogeneous, real-time visibility into all HL7 transactions within a healthcare environment.

Healthcare IT and business leaders can now proactively discover and map HL7 communications across interfaces, analyze the performance and effectiveness of clinical workflows, and derive a wide range of valuable operational and business insights. This capability, combined with ExtraHop’s market leading cross-tier application performance, availability, and security monitoring makes the new Healthcare Edition the most comprehensive solution for Health IT on the market.

According to Gartner analyst, Barry Runyon, in the August 2014 report, Situational Awareness Is at the Heart of the Real-Time Healthcare System, “Situational awareness is the engine behind various ‘hospital of the future,’ ‘digital hospital’ and ‘smart patient room’ initiatives. It is at the heart of the real-time healthcare system. Situational awareness involves: (1) gathering information; (2) understanding that information in context; and (3) making short-term projections based on the current state. HDOs are real-time healthcare systems to the extent that they have mastered situational awareness. HDO CIOs will need to create situational awareness and intelligence in an environment rich with device technology and immature in technologies that create an integrated intelligence that crosses the IT/OT divide.”

Given these pressures, healthcare CIOs are increasingly looking for ways to address these challenges by leveraging innovative technology. In response, ExtraHop has introduced a Healthcare Edition of its leading Wire Data Analytics platform, a product specially designed to overcome the significant performance, end-user experience, data integration, and real-time analysis challenges facing healthcare organizations.

In addition to the value that the Healthcare Edition provides to a wide range of customers, ExtraHop’s recently-announced Open Data Stream technology allows healthcare IT teams to stream the ExtraHop dataset to a highly scalable, non-proprietary database like MongoDB, or a powerful search, analytics, and data visualization suite like the Elasticsearch ELK stack, enabling customers to achieve the following:

- Richer and deeper insights by comparing and contrasting healthcare data from multiple sources.

- Greater control over where critical patient data is stored and how it is queried, manipulated, and collected.

- Increased flexibility of available business intelligence and analytics tools.

“Healthcare IT professionals face management and visibility challenges associated with the recent explosion of data in their environments,” said Jesse Rothstein, CEO and co-founder of ExtraHop. “With this announcement, we are ushering in a new era of comprehensive IT and business insight for healthcare organizations. ExtraHop’s solutions enable these teams to more effectively derive valuable intelligence from the massive amounts of data they are currently struggling to manage.”

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ExtraHop Unveils Healthcare Edition

ExtraHop Networks announced the ExtraHop Healthcare Edition, an IT Operations Analytics (ITOA) solution with the ability to provide heterogeneous, real-time visibility into all HL7 transactions within a healthcare environment.

Healthcare IT and business leaders can now proactively discover and map HL7 communications across interfaces, analyze the performance and effectiveness of clinical workflows, and derive a wide range of valuable operational and business insights. This capability, combined with ExtraHop’s market leading cross-tier application performance, availability, and security monitoring makes the new Healthcare Edition the most comprehensive solution for Health IT on the market.

According to Gartner analyst, Barry Runyon, in the August 2014 report, Situational Awareness Is at the Heart of the Real-Time Healthcare System, “Situational awareness is the engine behind various ‘hospital of the future,’ ‘digital hospital’ and ‘smart patient room’ initiatives. It is at the heart of the real-time healthcare system. Situational awareness involves: (1) gathering information; (2) understanding that information in context; and (3) making short-term projections based on the current state. HDOs are real-time healthcare systems to the extent that they have mastered situational awareness. HDO CIOs will need to create situational awareness and intelligence in an environment rich with device technology and immature in technologies that create an integrated intelligence that crosses the IT/OT divide.”

Given these pressures, healthcare CIOs are increasingly looking for ways to address these challenges by leveraging innovative technology. In response, ExtraHop has introduced a Healthcare Edition of its leading Wire Data Analytics platform, a product specially designed to overcome the significant performance, end-user experience, data integration, and real-time analysis challenges facing healthcare organizations.

In addition to the value that the Healthcare Edition provides to a wide range of customers, ExtraHop’s recently-announced Open Data Stream technology allows healthcare IT teams to stream the ExtraHop dataset to a highly scalable, non-proprietary database like MongoDB, or a powerful search, analytics, and data visualization suite like the Elasticsearch ELK stack, enabling customers to achieve the following:

- Richer and deeper insights by comparing and contrasting healthcare data from multiple sources.

- Greater control over where critical patient data is stored and how it is queried, manipulated, and collected.

- Increased flexibility of available business intelligence and analytics tools.

“Healthcare IT professionals face management and visibility challenges associated with the recent explosion of data in their environments,” said Jesse Rothstein, CEO and co-founder of ExtraHop. “With this announcement, we are ushering in a new era of comprehensive IT and business insight for healthcare organizations. ExtraHop’s solutions enable these teams to more effectively derive valuable intelligence from the massive amounts of data they are currently struggling to manage.”

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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 ...

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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 ...