New Relic APM Integration for iOS and Android Apps

We integrate New Relic APM into mobile apps on iOS and Android. This system shows not just crashes but also UI slowness, slow network requests, and conversion drops. You get a single trace from button tap to SQL query — without additional correlation. The newrelic header (W3C TraceContext) is propagated automatically. In New Relic One, you can open an HTTP request from the app and drill into the server trace. We've completed 30+ integrations for projects with an audience from 50,000 DAU. We guarantee monitoring stability and correct sampling.

Why Distributed Tracing Is Mandatory for Mobile Monitoring

Without Distributed Tracing, you only see the client side. If a request fails with a 500 error on the backend, you won't know the reason. With tracing enabled, each HTTP call gets a unique identifier. The mobile agent adds traceparent and tracestate headers. The server-side New Relic agent picks them up and forms a single trace. You see timing for each segment: network call, SQL, cache. New Relic documentation recommends enabling Distributed Tracing for all applications with microservice architecture.

How to Install the New Relic Agent on iOS and Android

iOS via Swift Package Manager:

// Package.swift
.package(url: "https://github.com/newrelic/newrelic-ios-agent-spm", from: "7.4.0")
// AppDelegate.application(_:didFinishLaunchingWithOptions:)
import NewRelic
NewRelic.start(withApplicationToken: "AA-XXXXXXXX-XXXX")

Android via Gradle:

// build.gradle (project level)
classpath("com.newrelic.agent.android:agent-gradle-plugin:7.+")
// build.gradle (app level)
apply plugin: 'newrelic'
implementation("com.newrelic.agent.android:android-agent:7.+")
// Application.onCreate()
NewRelic.withApplicationToken("AA-XXXXXXXX-XXXX")
        .withLoggingEnabled(false)
        .start(applicationContext)

After installation, the agent automatically instruments HTTP calls: iOS intercepts URLSession through swizzling, Android through bytecode instrumentation of OkHttp and HttpURLConnection. If you use custom networking layers (NWConnection, custom URLProtocol), verify that tracking works explicitly.

How to Verify Auto-Instrumentation

Immediately after launch, open the Distributed traces tab in New Relic One. If requests appear with correct durations and statuses, the integration is set correctly. Otherwise, check that the agent is initialized before the first network request.

What Is Distributed Tracing and How to Enable It

Distributed Tracing is enabled by default only for Infinite Tracing. For standard sampling, add:

NewRelic.enableFeatures([.NRFeatureFlag_DistributedTracing])

On Android, no similar flag is required — tracing works after activation in New Relic settings. The TraceContext header is automatically propagated to backend requests, where the New Relic APM agent picks it up and forms a single trace.

How Custom Events Improve Business Metrics

Custom events allow tracking of business funnels. For example, record a CheckoutCompleted event with attributes order_id, total, payment_method.

// iOS
NewRelic.recordCustomEvent("CheckoutCompleted",
    attributes: ["order_id": orderId, "total": total, "payment_method": method])

// Android
NewRelic.recordCustomEvent("CheckoutCompleted",
    mapOf("order_id" to orderId, "total" to total))

These events flow into NRQL — a powerful SQL-like language. We build dashboards with time series, FACET by payment methods, and calculate funnel conversion.

Error and Crash Tracking

Crashes are collected automatically. Handled exceptions are recorded explicitly:

// iOS
do {
    try performPayment()
} catch {
    NewRelic.recordError(error, attributes: ["context": "checkout"])
}

// Android
NewRelic.recordError(exception, mapOf("context" to "checkout"))

Crash reports include Thread State of all threads, ANR events, and Breadcrumb Trail — a sequence of actions leading to the crash.

Why New Relic Is Better Than Firebase Crashlytics for Business Metrics

New Relic allows you to set an alert on crash-free rate dropping below 99.5% or correlate network error rate with a business metric. Firebase doesn't offer that.

How We Configure NRQL Alerts

Typical alerts we set up:

NewRelic.withApplicationToken("AA-XXXXXXXX-XXXX")
    .withLoggingEnabled(true)
    .withCrashReporting(true)
    .withHttpResponseBodyCaptureEnabled(true)
    .start(applicationContext)

How We Implement New Relic

1. Analyze the current application — identify key scenarios, network requests, business events.
2. Install the agent on iOS and Android, verify HTTP auto-instrumentation.
3. Configure Distributed Tracing with the backend agent, verify traces.
4. Create custom events for the business funnel — registration, view, purchase.
5. Configure NRQL alerts with notifications to Slack/PagerDuty.
6. Deliver documentation — dashboards, alerts, instructions for further improvements.

What's Included in the Work

• Agent installation iOS/Android (including React Native via @newrelic/react-native-agent)
• Verification of HTTP auto-instrumentation
• Distributed Tracing setup
• Custom events for business funnel
• NRQL alerts
• Documentation for dashboards and alerts
• Team training on New Relic One
• 2 weeks post-release support

Timeline

Basic integration with auto-instrumentation: 1–2 days. Custom events and dashboards: +1 day. Cost is determined individually for your project.

Get a consultation on New Relic integration for your mobile app — contact us to discuss details. Order monitoring setup today.

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.