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AppNeta Launches Real User Monitoring for Web Developers

AppNeta launched new Real User Monitoring (RUM) capabilities designed for web development and enhanced application performance.

As a key feature of AppNeta’s TraceView application performance management (APM) solution, the SaaS-delivered RUM functionality brings web developers and operations teams:

- visibility into critical client side latency and errors

- an integrated view of client- and server-side performance data

- proactive alerting to ensure consistent end user performance

As website and application performance become more dependent on activity in the end user browser, it is necessary for web developers and operations teams to see into and understand client-side performance and critical errors. TraceView’s RUM capabilities are designed to provide this enhanced visibility into the client side performance data integrated with full application stack monitoring visibility. The new capabilities enable developers to accurately measure and improve end user latency, providing detailed performance and errors data across pages, browsers, and geography.

“Browser performance is becoming more and more impactful to end user experience,” said Dan Kuebrich, Director of APM Product Management, AppNeta. “The lack of client-side visibility, particularly into errors and latency, is creating enormous challenges for managing performance. TraceView’s new RUM capabilities are designed to arm dev and ops customers with the visibility and data they need to manage the demands of both modern web architectures and end users.”

The new RUM capabilities enhance TraceView’s deep, detailed analysis of performance issues and bottlenecks, extending from the full application stack to the browser and providing critical data for quick problem resolution and improved end user experience. In addition to the client performance and error data, TraceView’s RUM capabilities include tightly integrated client and server data with correlated, actionable information and configurable sample rate for deeper, cross application visibility.

The RUM features will be included in all TraceView technology and additional enhancements will be available in November, 2012.

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AppNeta Launches Real User Monitoring for Web Developers

AppNeta launched new Real User Monitoring (RUM) capabilities designed for web development and enhanced application performance.

As a key feature of AppNeta’s TraceView application performance management (APM) solution, the SaaS-delivered RUM functionality brings web developers and operations teams:

- visibility into critical client side latency and errors

- an integrated view of client- and server-side performance data

- proactive alerting to ensure consistent end user performance

As website and application performance become more dependent on activity in the end user browser, it is necessary for web developers and operations teams to see into and understand client-side performance and critical errors. TraceView’s RUM capabilities are designed to provide this enhanced visibility into the client side performance data integrated with full application stack monitoring visibility. The new capabilities enable developers to accurately measure and improve end user latency, providing detailed performance and errors data across pages, browsers, and geography.

“Browser performance is becoming more and more impactful to end user experience,” said Dan Kuebrich, Director of APM Product Management, AppNeta. “The lack of client-side visibility, particularly into errors and latency, is creating enormous challenges for managing performance. TraceView’s new RUM capabilities are designed to arm dev and ops customers with the visibility and data they need to manage the demands of both modern web architectures and end users.”

The new RUM capabilities enhance TraceView’s deep, detailed analysis of performance issues and bottlenecks, extending from the full application stack to the browser and providing critical data for quick problem resolution and improved end user experience. In addition to the client performance and error data, TraceView’s RUM capabilities include tightly integrated client and server data with correlated, actionable information and configurable sample rate for deeper, cross application visibility.

The RUM features will be included in all TraceView technology and additional enhancements will be available in November, 2012.

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In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

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