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The Power of the Pivot

A look into the benefits of combining user experience monitoring with application side analysis
Denis Goodwin

The ability to view things from the end user perspective and to drill down into the code level deep dive can be extremely powerful, and the information gathered from this ability provides DevOps teams with an instant view into the direct root cause of any user experience problem they may not otherwise have noticed.

Traditional real-user monitoring (RUM) techniques provide insight into how your user actually interacts with your website or application. Synthetic monitoring, particularly when using real browsers, provides a similar assessment of expected user experience along with the benefits of true availability monitoring, third-party impact, and consistent baselining capabilities.

Combining synthetic and RUM gives a complete view of the user experience along with high level root cause clues. RUM, by itself, can miss outages, page errors, and third-party problems. Synthetic, by itself, is really only a proxy for real-user experience and can miss problems experienced by various user populations. Using both techniques in tandem eliminates those inherent blind spots and can provide an organization with the best view of their users’ experience – both actual and potential.


But monitoring user experience only tells you half of the story. The ability to look at things from the application/back-end perspective and drill down to the code (or up to end-user transactions) is a powerful root cause identifier. By discovering problems in delivery, DevOps teams can work to prevent or minimize user impact on their software.

Application and server monitoring provide insight into relative transaction performance. Furthermore, it provides an accurate view into the root cause of user experience degradation in your own infrastructure. These tools allow developers to identify issues before code is deployed while simultaneously giving ops teams the tools to address issues and communicate to app owners in real time. Providing this flexible view of user experience and application health provides a clear view of impact and root cause, allowing dev and ops to work together prevent and minimize damaging negative user experiences. Having all of this working together at the same time will do wonders for your overall relationship with your end user.

The ability to pivot the perspective from user experience to application transaction performance can give your organization a powerful view into user experience and root cause diagnostics. Put another way, it helps to answer the “what” along with (possibly more importantly) the “why” when it comes to performance issues. When these perspectives are seamlessly tied together and are easily available to a variety of technical and business users, the result can only be APM awesomeness!

Denis Goodwin is Director of Product Management for APM at SmartBear.

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The Power of the Pivot

A look into the benefits of combining user experience monitoring with application side analysis
Denis Goodwin

The ability to view things from the end user perspective and to drill down into the code level deep dive can be extremely powerful, and the information gathered from this ability provides DevOps teams with an instant view into the direct root cause of any user experience problem they may not otherwise have noticed.

Traditional real-user monitoring (RUM) techniques provide insight into how your user actually interacts with your website or application. Synthetic monitoring, particularly when using real browsers, provides a similar assessment of expected user experience along with the benefits of true availability monitoring, third-party impact, and consistent baselining capabilities.

Combining synthetic and RUM gives a complete view of the user experience along with high level root cause clues. RUM, by itself, can miss outages, page errors, and third-party problems. Synthetic, by itself, is really only a proxy for real-user experience and can miss problems experienced by various user populations. Using both techniques in tandem eliminates those inherent blind spots and can provide an organization with the best view of their users’ experience – both actual and potential.


But monitoring user experience only tells you half of the story. The ability to look at things from the application/back-end perspective and drill down to the code (or up to end-user transactions) is a powerful root cause identifier. By discovering problems in delivery, DevOps teams can work to prevent or minimize user impact on their software.

Application and server monitoring provide insight into relative transaction performance. Furthermore, it provides an accurate view into the root cause of user experience degradation in your own infrastructure. These tools allow developers to identify issues before code is deployed while simultaneously giving ops teams the tools to address issues and communicate to app owners in real time. Providing this flexible view of user experience and application health provides a clear view of impact and root cause, allowing dev and ops to work together prevent and minimize damaging negative user experiences. Having all of this working together at the same time will do wonders for your overall relationship with your end user.

The ability to pivot the perspective from user experience to application transaction performance can give your organization a powerful view into user experience and root cause diagnostics. Put another way, it helps to answer the “what” along with (possibly more importantly) the “why” when it comes to performance issues. When these perspectives are seamlessly tied together and are easily available to a variety of technical and business users, the result can only be APM awesomeness!

Denis Goodwin is Director of Product Management for APM at SmartBear.

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For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

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 ...