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18 Ways to Ensure Mobile App Performance - Part 1

Mobile apps are serious business. Every year mobile apps are becoming more critical to the way consumers buy, organizations do business, and the world communicates.

Earlier this year Flurry released a report on mobile app usage stating: "In the six years that Flurry has been reporting on our mobile app usage, and in some cases addiction, we’ve seen stunning growth. This last year was no different. According to Flurry Analytics, in 2014 overall app usage grew by 76%. In this context, Flurry defines app usage as a user opening an app and recording what we call a session. In 2014, Shopping, Utilities & Productivity, and Messaging experienced triple-digit growth and were the key drivers. As our mobile devices become more and more a part of our everyday lives, we are increasingly using them for always-on shopping, working, and communication. Where years past have seen massive growth in games and entertainment, 2014 was the year apps got down to serious business."

If mobile apps are becoming vital to business, then mobile app performance is key – from development through production.

"If you're not designing your apps with mobile users in mind, you are taking a big risk in terms of attracting and retaining your customers, and gaining their loyalty and commitment to coming back," warns David Jones, APM Evangelist.

With this in mind, APMdigest asked industry experts – from analysts and consultants to the top vendors – to recommend the best ways to ensure mobile app performance. The full list of 18 Ways to Ensure Mobile App Performance will be posted over the next 4 days. With Part 1, we start at the beginning, at the development and testing stages.

1. BIZDEVOPS

The top way to ensure mobile application performance is through application governance, or BizDevOps. Better communication and collaboration between mobile dev, ops and QA teams, working in concert with business teams of application owners and users, allows for better application governance. Teams can determine what capabilities apps should have, and a faster feedback loop allows for changes to be made faster and more continuously. By moving performance management forward in the development cycle, teams can better understand dependencies and operational or quality issues across the entire application delivery chain – before apps are launched into production.
Gabe Lowy
Technology Analyst and Founder of TechTonics Advisors

2. DEVOPS

Highly performing mobile applications invariably share one common trait and that is robust testing in pre-production environments. Instrumenting mobile apps to collect critical business, performance and health data across languages, methodologies and platforms is not easy and requires real collaboration between development and operations. Operations teams must regularly share crash reports with development along with supporting stack traces, activity logs and code-level visibility needed to continually improve the next version of the app.
Aruna Ravichandran
VP Marketing, CA Product and Solutions Marketing, CA Technologies

Mobile performance excellence starts at the onset of an application's lifecycle and involves immediate collaboration and a committed transparency across all functional teams, including Product Management, Development, and IT Operations. As early as app conceptualization, product management should clearly communicate the app's intent, both the acceptable and optimum user experience, and the possible usage and behavioral variances between OS, device and user location. With this understanding, Development and IT Operations will be able monitor and optimize the various applications stack touch points in both the pre-production and production environments well before the app is ever rolled out.
Christopher Reynolds
Director, Product Management – Mobile APM, Aternity

Monitor every aspect of the application and it's infrastructure, from the backend all the way to the application rendering. Make sure that this practice is started from the moment you start building the product so that performance will be on everybody's mind, both Dev and Ops. Make performance a key KPI during development, test the performance in details during functional and/or performance testing and guaranty performance monitoring in production!
Coen Meerbeek
Online Performance Consultant and Founder of Blue Factory Internet

3. PERFORMANCE TESTING

Mobile performance assurance is best assured, following unit and functional testing, by a structured, integrated program of performance testing, at or above anticipated traffic levels. Such testing should combine wide ranging device emulation on an appropriate browser and consistent PC platform across public carrier networks in key global markets, and "real device" originated testing for key mobile devices, as determined, where possible, from web traffic analytics of the live application.
Larry Haig
Senior Consultant, Intechnica

Typically, consumers do not want to install a piece of software to monitor each application. However, an alternative exists – by leveraging synthetic testing to measure end user experience one can see where performance bottlenecks lie. This data helps answer the question: is it the network, the end point the user is going to, or the application itself?
Matt Goldberg
Senior Director of Service Provider Solutions, SevOne

4. NETWORK EMULATION

Delivering good performance of mobile applications is challenging due to the highly variable conditions of the mobile networks themselves. You can be getting sparkling 4G one minute but move a couple of blocks in another direction and it can be a very different experience. Therefore, when developing mobile apps you need to factor into your design and usability testing, the ability to function properly across networks that suffer from restricted bandwidths, high latencies and high data loss. The best way to achieve this is to ensure, at every stage of the development lifecycle, that you app is tested to see how it copes with the very worst conditions you can anticipate and the best way to achieve this is through the use of network emulation technology.
Frank Puranik
Senior Technical Specialist, iTrinegy

You must be obsessively cognizant that your user community is not solely comprised of residents of major cities with stable 4G and LTE signals. High latency, limited bandwidth and connectivity failures are the bane of mobile applications, so your QA methodology should leverage WAN emulation to test against worst-case scenarios. This will quickly reveal chatty and bulky parts of your application, as well as areas sensitive to losses in connectivity. NPM products with modeling capabilities can also be used to capture best-case transactions and virtually introduce complex network effects to predict worst-case performance.
Jon C. Hodgson
Global Consulting Engineer, Riverbed

Read Part 2 of 18 Ways to Ensure Mobile App Performance, with recommendations all about mobile app design.

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 ...

18 Ways to Ensure Mobile App Performance - Part 1

Mobile apps are serious business. Every year mobile apps are becoming more critical to the way consumers buy, organizations do business, and the world communicates.

Earlier this year Flurry released a report on mobile app usage stating: "In the six years that Flurry has been reporting on our mobile app usage, and in some cases addiction, we’ve seen stunning growth. This last year was no different. According to Flurry Analytics, in 2014 overall app usage grew by 76%. In this context, Flurry defines app usage as a user opening an app and recording what we call a session. In 2014, Shopping, Utilities & Productivity, and Messaging experienced triple-digit growth and were the key drivers. As our mobile devices become more and more a part of our everyday lives, we are increasingly using them for always-on shopping, working, and communication. Where years past have seen massive growth in games and entertainment, 2014 was the year apps got down to serious business."

If mobile apps are becoming vital to business, then mobile app performance is key – from development through production.

"If you're not designing your apps with mobile users in mind, you are taking a big risk in terms of attracting and retaining your customers, and gaining their loyalty and commitment to coming back," warns David Jones, APM Evangelist.

With this in mind, APMdigest asked industry experts – from analysts and consultants to the top vendors – to recommend the best ways to ensure mobile app performance. The full list of 18 Ways to Ensure Mobile App Performance will be posted over the next 4 days. With Part 1, we start at the beginning, at the development and testing stages.

1. BIZDEVOPS

The top way to ensure mobile application performance is through application governance, or BizDevOps. Better communication and collaboration between mobile dev, ops and QA teams, working in concert with business teams of application owners and users, allows for better application governance. Teams can determine what capabilities apps should have, and a faster feedback loop allows for changes to be made faster and more continuously. By moving performance management forward in the development cycle, teams can better understand dependencies and operational or quality issues across the entire application delivery chain – before apps are launched into production.
Gabe Lowy
Technology Analyst and Founder of TechTonics Advisors

2. DEVOPS

Highly performing mobile applications invariably share one common trait and that is robust testing in pre-production environments. Instrumenting mobile apps to collect critical business, performance and health data across languages, methodologies and platforms is not easy and requires real collaboration between development and operations. Operations teams must regularly share crash reports with development along with supporting stack traces, activity logs and code-level visibility needed to continually improve the next version of the app.
Aruna Ravichandran
VP Marketing, CA Product and Solutions Marketing, CA Technologies

Mobile performance excellence starts at the onset of an application's lifecycle and involves immediate collaboration and a committed transparency across all functional teams, including Product Management, Development, and IT Operations. As early as app conceptualization, product management should clearly communicate the app's intent, both the acceptable and optimum user experience, and the possible usage and behavioral variances between OS, device and user location. With this understanding, Development and IT Operations will be able monitor and optimize the various applications stack touch points in both the pre-production and production environments well before the app is ever rolled out.
Christopher Reynolds
Director, Product Management – Mobile APM, Aternity

Monitor every aspect of the application and it's infrastructure, from the backend all the way to the application rendering. Make sure that this practice is started from the moment you start building the product so that performance will be on everybody's mind, both Dev and Ops. Make performance a key KPI during development, test the performance in details during functional and/or performance testing and guaranty performance monitoring in production!
Coen Meerbeek
Online Performance Consultant and Founder of Blue Factory Internet

3. PERFORMANCE TESTING

Mobile performance assurance is best assured, following unit and functional testing, by a structured, integrated program of performance testing, at or above anticipated traffic levels. Such testing should combine wide ranging device emulation on an appropriate browser and consistent PC platform across public carrier networks in key global markets, and "real device" originated testing for key mobile devices, as determined, where possible, from web traffic analytics of the live application.
Larry Haig
Senior Consultant, Intechnica

Typically, consumers do not want to install a piece of software to monitor each application. However, an alternative exists – by leveraging synthetic testing to measure end user experience one can see where performance bottlenecks lie. This data helps answer the question: is it the network, the end point the user is going to, or the application itself?
Matt Goldberg
Senior Director of Service Provider Solutions, SevOne

4. NETWORK EMULATION

Delivering good performance of mobile applications is challenging due to the highly variable conditions of the mobile networks themselves. You can be getting sparkling 4G one minute but move a couple of blocks in another direction and it can be a very different experience. Therefore, when developing mobile apps you need to factor into your design and usability testing, the ability to function properly across networks that suffer from restricted bandwidths, high latencies and high data loss. The best way to achieve this is to ensure, at every stage of the development lifecycle, that you app is tested to see how it copes with the very worst conditions you can anticipate and the best way to achieve this is through the use of network emulation technology.
Frank Puranik
Senior Technical Specialist, iTrinegy

You must be obsessively cognizant that your user community is not solely comprised of residents of major cities with stable 4G and LTE signals. High latency, limited bandwidth and connectivity failures are the bane of mobile applications, so your QA methodology should leverage WAN emulation to test against worst-case scenarios. This will quickly reveal chatty and bulky parts of your application, as well as areas sensitive to losses in connectivity. NPM products with modeling capabilities can also be used to capture best-case transactions and virtually introduce complex network effects to predict worst-case performance.
Jon C. Hodgson
Global Consulting Engineer, Riverbed

Read Part 2 of 18 Ways to Ensure Mobile App Performance, with recommendations all about mobile app design.

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 ...