Skip to main content

The User is King

Seeing What Matters Through End User Experience Management
Trevor Matz

Growing mobile device diversity and management was high on the list of Gartner’s 10 top strategic technology trends for 2014. Gartner predicts that by 2018 BYOD users will double, or even triple, the size of the mobile workforce.

Gartner’s prediction describes the new reality of IT management: the User is King. End users want to work in the most efficient way — whether they are sitting at their desktops, accessing a virtualized application from their personal laptop, or using their mobile devices. In order to maximize user productivity, forward-looking enterprises need to embrace this reality and adopt a monitoring strategy that supports all of the application types, devices and delivery methods accessed by their users.

IT operations understand they are facing a potential conundrum. As Pete Goldin, APMdigest's Editor-in-Chief observed, "Progressive IT departments understand that success is about serving the business goals of the company, and, from an IT point of view, that revolves around the End User Experience." However, at the same time, the growth of virtualization, of third-party cloud applications, and of mobile devices have all diminished visibility into End Users' experiences.

To meet this challenge effectively, IT operations must shift from a data center-centric to a user-centric computing model, and undergo a similar shift in how they measure performance and productivity. Meeting service level agreements on corporate server and network performance is no longer enough.

The popularity of Application Performance Management (APM) has shined a light on only one sub-component of End User Experience Management (EUEM), obscuring the fact that EUEM is a separate, multi-dimensional solution. EUEM encompasses the three primary components that dynamically interact to impact how End Users experience IT services:

- Application performance

- Physical, virtual and mobile device performance

- User productivity

With EUEM, enterprises are able to directly correlate the impact of IT on user productivity as they can see exactly what all of their end users are experiencing. This ability to see from the end user's "point of view" is especially critical as IT is tasked with monitoring, managing, and troubleshooting performance issues across the entire enterprise application portfolio, all of its device types and all of the delivery methods accessed by their users.

Companies who successfully pivot their "point of view" will readily monitor, validate and manage user experience no matter the application, the device or the user in order to:

- Automate monitoring performance

- Enhance service levels

- Promote business agility

- Optimize end user productivity

"EUEM is more than just monitoring application response times from the user's perspective," says David Williams, VP of Strategy in the Office of the CTO at BMC. "It is about understanding how IT consumers work, and empowering them to work smarter and faster."

In today’s reality of proliferating virtualized and cloud services, mobile device diversity and BYOD, the need for enterprises to see as their users see is more urgent than ever.

Trevor Matz is President and CEO of Aternity Inc.

Related Links:

Gartner Top 10 Strategic Technology Trends for 2013: Big Data, Cloud, Analytics and Mobile

Trevor Matz, President and CEO of Aternity, Joins the Vendor Forum

The Latest

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

The User is King

Seeing What Matters Through End User Experience Management
Trevor Matz

Growing mobile device diversity and management was high on the list of Gartner’s 10 top strategic technology trends for 2014. Gartner predicts that by 2018 BYOD users will double, or even triple, the size of the mobile workforce.

Gartner’s prediction describes the new reality of IT management: the User is King. End users want to work in the most efficient way — whether they are sitting at their desktops, accessing a virtualized application from their personal laptop, or using their mobile devices. In order to maximize user productivity, forward-looking enterprises need to embrace this reality and adopt a monitoring strategy that supports all of the application types, devices and delivery methods accessed by their users.

IT operations understand they are facing a potential conundrum. As Pete Goldin, APMdigest's Editor-in-Chief observed, "Progressive IT departments understand that success is about serving the business goals of the company, and, from an IT point of view, that revolves around the End User Experience." However, at the same time, the growth of virtualization, of third-party cloud applications, and of mobile devices have all diminished visibility into End Users' experiences.

To meet this challenge effectively, IT operations must shift from a data center-centric to a user-centric computing model, and undergo a similar shift in how they measure performance and productivity. Meeting service level agreements on corporate server and network performance is no longer enough.

The popularity of Application Performance Management (APM) has shined a light on only one sub-component of End User Experience Management (EUEM), obscuring the fact that EUEM is a separate, multi-dimensional solution. EUEM encompasses the three primary components that dynamically interact to impact how End Users experience IT services:

- Application performance

- Physical, virtual and mobile device performance

- User productivity

With EUEM, enterprises are able to directly correlate the impact of IT on user productivity as they can see exactly what all of their end users are experiencing. This ability to see from the end user's "point of view" is especially critical as IT is tasked with monitoring, managing, and troubleshooting performance issues across the entire enterprise application portfolio, all of its device types and all of the delivery methods accessed by their users.

Companies who successfully pivot their "point of view" will readily monitor, validate and manage user experience no matter the application, the device or the user in order to:

- Automate monitoring performance

- Enhance service levels

- Promote business agility

- Optimize end user productivity

"EUEM is more than just monitoring application response times from the user's perspective," says David Williams, VP of Strategy in the Office of the CTO at BMC. "It is about understanding how IT consumers work, and empowering them to work smarter and faster."

In today’s reality of proliferating virtualized and cloud services, mobile device diversity and BYOD, the need for enterprises to see as their users see is more urgent than ever.

Trevor Matz is President and CEO of Aternity Inc.

Related Links:

Gartner Top 10 Strategic Technology Trends for 2013: Big Data, Cloud, Analytics and Mobile

Trevor Matz, President and CEO of Aternity, Joins the Vendor Forum

The Latest

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...