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Delivering Deep Insights Into End User Quality of Experience

The quality of an end user's experience of an application is becoming an ever more important consideration in the APM world. It's not enough to draw a conclusion about the end user's experience based on an evaluation of how an individual application is performing. Increasingly, multiple applications and loosely coupled infrastructure components are coming together to contribute to the end user's experience. Understanding how all those applications and components are interacting at the point where the user is engaging them is crucial to an understanding of the user's experience.

So where do you start to gain this understanding? First, you must identify what constitutes a user's experience of an application: Response speed? Ease of information access? Depth of integration with other applications? Until you understand what constitutes a user's experience, you're not in a position to measure or quantify it.

Some of the elements that contribute to an end user's experience of an application will be inside the corporate firewall — servers, routers, database machines, and more.

Other elements contributing to the end user's experience will be outside the corporate firewall — data feeds from third parties, for example.

Organizations that want to know how well their applications are performing for users — particularly customers who are interacting from outside the firewall — need tools to monitor the user's experience that look at it from both the inside and the outside.

Monitoring Application Response Times For Each Transaction

Today's application infrastructures involve many servers, routers, switches, load balancers, and more. In any given application, information moves among these different devices. To understand fully what is happening every time the data moves among application or network elements, you need tools that can track and capture transaction information in real time and at a very granular level.

You also need to monitor for patterns in user engagement. Response times for an online booking application, for example, may be consistent all week long, then spike suddenly on a Friday night when everyone leaves work for the weekend. The user experience of your applications on a Friday night may be poor, given the traffic that your systems are experiencing.

Without insight into the response times for each movement between application and infrastructure elements, though, you won't know where to make changes to improve the end user experience.

Monitoring Business Metrics Related to Application Performance

While the ability to monitor all the different aspects of the application and infrastructure that contribute to end user experience is critical, you also need a context in which the data you capture from that monitoring effort has relevance. You need to develop business metrics that identify desired transaction performance levels.

Without both the metrics and the ability to track transaction performance against those metrics, you have information without any context — and it is impossible know where or how to refine a user's experience without that context.

Monitoring the Impact on End User Experience Across Infrastructure Tiers

Increasingly, today's applications are built from loosely coupled components that can exist in many different places and in many different infrastructure tiers — even within a single organization. Tracing root causes of end user experience problems is more complicated now, given the different infrastructure tiers in place.

In order to improve that end user experience, you need tools that can provide a comprehensive view of all those infrastructure elements — and show you how data and messages are moving between those elements.

Generating Synthetic Transactions For Measuring End User Performance

Finally, the ability to monitor the end user experience and trace root causes of problems across different transactions and infrastructure elements is crucial when an end user calls to report a problem. With these tools, you can find and fix a problem quickly.

However, it would be better to monitor the system proactively, finding end user experience problems before the end users report them. If you are able to do that, you could eliminate a large number of poor experiences before users even encounter them.

Passive monitoring tools can provide insights into the end user experience from outside the firewall. They can monitor the transactions, the transitions from page to page in a web application, and how much time it takes before the user can move on to a next step while waiting for a transaction to complete.

Active monitoring tools, in contrast, can create synthetic transactions that you can use to understand end user experience without the end user's involvement. They enable you to get a jump on end user experience management, because you can find and fix problems before the users do.

Ultimately, when you're looking at APM, you need to pay particular attention to the tools that enable you to monitor and manage the experience of the end user. The traditional APM tools are powerful tools for managing traditional applications, but as newer applications veer away from the traditional development and deployment models, you need tools that can focus on the end user experience, in order to understand how best to use the APM tools to modify the application delivery environment.

Create the right user experience, and you will keep more customers. They will be engaged with the experience you have created — and that, ultimately, is the best measure of application performance.

About Raj Sabhlok and Suvish Viswanathan

Raj Sabhlok is the President of ManageEngine. Suvish Viswanathan is an APM Research Analyst at ManageEngine. ​ ManageEngine is a division of Zoho Corp. and makers of a globally renowned suite of cost-effective network, systems, security, and applications management software solutions.

Related Links:

www.manageengine.com

Click to read "Another Look at Gartner's 5 Dimensions of APM" by Raj Sabhlok and Suvish Viswanathan

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Delivering Deep Insights Into End User Quality of Experience

The quality of an end user's experience of an application is becoming an ever more important consideration in the APM world. It's not enough to draw a conclusion about the end user's experience based on an evaluation of how an individual application is performing. Increasingly, multiple applications and loosely coupled infrastructure components are coming together to contribute to the end user's experience. Understanding how all those applications and components are interacting at the point where the user is engaging them is crucial to an understanding of the user's experience.

So where do you start to gain this understanding? First, you must identify what constitutes a user's experience of an application: Response speed? Ease of information access? Depth of integration with other applications? Until you understand what constitutes a user's experience, you're not in a position to measure or quantify it.

Some of the elements that contribute to an end user's experience of an application will be inside the corporate firewall — servers, routers, database machines, and more.

Other elements contributing to the end user's experience will be outside the corporate firewall — data feeds from third parties, for example.

Organizations that want to know how well their applications are performing for users — particularly customers who are interacting from outside the firewall — need tools to monitor the user's experience that look at it from both the inside and the outside.

Monitoring Application Response Times For Each Transaction

Today's application infrastructures involve many servers, routers, switches, load balancers, and more. In any given application, information moves among these different devices. To understand fully what is happening every time the data moves among application or network elements, you need tools that can track and capture transaction information in real time and at a very granular level.

You also need to monitor for patterns in user engagement. Response times for an online booking application, for example, may be consistent all week long, then spike suddenly on a Friday night when everyone leaves work for the weekend. The user experience of your applications on a Friday night may be poor, given the traffic that your systems are experiencing.

Without insight into the response times for each movement between application and infrastructure elements, though, you won't know where to make changes to improve the end user experience.

Monitoring Business Metrics Related to Application Performance

While the ability to monitor all the different aspects of the application and infrastructure that contribute to end user experience is critical, you also need a context in which the data you capture from that monitoring effort has relevance. You need to develop business metrics that identify desired transaction performance levels.

Without both the metrics and the ability to track transaction performance against those metrics, you have information without any context — and it is impossible know where or how to refine a user's experience without that context.

Monitoring the Impact on End User Experience Across Infrastructure Tiers

Increasingly, today's applications are built from loosely coupled components that can exist in many different places and in many different infrastructure tiers — even within a single organization. Tracing root causes of end user experience problems is more complicated now, given the different infrastructure tiers in place.

In order to improve that end user experience, you need tools that can provide a comprehensive view of all those infrastructure elements — and show you how data and messages are moving between those elements.

Generating Synthetic Transactions For Measuring End User Performance

Finally, the ability to monitor the end user experience and trace root causes of problems across different transactions and infrastructure elements is crucial when an end user calls to report a problem. With these tools, you can find and fix a problem quickly.

However, it would be better to monitor the system proactively, finding end user experience problems before the end users report them. If you are able to do that, you could eliminate a large number of poor experiences before users even encounter them.

Passive monitoring tools can provide insights into the end user experience from outside the firewall. They can monitor the transactions, the transitions from page to page in a web application, and how much time it takes before the user can move on to a next step while waiting for a transaction to complete.

Active monitoring tools, in contrast, can create synthetic transactions that you can use to understand end user experience without the end user's involvement. They enable you to get a jump on end user experience management, because you can find and fix problems before the users do.

Ultimately, when you're looking at APM, you need to pay particular attention to the tools that enable you to monitor and manage the experience of the end user. The traditional APM tools are powerful tools for managing traditional applications, but as newer applications veer away from the traditional development and deployment models, you need tools that can focus on the end user experience, in order to understand how best to use the APM tools to modify the application delivery environment.

Create the right user experience, and you will keep more customers. They will be engaged with the experience you have created — and that, ultimately, is the best measure of application performance.

About Raj Sabhlok and Suvish Viswanathan

Raj Sabhlok is the President of ManageEngine. Suvish Viswanathan is an APM Research Analyst at ManageEngine. ​ ManageEngine is a division of Zoho Corp. and makers of a globally renowned suite of cost-effective network, systems, security, and applications management software solutions.

Related Links:

www.manageengine.com

Click to read "Another Look at Gartner's 5 Dimensions of APM" by Raj Sabhlok and Suvish Viswanathan

The Latest

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...

In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ... 

Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...