5 Principles to Guide Your Mobile Monitoring Decisions

Amir Rozenberg

Mobile is explosive in nature. It has been shown more than once that across verticals, it’s very expensive to be naïve as to the expected user adoption when it comes to mobile applications. You quickly come to realize you need to understand the behavior of the application in production.

Mobile monitoring is materially different from web monitoring, mainly due to the nature of the highly capable thick client. At the same time, the trends repeat: in the same way web monitoring quickly evolved to adopt the end user perspective through specific browsers and browser versions, also here, mobile monitoring is irrelevant if you’re not opting to adopt the end user perspective.

With that in mind, there are more than a few choices when coming to select your mobile monitoring solution. Here are some principles you want to keep in mind as you decide about your initial foray into this space.

1. Real Devices Matter

Adopt your end user perspective. This is a very simple, core principle. Browser emulation is equivalent to network monitoring. Imagine one user with iPhone 4S, and 10 applications running in the background. Another user with iPhone 6 and no applications running in the background. Will the server respond to both at the same time? Of course. Will the customer experience be the same? Absolutely not.

Further, commonly it’s not even possible to record and replay the calls from the device to the backend correctly. You almost need to recreate the application in your script, not to mention complex encryption that is usually applied to the backend calls. Long story short, if you’re not using what your users are seeing, you’re blind. It’s as simple as that.

2. Real devices drive triage

Are your existing tools able to provide you sufficient data about what happens on the application? With so much happening inside the thick client, you may want to understand the CPU and memory consumption when things go south. You will want to contrast this data across different devices, versions of the application, geographies and carriers. You will also want to have access to clean data that’s devoid of as much noise from the crowd, because it’s important for you to get to the root cause fast. We’ll come to it a bit later, but also your ability to extract UI elements will help you understand better what happened.

3. Know early

Probably the one thing you really want to avoid is seeing your brand showing in the media with the word "outage" next to it. The key is to know early there’s an issue and eliminate it quickly. To know early means that you can’t wait on your users to tell you: you need to proactively exercise the application and complete delivery chain frequently through the key user scenarios that are important. You want to setup and fine tune alerts that give you the information you need to be aware and act quickly.

4. Independence is key

If you made it this far down the article, you’re serious about finding a solution, and you need to show impact quickly. Going to the IT organization and asking them to install an agent inside the firewall to report metrics? Going to the developer and convincing them to embed a 3rd party SDK into the application? Maybe not the best strategy to achieve the desired outcome quickly. In fact, it’s commonly known that SDKs embedded into the application need to be looked at closely in terms of user privacy, application security and hit on the application performance. So much so that only 21% of developers integrate such SDKs into their application, according to Forrester.

The solution to gain insight into the end user experience quickly is via a SaaS solution that’s based on real devices and provides end-user perspective ongoing monitoring of the mobile application.

5. Continuous Integration schemas mandate insight ahead of launch

It’s no secret the mobile ecosystem is leading the "Shift-Left" paradigm change. With 2-week release cycles, there is no room for error, nor is there room for finding a performance issue just before going to production. Many organizations are breaking ground by monitoring the next release of the application based on the nightly build. This is a good measure to ensure there are no surprises on the launch of a new version of the application, perhaps even on new devices, such as iPhone 6, or new OS such as iOS8.

The practice of mobile monitoring is evolving the way people are used to think about monitoring. There are new users with challenging expectations, new people involved in monitoring (such as DevOps) and new tools. It’s important to pick the right tool to achieve insight into the application in production before your users share their frustration with friends and the media.

Amir Rozenberg is Director of Product Management for Perfecto Mobile.

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5 Principles to Guide Your Mobile Monitoring Decisions

Amir Rozenberg

Mobile is explosive in nature. It has been shown more than once that across verticals, it’s very expensive to be naïve as to the expected user adoption when it comes to mobile applications. You quickly come to realize you need to understand the behavior of the application in production.

Mobile monitoring is materially different from web monitoring, mainly due to the nature of the highly capable thick client. At the same time, the trends repeat: in the same way web monitoring quickly evolved to adopt the end user perspective through specific browsers and browser versions, also here, mobile monitoring is irrelevant if you’re not opting to adopt the end user perspective.

With that in mind, there are more than a few choices when coming to select your mobile monitoring solution. Here are some principles you want to keep in mind as you decide about your initial foray into this space.

1. Real Devices Matter

Adopt your end user perspective. This is a very simple, core principle. Browser emulation is equivalent to network monitoring. Imagine one user with iPhone 4S, and 10 applications running in the background. Another user with iPhone 6 and no applications running in the background. Will the server respond to both at the same time? Of course. Will the customer experience be the same? Absolutely not.

Further, commonly it’s not even possible to record and replay the calls from the device to the backend correctly. You almost need to recreate the application in your script, not to mention complex encryption that is usually applied to the backend calls. Long story short, if you’re not using what your users are seeing, you’re blind. It’s as simple as that.

2. Real devices drive triage

Are your existing tools able to provide you sufficient data about what happens on the application? With so much happening inside the thick client, you may want to understand the CPU and memory consumption when things go south. You will want to contrast this data across different devices, versions of the application, geographies and carriers. You will also want to have access to clean data that’s devoid of as much noise from the crowd, because it’s important for you to get to the root cause fast. We’ll come to it a bit later, but also your ability to extract UI elements will help you understand better what happened.

3. Know early

Probably the one thing you really want to avoid is seeing your brand showing in the media with the word "outage" next to it. The key is to know early there’s an issue and eliminate it quickly. To know early means that you can’t wait on your users to tell you: you need to proactively exercise the application and complete delivery chain frequently through the key user scenarios that are important. You want to setup and fine tune alerts that give you the information you need to be aware and act quickly.

4. Independence is key

If you made it this far down the article, you’re serious about finding a solution, and you need to show impact quickly. Going to the IT organization and asking them to install an agent inside the firewall to report metrics? Going to the developer and convincing them to embed a 3rd party SDK into the application? Maybe not the best strategy to achieve the desired outcome quickly. In fact, it’s commonly known that SDKs embedded into the application need to be looked at closely in terms of user privacy, application security and hit on the application performance. So much so that only 21% of developers integrate such SDKs into their application, according to Forrester.

The solution to gain insight into the end user experience quickly is via a SaaS solution that’s based on real devices and provides end-user perspective ongoing monitoring of the mobile application.

5. Continuous Integration schemas mandate insight ahead of launch

It’s no secret the mobile ecosystem is leading the "Shift-Left" paradigm change. With 2-week release cycles, there is no room for error, nor is there room for finding a performance issue just before going to production. Many organizations are breaking ground by monitoring the next release of the application based on the nightly build. This is a good measure to ensure there are no surprises on the launch of a new version of the application, perhaps even on new devices, such as iPhone 6, or new OS such as iOS8.

The practice of mobile monitoring is evolving the way people are used to think about monitoring. There are new users with challenging expectations, new people involved in monitoring (such as DevOps) and new tools. It’s important to pick the right tool to achieve insight into the application in production before your users share their frustration with friends and the media.

Amir Rozenberg is Director of Product Management for Perfecto Mobile.

Related Links

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Related Vendors

The Latest

The Performance Bottleneck in Enterprise AI Has Been Exposed – Now We Must Fix It

Performance bottlenecks aren't uncommon when it comes to rolling out new technology, regardless of how capable or game-changing that technology might be. Every generation of new tech has encountered roadblocks that had to be overcome before it was truly able to shine. Virtualization forced organizations to rethink resource allocation, cloud transformation had us shift our focus toward scalability and elasticity, and microservices introduced entirely new challenges around observability and distributed systems. There's something different about AI, however ...

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Consider a single order represented across order-management, execution, and settlement systems. Each database, message broker, and application may be online and processing its own records correctly. Yet the workflow has failed if related events arrive on different clocks, rely on inconsistent state, or cannot be reconciled before an operational decision must be made ...

Why AI in IT Is Producing High Productivity but Heavy Workloads

AI now exists in almost every IT workflow. In a recent survey of more than 800 IT service professionals, all respondents indicated the use of AI in some form within their organization. But there's a growing paradox: if dashboards are clearing faster and alerts are resolved at unprecedented speed, why aren't IT service desks reporting lighter workloads? The research found that 71% of IT teams said their actual workload has remained flat or increased since adopting AI. This reality appears to contradict what we’ve been told about AI ...

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Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

The Incident Load Is Rising, but Recovery Times Aren't Moving

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

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If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

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Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

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Agentic Operations Begin with Governed Middleware Access

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...