Sentry Integration for Mobile App Error Tracking

Imagine you release a mobile app update, and within an hour crash reports show a 200% error spike. You open Firebase Crashlytics and see the stack trace, but have no idea what the user was doing. Sentry solves this by collecting not only stack traces but also breadcrumbs, performance data, and user context. Our team, with over 5 years of production experience, ensures a stable turnkey integration. Basic setup takes 0.5 to 1 day; full performance tracing takes 1 to 2 days. The investment pays off after the first release: average debugging time drops by 40%, and crash rates can decrease by 90%.

Why Choose Sentry?

Sentry goes beyond crash reporting by including performance monitoring: transactions, spans, slow HTTP requests, and ANR detection. For apps that need a smooth UI, this provides a fuller picture. According to Sentry documentation, breadcrumbs reconstruct the user's action sequence, cutting diagnosis time by half compared to raw stack traces.

Sentry wins in scenarios where you need not just to log crashes but to investigate their root cause: breadcrumbs show the user's path, and performance tracing uncovers slow requests.

How We Implement Sentry

We connect Sentry to your specific platform, following best practices. Example configuration for iOS (SwiftPM):

// AppDelegate.swift or @main
import Sentry

SentrySDK.start { options in
    options.dsn = "https://[email protected]/project"
    options.environment = Bundle.main.object(forInfoDictionaryKey: "SentryEnvironment") as? String ?? "production"
    options.tracesSampleRate = 0.2 // 20% of transactions for performance
    options.profilesSampleRate = 0.1
    options.attachViewHierarchy = true // UI snapshot on crash
}

SentrySDK.configureScope { scope in
    scope.setUser(SentryUser(userId: userId))
    scope.setTag(value: "premium", key: "subscription")
    scope.addBreadcrumb({
        let crumb = Breadcrumb()
        crumb.message = "Cart screen opened"
        crumb.category = "navigation"
        return crumb
    }())
}

For Android (Gradle + Application):

// build.gradle (module)
implementation("io.sentry:sentry-android:7.+")

// Application.onCreate()
SentryAndroid.init(this) { options ->
    options.dsn = "https://[email protected]/project"
    options.environment = BuildConfig.SENTRY_ENVIRONMENT
    options.tracesSampleRate = 0.2
    options.isEnableUserInteractionTracing = true // auto trace taps
}

// add breadcrumbs
Sentry.configureScope { scope ->
    scope.setUser(SentryUser(id = userId))
    scope.setTag("subscription", "premium")
    scope.addBreadcrumb(Breadcrumb().apply {
        message = "Cart screen opened"
        category = "navigation"
    })
}

We also add manual transactions for performance monitoring:

let transaction = SentrySDK.startTransaction(name: "checkout", operation: "ui.action")
let span = transaction.startChild(operation: "http.client", description: "POST /orders")
// ... perform request ...
span.finish()
transaction.finish()

What to Know About Sample Rate?

Sample rate determines what percentage of sessions send performance traces. For production, we recommend 0.2 (20%) to avoid hitting quotas. Setting it to 1.0 can lead to extra costs. We help you find the optimal value for your audience.

Step-by-Step Integration Guide

1. Create a project in Sentry and obtain the DSN.
2. Add SDK via SPM/CocoaPods/Gradle/Maven.
3. Configure environments (dev/staging/production) via environment variables.
4. Set up performance tracing with a chosen sample rate (recommend 0.2 for production).
5. Add breadcrumbs at key points (navigation, network requests).
6. Set up upload of dSYM/ProGuard mapping/JS source maps in CI/CD.
7. Create alerts based on error rate and p95 latency.

How to Set Up Alerts and Dashboards?

After integration, configure alerts to respond in time. Sentry allows rules based on:

• Error rate – e.g., >10 crashes per hour per version.
• p95 latency – if p95 exceeds 2 seconds.
• New errors – first-time crash seen.

Dashboards show heatmaps of slow requests, performance percentiles, and error trends. We tailor these to your business metrics.

Common Problems When Setting Up Sentry

• High sample rate: Setting it to 1.0 will send 100% of transactions, potentially exceeding quota. Stick to 0.2 for production.
• Missing source maps: React Native stack traces become useless. Always set up upload in CI.
• Ignoring environments: All errors land in production, making filtering impossible.
• No user context: Without tags and breadcrumbs, investigating errors is difficult.

Performance Comparison: Sentry vs Crashlytics

In our measurements, Sentry adds roughly 2-5% to app launch time with proper setup. Crashlytics adds about 1-3%. But Sentry provides much richer data for analysis.

What's Included in the Work

• Connecting sentry-cocoa / sentry-android / sentry-react-native
• Setting up environments (dev, staging, production)
• Configuring performance tracing with optimal sample rate
• Integrating scope: User ID, tags, breadcrumbs
• Setting up alerts by error rate and p95 latency
• Uploading dSYM / ProGuard mapping / JS source maps in CI
• Documentation and team training

Process for Integration

1. Analysis: Review your app and choose the best configuration.
2. Design: Plan scope, tags, and breadcrumbs matching your business logic.
3. Implementation: Integrate SDK, configure environments, add code.
4. Testing: Simulate errors, verify dashboards.
5. Deployment: Set up symbol upload in CI, document setup.

Timeline and Pricing

Basic crash reporting setup takes 0.5 to 1 day. Full performance tracing with custom transactions and alerts takes 1 to 2 days. Cost is calculated individually based on app complexity. We've completed over 30 successful integrations for apps with up to 10 million users. On average, the investment pays back within 2 months by reducing debugging time.

Contact us to discuss the details of integrating Sentry. Get a consultation and preliminary estimate within one day. Order Sentry integration and cut your error-search time.

Mobile App Analytics: Firebase, Amplitude, AppsFlyer and Attribution

Our team regularly encounters projects where analytics is already "set up" but yields no real insights. A typical example is a startup with 50k DAU: tracking dozens of events without a single answer to the question "why don't users reach payment?". In two weeks we built a basic funnel and found that 70% of users drop off at the phone number verification screen. After fixing the bug, retention increased by 12%. The takeaway: analytics should start with specific questions, not tracking everything indiscriminately.

Why Event Taxonomy is the Foundation of Mobile App Analytics?

Firebase Analytics, Amplitude, Mixpanel — technically similar. The difference lies in what you put into them. A common mistake: events like screen_view, button_tap_1, button_tap_2 without context. A month later, no one remembers what button_tap_2 means.

Proper taxonomy: object + action + context. product_viewed, checkout_started, payment_completed with parameters product_id, category, price, source. This allows building funnels, cohort analysis, and retention without additional tracking.

We document the naming convention in a tracking plan — a document (Google Sheet or Amplitude Data Catalog) describing every event, its parameters, and triggering conditions. The tracking plan is synced with the analytics team before development begins, not after. This approach ensures that data remains interpretable months later and doesn't become a dump. Experience from 50+ projects confirms: without a tracking plan, analytics maintenance costs increase 2-3 times due to rework.

What Should You Choose for Mobile App Analytics: Firebase, Amplitude, or Mixpanel?

The table below highlights key differences between the three popular platforms. Choice depends on budget, traffic, and tasks.

Firebase Analytics — free, deep integration with Google Ads, BigQuery export for raw data. Limitations: data latency up to 24 hours, limited funnels. For startups with Google Ads traffic, it's the first choice.

Amplitude — product analytics focused on cohorts and user journeys. Journeys (formerly Pathfinder) shows actual paths between events — not assumed funnels but real routes. Session Replay records sessions for UX analysis. The free tier up to 10M events/month is enough for most products at launch.

Mixpanel — close to Amplitude, stronger in real-time segmentation. Insights, Funnels, Retention cover 90% of product analysts' tasks.

How to Solve Multi-Channel Attribution with AppsFlyer?

Knowing where a user came from is a separate task. Firebase Attribution works only within the Google ecosystem. For multi-channel attribution (Facebook Ads, TikTok, Apple Search Ads, programmatic), an MMP (Mobile Measurement Partner) is needed.

AppsFlyer is the market leader. OneLink — universal deep link working on iOS and Android, correctly attributing installs from any channel. Protect360 — built-in fraud protection (fake installs, click injection on Android). Adjust and Branch are competitors with similar features. Branch excels in deep linking; Adjust is popular in gaming.

According to Apple, with iOS 14.5, apps must obtain user permission via ATT before collecting IDFA for tracking. AppsFlyer uses probabilistic matching (IP + user agent + timing) for these users — accuracy is lower but better than nothing. SKAdNetwork and Privacy Preserving Attribution provide aggregated data from Apple with a 24-72 hour delay.

How to Set Up Crash Analytics to Not Miss Bugs?

Firebase Crashlytics is the standard for crash reporting. It automatically groups crashes by stack trace, shows affected users %, and sends velocity alerts when crash rate increases by more than 10% per hour.

Important: symbolication. On iOS, .dSYM files must be automatically uploaded with each build — via Fastlane upload_symbols_to_crashlytics or Xcode Cloud built-in. Without symbols, crashes in Crashlytics appear as memory addresses. This happens more often than expected when switching to a new CI — in one project with 500k users, we found that 40% of crashes remained unsymbolicated due to a missing CI/CD step. After automation, bug response time dropped from 3 hours to 15 minutes.

For React Native and Flutter, @sentry/react-native and sentry_flutter provide additional context: breadcrumbs, network requests before the crash, Redux/Provider state.

Below is a comparison of popular crash analytics tools to choose according to your needs.

Environment Setup

Three environments with separate Firebase projects: dev, staging, production. Mixing analytics from test sessions and production is a common mistake that skews all metrics. On iOS via GoogleService-Info.plist per scheme, on Android via google-services.json in each flavor folder.

Timelines: basic analytics with Firebase + Crashlytics — 3-5 days. Full tracking plan + Amplitude/Mixpanel with funnels and cohorts — 2-3 weeks. Attribution via AppsFlyer with deep linking and fraud protection — 1-2 weeks. Cost is calculated individually based on integration complexity.

What Is Included in Our Work

As part of analytics implementation, we provide:

• Development and approval of a tracking plan with product and marketing teams.
• SDK integration (Firebase, Amplitude, Mixpanel, AppsFlyer) considering your stack (Swift/Kotlin/Flutter/React Native).
• Setup of funnels, cohorts, dashboards, and alerts.
• Automation of symbolication and .dSYM upload via Fastlane.
• Documentation of events and parameters.
• Team training on the analytics platform.
• Two weeks of post-release support and tracking adjustments.

Our experience: 7 years of analytics implementation and over 80 successful projects in mobile development. We guarantee data correctness and transparency at every stage.

Contact us for a consultation on setting up analytics for your app. Request an audit of your current analytics — and we will show you which metrics you are losing.