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

James Smith
SmartBear
Learn more about 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
Learn more about 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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When AI Becomes the Corporate OS

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

The $600 Billion Wake Up Call

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Breaking Down Agentic AI Fragmentation and Complexity with Governance

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

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As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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