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Android WebView Caused a Google App Crash: How to Avoid a Similar Outage

James Smith
SmartBear

On March 22, Android users around the globe suddenly saw notifications pop up on their devices saying that apps had stopped running. Critical apps such as Gmail, Google Pay, Amazon, Yahoo and certain banking apps couldn't be opened, creating widespread consumer concerns. Later, Google revealed the cause was a bug residing in the Android System WebView. Some users were able to remediate this issue by manually uninstalling the latest update and waiting for Google to release a fix. While the issue was resolved by relying on affected consumers to manually update, major crashes and painful manual workarounds can leave a lasting negative impression for users and the brand's reputation.

Software bugs are inevitable in code, so engineering teams don't realistically need to aim for 100% error-free software. However, they should have pre-production quality assurance measures in place that act as a safety net for situations like this. These tools provide comprehensive error diagnostics and actionable insights that allow software engineers to prioritize the bugs creating the most damaging user experience. Even giants like Google and Facebook still experience lapses in this process, but it is a critical step in delivering consistent, quality software.


Post-Mortem Evaluation: Breaking Down App Stability Data from the Crash

At the start of the Android app outage, Bugsnag data illustrating app stability showed four times the volume of regular Android errors registered within one day, indicating significant impact across the Android user base. The Webview bug caused approximately 75% of the crashes in the leading Android projects monitored. These projects saw around 40 times more crashes compared to the same period in the previous week. On top of that, the worst-affected projects saw 200 times the number of crashes compared to the same period in the previous week.

Additionally, an estimated 2 million users were impacted across all apps that were monitored. There was also a detected drop in overall application stability by at least 2% in Android applications, with the worst-affected projects seeing a 10% decrease in app stability scores, meaning 1 in 10 Android customers were experiencing a crash.

It's also worth noting that this Android WebView error was caused by a Native Development Kit error (NDK), which can only be detected if your crash reporting supports NDK crash detection, and if it is enabled. App stability monitoring is critical in situations like this, because certain systems don't make you opt-in for NDK monitoring like you do with others. Make sure NDK error detection is available by default.

Best Practices To Protect Your Apps from Similar Outages

Given that it was an operating system component at fault in this scenario, there is not a lot development teams could have done to prevent applications from crashing in this situation. However, there are many other types of serious app outages that can be prevented by implementing best practices and defensive programming. Below are some proactive steps engineering teams can take to protect their applications from similar problems that may impact application stability:

1. Monitor for Stability Issues in Production

This is critical for engineering teams to gain immediate visibility into crashes and spikes in errors. Not only can engineering react quickly to fix issues, but it supports impact analysis which can be used to provide clear guidance to support and customer success teams to handle customer communications with confidence. Configure team notifications and incident management integrations to quickly align the team and deal with business-critical issues.

2. Track Application Freezes

This will give the team visibility into if certain features are the root cause of any ANRs (Application Not Responding) being captured. You can track application freezes by using the stack trace to see if the line of code that was running when the application froze and set off the ANR. Stack trace information identifies where in the program the error occurs so that it can be fixed.

3. A/B Test New Features

This will help teams understand how certain features are impacting application stability before releasing them to production. You should also always phase the rollouts and test features with a small group of users before releasing to your entire user base.

The Key Takeaway

Because consumers rely heavily on mobile apps to navigate day-to-day life, application stability is absolutely critical, especially in today's relentlessly competitive environment. Difficult-to-prevent system errors like the Android Systems Webview crash highlight the importance of minimizing preventable errors with defensive programming and better handling of malformed data.

The silver lining of outages like this is that it draws attention to the dire need for good software design and process. It surfaces where software engineering teams need to introduce new best practices or where to to fine-tune existing ones.

James Smith is SVP of the Bugsnag Product Group at SmartBear

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Android WebView Caused a Google App Crash: How to Avoid a Similar Outage

James Smith
SmartBear

On March 22, Android users around the globe suddenly saw notifications pop up on their devices saying that apps had stopped running. Critical apps such as Gmail, Google Pay, Amazon, Yahoo and certain banking apps couldn't be opened, creating widespread consumer concerns. Later, Google revealed the cause was a bug residing in the Android System WebView. Some users were able to remediate this issue by manually uninstalling the latest update and waiting for Google to release a fix. While the issue was resolved by relying on affected consumers to manually update, major crashes and painful manual workarounds can leave a lasting negative impression for users and the brand's reputation.

Software bugs are inevitable in code, so engineering teams don't realistically need to aim for 100% error-free software. However, they should have pre-production quality assurance measures in place that act as a safety net for situations like this. These tools provide comprehensive error diagnostics and actionable insights that allow software engineers to prioritize the bugs creating the most damaging user experience. Even giants like Google and Facebook still experience lapses in this process, but it is a critical step in delivering consistent, quality software.


Post-Mortem Evaluation: Breaking Down App Stability Data from the Crash

At the start of the Android app outage, Bugsnag data illustrating app stability showed four times the volume of regular Android errors registered within one day, indicating significant impact across the Android user base. The Webview bug caused approximately 75% of the crashes in the leading Android projects monitored. These projects saw around 40 times more crashes compared to the same period in the previous week. On top of that, the worst-affected projects saw 200 times the number of crashes compared to the same period in the previous week.

Additionally, an estimated 2 million users were impacted across all apps that were monitored. There was also a detected drop in overall application stability by at least 2% in Android applications, with the worst-affected projects seeing a 10% decrease in app stability scores, meaning 1 in 10 Android customers were experiencing a crash.

It's also worth noting that this Android WebView error was caused by a Native Development Kit error (NDK), which can only be detected if your crash reporting supports NDK crash detection, and if it is enabled. App stability monitoring is critical in situations like this, because certain systems don't make you opt-in for NDK monitoring like you do with others. Make sure NDK error detection is available by default.

Best Practices To Protect Your Apps from Similar Outages

Given that it was an operating system component at fault in this scenario, there is not a lot development teams could have done to prevent applications from crashing in this situation. However, there are many other types of serious app outages that can be prevented by implementing best practices and defensive programming. Below are some proactive steps engineering teams can take to protect their applications from similar problems that may impact application stability:

1. Monitor for Stability Issues in Production

This is critical for engineering teams to gain immediate visibility into crashes and spikes in errors. Not only can engineering react quickly to fix issues, but it supports impact analysis which can be used to provide clear guidance to support and customer success teams to handle customer communications with confidence. Configure team notifications and incident management integrations to quickly align the team and deal with business-critical issues.

2. Track Application Freezes

This will give the team visibility into if certain features are the root cause of any ANRs (Application Not Responding) being captured. You can track application freezes by using the stack trace to see if the line of code that was running when the application froze and set off the ANR. Stack trace information identifies where in the program the error occurs so that it can be fixed.

3. A/B Test New Features

This will help teams understand how certain features are impacting application stability before releasing them to production. You should also always phase the rollouts and test features with a small group of users before releasing to your entire user base.

The Key Takeaway

Because consumers rely heavily on mobile apps to navigate day-to-day life, application stability is absolutely critical, especially in today's relentlessly competitive environment. Difficult-to-prevent system errors like the Android Systems Webview crash highlight the importance of minimizing preventable errors with defensive programming and better handling of malformed data.

The silver lining of outages like this is that it draws attention to the dire need for good software design and process. It surfaces where software engineering teams need to introduce new best practices or where to to fine-tune existing ones.

James Smith is SVP of the Bugsnag Product Group at SmartBear

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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 ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...