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The End-User is Always Right

Bruce Kosbab

The phrase "The customer is always right" is ubiquitous in the business and retail world and one that companies should extend as a matter of course to refer to their employees. For IT teams, they are usually known as the "end user". It is a company’s employees who keep it running and when a network problem gets in the way not only is the end-user frustrated and annoyed, but productivity can quickly be driven to a halt.

One of the biggest challenges network managers face when liaising with the end-user is that user’s lack of understanding of the problem. To a user, their application is not working properly. So they call the Helpdesk. "Just get the technology to work, the sooner the better", the user requests (or demands). They probably have no idea just how complicated that fix might be, and no idea whether the problem is with the application or the network. However complex the problem may be, the end-user expects it to be fixed (relatively) quickly so they can continue with their job and the business can operate smoothly.

AANPM – the End-User Pacifier

If the problem affects multiple users, then the business begins to have a serious problem. If there’s a slowdown or shutdown of the network, or any kind of problem involving the applications running on it, the impact on the business can be huge and costly.

According to a recent Globalscape study, downtime can cost as much as $1 million per hour after accounting for all of the consequences of being offline for a period, and 76 percent of survey respondents referred to end user frustration.

The perfect solution clearly is to fix a problem before this stage. To do this, the network and application teams need complete visibility from the network through to the application to enable them to quickly identify root cause. AANPM (Application-Aware Network Performance Management) can do this by enabling teams to monitor all levels of the user experience and address issues before they become serious. It also provides continuous monitoring to support analysis of trends in the network and applications’ performance.

As AANPM provides end-to-end visibility of the entire IT infrastructure, a single-dashboard view covering both critical applications and the underlying network infrastructure problem-solving is made much faster. It enables engineers to identify problems with a key application and right away use that cross-platform visibility of AANPM to track down the root cause.

And what does this mean? A happy end-user.

Bruce Kosbab is CTO of Fluke Networks.

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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 End-User is Always Right

Bruce Kosbab

The phrase "The customer is always right" is ubiquitous in the business and retail world and one that companies should extend as a matter of course to refer to their employees. For IT teams, they are usually known as the "end user". It is a company’s employees who keep it running and when a network problem gets in the way not only is the end-user frustrated and annoyed, but productivity can quickly be driven to a halt.

One of the biggest challenges network managers face when liaising with the end-user is that user’s lack of understanding of the problem. To a user, their application is not working properly. So they call the Helpdesk. "Just get the technology to work, the sooner the better", the user requests (or demands). They probably have no idea just how complicated that fix might be, and no idea whether the problem is with the application or the network. However complex the problem may be, the end-user expects it to be fixed (relatively) quickly so they can continue with their job and the business can operate smoothly.

AANPM – the End-User Pacifier

If the problem affects multiple users, then the business begins to have a serious problem. If there’s a slowdown or shutdown of the network, or any kind of problem involving the applications running on it, the impact on the business can be huge and costly.

According to a recent Globalscape study, downtime can cost as much as $1 million per hour after accounting for all of the consequences of being offline for a period, and 76 percent of survey respondents referred to end user frustration.

The perfect solution clearly is to fix a problem before this stage. To do this, the network and application teams need complete visibility from the network through to the application to enable them to quickly identify root cause. AANPM (Application-Aware Network Performance Management) can do this by enabling teams to monitor all levels of the user experience and address issues before they become serious. It also provides continuous monitoring to support analysis of trends in the network and applications’ performance.

As AANPM provides end-to-end visibility of the entire IT infrastructure, a single-dashboard view covering both critical applications and the underlying network infrastructure problem-solving is made much faster. It enables engineers to identify problems with a key application and right away use that cross-platform visibility of AANPM to track down the root cause.

And what does this mean? A happy end-user.

Bruce Kosbab is CTO of Fluke Networks.

Hot Topics

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 ...