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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.

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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.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...