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ExtraHop Delivers Real-User Monitoring

ExtraHop announced the ExtraHop Real-User Monitoring (RUM) bundle.

The ExtraHop RUM bundle is free to all ExtraHop users, even those using the ExtraHop free-forever Discovery Edition.

“ExtraHop’s approach to user experience management (UEM) is innovative, integrated, and natively extensible in value,” said Dennis Drogseth, vice president, Enterprise Management Associates. “It combines valuable insights into user experience regarding browser, web page, and web page components, with real-time perspectives on network and systems latencies. As such, it’s both a natural and highly-efficient addition to ExtraHop’s broader analytic directions.”

The ExtraHop RUM bundle correlates data delivered by Boomerang with all ExtraHop wire data analysis metrics to show an end-to-end view of the client and all application, network and infrastructure components involved in a web application.

With the RUM bundle, the ExtraHop platform allows IT to measure users’ perceived page-load time against 3,000+ back-end performance metrics such as server processing time and network latency to generate a complete picture of the user’s experience and the infrastructure that delivers it. Web developers have a view of the performance contribution of every object served from any page. In turn, business stakeholders are equipped with the insight they need to understand user experience by web page, browser type, mobile, laptop, and desktop platform to take proactive steps prioritizing development and improving audience experience to keep users engaged.

Other key benefits and capabilities of the ExtraHop RUM bundle include the following:

- Real-time analysis, visualization, and alerting on client load time metrics provided by Boomerang.

- A comprehensive view of perceived load times provided by correlating client metrics from Boomerang with network health metrics and web server processing times.

- Measurement of bandwidth being used by all web pages to assist IT in capacity planning.

- Tracking of the impact of website changes both pre- and post-deployment to improve response times and avoid service disruptions or latencies.

- The industry’s simplest deployment model via application delivery controllers which create no added management overhead or performance impact on web servers.

“Web application performance problems are frustrating at best, while severe problems can damage the brand and negatively impact revenue,” said Jesse Rothstein, CEO, ExtraHop. “With client-side JavaScript and Navigation Timing APIs, the problem of measuring end-user experience has been solved, but large challenges remain around making sense of the data. With ExtraHop’s new RUM bundle, IT teams can easily visualize and correlate end-user experience to performance across the network, servers, databases, message queues, and other components of the application delivery chain.”

The ExtraHop RUM bundle is available to both Enterprise Edition and Discovery Edition customers at no additional charge and with no usage limits.

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ExtraHop Delivers Real-User Monitoring

ExtraHop announced the ExtraHop Real-User Monitoring (RUM) bundle.

The ExtraHop RUM bundle is free to all ExtraHop users, even those using the ExtraHop free-forever Discovery Edition.

“ExtraHop’s approach to user experience management (UEM) is innovative, integrated, and natively extensible in value,” said Dennis Drogseth, vice president, Enterprise Management Associates. “It combines valuable insights into user experience regarding browser, web page, and web page components, with real-time perspectives on network and systems latencies. As such, it’s both a natural and highly-efficient addition to ExtraHop’s broader analytic directions.”

The ExtraHop RUM bundle correlates data delivered by Boomerang with all ExtraHop wire data analysis metrics to show an end-to-end view of the client and all application, network and infrastructure components involved in a web application.

With the RUM bundle, the ExtraHop platform allows IT to measure users’ perceived page-load time against 3,000+ back-end performance metrics such as server processing time and network latency to generate a complete picture of the user’s experience and the infrastructure that delivers it. Web developers have a view of the performance contribution of every object served from any page. In turn, business stakeholders are equipped with the insight they need to understand user experience by web page, browser type, mobile, laptop, and desktop platform to take proactive steps prioritizing development and improving audience experience to keep users engaged.

Other key benefits and capabilities of the ExtraHop RUM bundle include the following:

- Real-time analysis, visualization, and alerting on client load time metrics provided by Boomerang.

- A comprehensive view of perceived load times provided by correlating client metrics from Boomerang with network health metrics and web server processing times.

- Measurement of bandwidth being used by all web pages to assist IT in capacity planning.

- Tracking of the impact of website changes both pre- and post-deployment to improve response times and avoid service disruptions or latencies.

- The industry’s simplest deployment model via application delivery controllers which create no added management overhead or performance impact on web servers.

“Web application performance problems are frustrating at best, while severe problems can damage the brand and negatively impact revenue,” said Jesse Rothstein, CEO, ExtraHop. “With client-side JavaScript and Navigation Timing APIs, the problem of measuring end-user experience has been solved, but large challenges remain around making sense of the data. With ExtraHop’s new RUM bundle, IT teams can easily visualize and correlate end-user experience to performance across the network, servers, databases, message queues, and other components of the application delivery chain.”

The ExtraHop RUM bundle is available to both Enterprise Edition and Discovery Edition customers at no additional charge and with no usage limits.

The Latest

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.