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2022 App Stability Report: Driving Quality with Visibility

Michael Olechna
Guardsquare

Users today expect a seamless, uninterrupted experience when interacting with their web and mobile apps. Their expectations have continued to grow in tandem with their appetite for new features and consistent updates. Mobile apps have responded by increasing their release cadence by up to 40%, releasing a new full version of their app every 4-5 days, as determined in this year's SmartBear State of Software Quality | Application Stability Index report. When examining last year's report, mobile apps were on average issuing a new release once a week, about once every seven days. To accommodate the market's new standard of faster releases, a growing number of mobile apps are adopting progressive delivery practices, like feature flags and experiments, to accelerate the release of new features while minimizing the risk of releasing new errors to their user base that would impact the stability of their applications. Stability score measures the percentage of app sessions that are crash-free, providing visibility into app health as well as user experience. It can be thought of as a barometer of quality and quantity: the lower the number of errors in your app, the higher your stability score is and the quality of your app. Overall, there is a continuing trend of increasing stability among web and mobile apps with the industry striving for five nines or 99.999% stability. In last year's report, mobile apps had a median stability score of 99.80%. In the 2020 report, the last direct comparison of web and mobile app stability score, mobile apps outscored web apps by a significant margin, 99.63% to 99.39%. Perhaps the most surprising finding of this year's report is the revelation web apps had a higher stability score, 99.94%, than their mobile counterparts score of 99.88%. Diving deeper into the data provides some insight into why web app scores were much higher than in 2020 and against this year's mobile median score. The top two industries by stability score in the report were Media and Entertainment, 99.97% and e-commerce, 99.94%. Media and Entertainment had a strong web app presence, especially with the takeoff of streaming media in the past year. As many newcomers attempt to grow their users, it remains essential for them to provide an optimal, uninterrupted experience. Meanwhile, to retain their massive subscriber base against increased competition, streaming giants seek to strike a balance between delivering a seamless experience and consistently offering new features to enhance their application — across a range of devices. On the other hand, perhaps no better example of the link between stability and revenue can be thought of than e-commerce applications. The last moment any organization wants their app to crash is during the checkout process. As worldwide e-commerce revenue expects to climb past $5.5 trillion in 2022, one can assume there is a lot of money in customers' carts when they arrive at checkout. Giving customers a smooth experience is paramount, as crashes directly impact revenue. These two industries provide a model that the lowest scoring industries in the report can learn from. As in previous reports, Gaming was the lowest scoring industry at 99.60%, with the widest range of score distribution between apps. Health and Wellness did not fare much better, scoring the second-lowest at 99.71%. The low stability score of Health and Wellness combined with its median release cadence of every other day and the widest release distribution of all industries demonstrates a balance must be reached between roadmap agility and app stability. With the user experience becoming increasingly dominant to app success, app stability has evolved into application observability as the need for visibility into software releases has grown. Perhaps most importantly, we're learning that visibility into app stability is key for innovating quickly and delivering apps with speed and confidence.

Michael Olechna is Product Marketing Manager at Guardsquare

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.

2022 App Stability Report: Driving Quality with Visibility

Michael Olechna
Guardsquare

Users today expect a seamless, uninterrupted experience when interacting with their web and mobile apps. Their expectations have continued to grow in tandem with their appetite for new features and consistent updates. Mobile apps have responded by increasing their release cadence by up to 40%, releasing a new full version of their app every 4-5 days, as determined in this year's SmartBear State of Software Quality | Application Stability Index report. When examining last year's report, mobile apps were on average issuing a new release once a week, about once every seven days. To accommodate the market's new standard of faster releases, a growing number of mobile apps are adopting progressive delivery practices, like feature flags and experiments, to accelerate the release of new features while minimizing the risk of releasing new errors to their user base that would impact the stability of their applications. Stability score measures the percentage of app sessions that are crash-free, providing visibility into app health as well as user experience. It can be thought of as a barometer of quality and quantity: the lower the number of errors in your app, the higher your stability score is and the quality of your app. Overall, there is a continuing trend of increasing stability among web and mobile apps with the industry striving for five nines or 99.999% stability. In last year's report, mobile apps had a median stability score of 99.80%. In the 2020 report, the last direct comparison of web and mobile app stability score, mobile apps outscored web apps by a significant margin, 99.63% to 99.39%. Perhaps the most surprising finding of this year's report is the revelation web apps had a higher stability score, 99.94%, than their mobile counterparts score of 99.88%. Diving deeper into the data provides some insight into why web app scores were much higher than in 2020 and against this year's mobile median score. The top two industries by stability score in the report were Media and Entertainment, 99.97% and e-commerce, 99.94%. Media and Entertainment had a strong web app presence, especially with the takeoff of streaming media in the past year. As many newcomers attempt to grow their users, it remains essential for them to provide an optimal, uninterrupted experience. Meanwhile, to retain their massive subscriber base against increased competition, streaming giants seek to strike a balance between delivering a seamless experience and consistently offering new features to enhance their application — across a range of devices. On the other hand, perhaps no better example of the link between stability and revenue can be thought of than e-commerce applications. The last moment any organization wants their app to crash is during the checkout process. As worldwide e-commerce revenue expects to climb past $5.5 trillion in 2022, one can assume there is a lot of money in customers' carts when they arrive at checkout. Giving customers a smooth experience is paramount, as crashes directly impact revenue. These two industries provide a model that the lowest scoring industries in the report can learn from. As in previous reports, Gaming was the lowest scoring industry at 99.60%, with the widest range of score distribution between apps. Health and Wellness did not fare much better, scoring the second-lowest at 99.71%. The low stability score of Health and Wellness combined with its median release cadence of every other day and the widest release distribution of all industries demonstrates a balance must be reached between roadmap agility and app stability. With the user experience becoming increasingly dominant to app success, app stability has evolved into application observability as the need for visibility into software releases has grown. Perhaps most importantly, we're learning that visibility into app stability is key for innovating quickly and delivering apps with speed and confidence.

Michael Olechna is Product Marketing Manager at Guardsquare

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.