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The Importance of Real and Synthetic End User Monitoring

Dennis Rietvink

Organizations have many ways of ensuring that their systems are functioning properly. One of the most important things to measure, when assessing the performance of a system, is the end user experience.

Can users access the system quickly? Do they experience errors while accessing the system? Can they easily interact with the system across all the available channels? For the IT department, the answers to these questions determine whether or not the system is functioning properly. For the organization, they reveal the most important thing – whether or not their customers are happy, and are likely to continue using their services.

There are two ways to monitor user transactions and interactions with your website:

Real User Monitoring

This method uses a passive monitoring system, documenting all actions of users as they interact with your website. The feedback, generated in real time, is automatically assessed against established benchmarks, to correctly measure the quality of delivered services.

Real user monitoring systems have many advantages – you get to know exactly how visitors to your website experience all its features and applications, and how the website is performing for your end users in various geographic locations. The biggest problem with this method is that you won’t know about any website issues until at least one user gets to experience an existing problem.

Synthetic User Monitoring

This method simulates user experience on your website. It works by scripting typical user actions, and then simulates user click at regular intervals, to ensure that your website is responsive.

This method enables you to proactively catch any existing problems before your end users get to experience slow or unresponsive applications, or encounter other errors.

The obvious downside is that this method requires you to spend time scripting typical user actions. In addition, if your website changes frequently, you’ll need to periodically update your scripted scenarios.

In addition to websites, synthetic transactions can be used to monitor databases and TCP ports.

Organizations need a solution that can help recognize potential system problems by categorizing and visually presenting information concerning end user behavior and website performance in real time. In addition, such solution should also offer a way to script common user transactions and monitor the system’s performance 24x7.

End user monitoring reflects end user health, but doesn’t tell you the root cause of a problem. Linking end user monitoring data with application and infrastructure monitoring data enables organizations to determine the impact of a problem, rank its priority and quickly navigate to the root cause.

Dennis Rietvink is Co-Founder and VP of Product Management at Savision

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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 Importance of Real and Synthetic End User Monitoring

Dennis Rietvink

Organizations have many ways of ensuring that their systems are functioning properly. One of the most important things to measure, when assessing the performance of a system, is the end user experience.

Can users access the system quickly? Do they experience errors while accessing the system? Can they easily interact with the system across all the available channels? For the IT department, the answers to these questions determine whether or not the system is functioning properly. For the organization, they reveal the most important thing – whether or not their customers are happy, and are likely to continue using their services.

There are two ways to monitor user transactions and interactions with your website:

Real User Monitoring

This method uses a passive monitoring system, documenting all actions of users as they interact with your website. The feedback, generated in real time, is automatically assessed against established benchmarks, to correctly measure the quality of delivered services.

Real user monitoring systems have many advantages – you get to know exactly how visitors to your website experience all its features and applications, and how the website is performing for your end users in various geographic locations. The biggest problem with this method is that you won’t know about any website issues until at least one user gets to experience an existing problem.

Synthetic User Monitoring

This method simulates user experience on your website. It works by scripting typical user actions, and then simulates user click at regular intervals, to ensure that your website is responsive.

This method enables you to proactively catch any existing problems before your end users get to experience slow or unresponsive applications, or encounter other errors.

The obvious downside is that this method requires you to spend time scripting typical user actions. In addition, if your website changes frequently, you’ll need to periodically update your scripted scenarios.

In addition to websites, synthetic transactions can be used to monitor databases and TCP ports.

Organizations need a solution that can help recognize potential system problems by categorizing and visually presenting information concerning end user behavior and website performance in real time. In addition, such solution should also offer a way to script common user transactions and monitor the system’s performance 24x7.

End user monitoring reflects end user health, but doesn’t tell you the root cause of a problem. Linking end user monitoring data with application and infrastructure monitoring data enables organizations to determine the impact of a problem, rank its priority and quickly navigate to the root cause.

Dennis Rietvink is Co-Founder and VP of Product Management at Savision

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 ...