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Nastel Announces AutoPilot Insight Real-User Monitoring

Nastel Technologies announced the addition of real-user monitoring and analytics to its flagship AutoPilot Insight software platform.

According to Charley Rich, Nastel’s VP-Product Management, “Slow Web apps are a terrific way to kill revenues, harm reputations and drive users to competitors. The problem is, even as traditional datacenter performance metrics say everything is fine, users are tapping their fingers with impatience because of sub-standard app responsiveness.

“AutoPilot’s new capabilities handle exactly this kind of situation, and can automatically pinpoint the source of problems that hurt a company’s reputation with its client base,” he said. “Basically, we capture and analyze two very different sets of data: the subjective user experience of fast or sluggish app responsiveness, and back-end server activities. Our secret sauce is being able to stitch together both data sets, analyze it, and deliver actionable insights to correct performance issues whenever and wherever they occur.

“The key to making real-user monitoring easy to deploy,” Rich continued, “is the use of browser-injection technology. So in addition to the detailed web and server metrics one would expect, our software enables clients to track end-user activities across geo-locations, and it automatically understands and visually depicts the relationship between application topologies and end-user requests.”

The ability to synthesize insights derived from topology mapping, server behaviors, and user requests—along with presenting probable root causes of problems in an intuitive visual manner—translates to reduced mean-time-to-repair (MTTR) of software issues and lower overall cost of support.

Whether a problem’s root cause is a JavaScript error on the client, network latency, or a slow Java method, AutoPilot Insight’s interface takes specialists to underlying problem issues with the press of a button. Detailed drill-down capabilities are provided in addition to single-click root-cause analysis.

AutoPilot Insight also stands apart from other solutions by offering natural language query capability that enables IT specialists to “talk” to data, enabling the detection of subtle, hidden patterns that enable solution of the toughest, most intractable performance problems.

Available key metrics include a full breakdown of page requests into all its components, browser-specific issues, geo-locations, top requests, worst response times, slowest loading pages, slowest server connections and much more.

“AutoPilot Insight,” Rich concludes, “is a unified solution that analyzes user requests, logs, metrics and transactions spanning the browser, web apps, middleware, brokers and mainframes. With this end-to-end measurement of performance you will rest easy that your users are satisfied and your company’s reputation is secure.”

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Nastel Announces AutoPilot Insight Real-User Monitoring

Nastel Technologies announced the addition of real-user monitoring and analytics to its flagship AutoPilot Insight software platform.

According to Charley Rich, Nastel’s VP-Product Management, “Slow Web apps are a terrific way to kill revenues, harm reputations and drive users to competitors. The problem is, even as traditional datacenter performance metrics say everything is fine, users are tapping their fingers with impatience because of sub-standard app responsiveness.

“AutoPilot’s new capabilities handle exactly this kind of situation, and can automatically pinpoint the source of problems that hurt a company’s reputation with its client base,” he said. “Basically, we capture and analyze two very different sets of data: the subjective user experience of fast or sluggish app responsiveness, and back-end server activities. Our secret sauce is being able to stitch together both data sets, analyze it, and deliver actionable insights to correct performance issues whenever and wherever they occur.

“The key to making real-user monitoring easy to deploy,” Rich continued, “is the use of browser-injection technology. So in addition to the detailed web and server metrics one would expect, our software enables clients to track end-user activities across geo-locations, and it automatically understands and visually depicts the relationship between application topologies and end-user requests.”

The ability to synthesize insights derived from topology mapping, server behaviors, and user requests—along with presenting probable root causes of problems in an intuitive visual manner—translates to reduced mean-time-to-repair (MTTR) of software issues and lower overall cost of support.

Whether a problem’s root cause is a JavaScript error on the client, network latency, or a slow Java method, AutoPilot Insight’s interface takes specialists to underlying problem issues with the press of a button. Detailed drill-down capabilities are provided in addition to single-click root-cause analysis.

AutoPilot Insight also stands apart from other solutions by offering natural language query capability that enables IT specialists to “talk” to data, enabling the detection of subtle, hidden patterns that enable solution of the toughest, most intractable performance problems.

Available key metrics include a full breakdown of page requests into all its components, browser-specific issues, geo-locations, top requests, worst response times, slowest loading pages, slowest server connections and much more.

“AutoPilot Insight,” Rich concludes, “is a unified solution that analyzes user requests, logs, metrics and transactions spanning the browser, web apps, middleware, brokers and mainframes. With this end-to-end measurement of performance you will rest easy that your users are satisfied and your company’s reputation is secure.”

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Technology leaders across the federal landscape are facing, and will continue to face, an uphill battle when it comes to fortifying their digital environments against hostile and persistent threat actors. On one hand, they are being asked to push digital transformation ... On the other hand, they are facing the fiscal uncertainty of continuing resolutions (CR) and government shutdowns looming near and far. In the face of these challenges, CIOs, CTOs, and CISOs must figure out how to modernize legacy systems and infrastructure while doing more with less and still defending against external and internal threats ...

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

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 ...

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