AI expert for integrating, configuring, and getting the most from Firebase Crashlytics in iOS and Android apps, including custom keys, non-fatal logging, and alert setup.
Firebase Crashlytics is the most widely used mobile crash reporting platform, but many teams integrate it at a surface level and miss the features that make crash data truly actionable. This AI assistant helps mobile developers implement Crashlytics deeply and correctly, configure it for maximum diagnostic value, and interpret the data it produces.
The assistant covers the complete Crashlytics integration journey. For new integrations, it walks through the SDK setup for both Android (Gradle plugin and dependency configuration) and iOS (SPM or CocoaPods setup, dSYM upload configuration), ensuring the crash reporter is initialized correctly and that dSYM or mapping files are uploaded automatically as part of the build pipeline. It addresses common setup mistakes like missing the Crashlytics Gradle plugin application or incorrect GoogleService-Info.plist placement that result in crashes being reported without symbolication.
Beyond basic setup, the assistant specializes in advanced Crashlytics instrumentation. It helps teams implement custom keys to attach relevant app state to crash reports—user ID, feature flags, last completed action—so that every crash report arrives with the context needed to reproduce it. It covers the correct use of log() for breadcrumb-style event logging before a crash, the distinction between recordException() for non-fatal error tracking and letting fatal crashes propagate naturally, and how to structure custom attributes for effective filtering in the Crashlytics dashboard.
The assistant also helps with crash alert configuration in the Firebase Console, setting up velocity alerts for sudden crash rate spikes, and integrating Crashlytics with PagerDuty or Slack for real-time notification. It addresses cross-platform scenarios including Flutter and React Native Crashlytics SDK configurations.
Ideal users include mobile developers adding Crashlytics to a new project, teams upgrading from legacy Fabric Crashlytics to the Firebase SDK, and engineering leads designing crash monitoring strategies that balance signal quality with alert fatigue.
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