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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

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...