Monitor your Flutter app and see every issue!
summary
Shows how to capture uncaught non‑crashing exceptions and full distributed traces using Sentry, instrumenting Flutter with a navigator observer, Sentry HTTP client and manual spans for GPS lock, and a Dart Frog backend with middleware for context propagation via W3 Trace Context. Uses a configurable sample rate (debug 1.0, production often 1–2%) to avoid millions of traces. The implemented pipeline joins client and server spans, exposes a large idle gap between HTTP and DB spans, and pinpoints where performance fixes are needed.
AI-written summary · about
chapters (7)
- 0:00Flutter app monitoring intro
- 1:08Catching non-crashing exceptions
- 7:42Exceptions and performance instrumentation
- 12:57Error monitoring services
- 14:07Distributed performance tracing
- 17:05Implementing tracing in Flutter/backend
- 21:35Analyzing performance bottlenecks
related talks
02mDebug and profile your app with Flutter DevTools
12mWatching a Flutter app crash
40mThread by Thread: The Hidden Battle for Flutter Stability
29mMeasure the Performance of your Android App with Sentry
49mDemystifying performance tune up in Flutter and Dart
36mObservation-based product development using Flutter 1
13mMonitoring your Flutter app's stability with Firebase Crashlytics
41mCrash-Proof Flutter: Building Apps That Refuse to Die