Real-Time Blockchain Transaction Monitor with Push Alerts

This mobile blockchain app provides real-time onchain monitoring with crypto push notifications and wallet tracking. Imagine needing instant blockchain transaction monitoring for OTC trades: a large USDT transfer arrives and you must know immediately. Dozens of wallets, hundreds of transactions per day make manual block explorer checks impractical. We build web3 mobile apps that solve this: subscribing to on-chain events via WebSocket, filtering by amount and type, and pushing alerts in 1-2 seconds. Such a system saves hours of manual work and reduces the risk of missing a large trade.

Over the past five years, we have delivered more than 15 projects for DeFi protocols and crypto funds, including a stablecoin monitoring solution with threshold filtering. Each app undergoes load testing at 1000+ notifications per minute and a security audit. The result: stable operation under high load and guaranteed delivery.

How transaction monitoring works

There are four main approaches; the choice depends on speed, load, and complexity requirements.

WebSocket via Infura gives 1-2 second latency — 30x faster than HTTP polling. For a mobile app with push notifications, the third option is optimal: Alchemy Notify → backend webhook → FCM/APNs → phone.

Why transaction filtering is critical

Notifying on every transaction is overwhelming for active addresses (whale wallets do hundreds of transactions per day). Filters are needed for effective crypto tracking:

• Minimum amount (e.g., only notify if > $500)
• Event type (only incoming, or only DEX swap)
• Quiet hours: batch notifications between 23:00–08:00, show a single summary push in the morning

On iOS, customize notifications via UNNotificationContent with UNNotificationServiceExtension — you can enrich push data before displaying. On Android, use NotificationCompat.Builder with InboxStyle for batching. Such filtering significantly saves bandwidth and battery, and reduces server load.

Supported blockchains

Different chains mean different RPCs, address formats, and token standards. This multi-chain app supports both EVM and Solana monitoring. Ethereum and EVM-compatible (Polygon, BSC, Arbitrum, Base) — one adapter with different RPC URL and chain ID. Solana — separate SDK, base58 addresses, tokens via SPL.

Each chain gets its own adapter:

interface ChainMonitor {
    val chainId: Int
    suspend fun subscribeToAddress(address: String, listener: TxEventListener)
    suspend fun unsubscribe(address: String)
    suspend fun getRecentTransactions(address: String, limit: Int): List<Transaction>
}

class EthereumMonitor(private val alchemyWsUrl: String) : ChainMonitor {
    override val chainId = 1
    // ...
}

class SolanaMonitor(private val heliusApiKey: String) : ChainMonitor {
    override val chainId = 101 // Solana mainnet
    // ...
}

RPC provider comparison for push notifications

For a mobile push app, we recommend Alchemy or QuickNode due to low latency and built-in webhook support. Provider choice impacts budget: Alchemy and QuickNode are more expensive than Infura but offer lower latency and built-in webhooks, which saves development time.

Application architecture

struct FilterConfig: Codable {
    var minAmountUSD: Double
    var eventTypes: [EventType]
    var quietHoursStart: Date?
    var quietHoursEnd: Date?
}

enum EventType: String, Codable {
    case incoming, outgoing, swap, contractInteraction
}

Monitoring setup process

1. Step 1: Requirements gathering — identify chains, addresses, filters, and notification scenarios.
2. Step 2: RPC provider selection — Alchemy, QuickNode, or Infura based on budget and load.
3. Step 3: Adapter development — build modules for each chain with WebSocket and webhook support.
4. Step 4: Filter configuration — set thresholds, quiet hours, and batching.
5. Step 5: Backend integration — backend receives events, stores them, and sends push via FCM/APNs.
6. Step 6: Load testing — simulate 1000 transactions per minute, check stability.
7. Step 7: Deployment and monitoring — deploy to production and track metrics.

What's included in a turnkey solution

• Multi-chain architecture (EVM + Solana optional)
• Wallet tracking and management of tracked addresses and contracts
• Event feed with filters and search
• Push notifications with amount/type filtering, quiet hours (transaction alerts)
• Detailed transaction card with block explorer link
• Offline mode with caching of recent events
• Integration with Alchemy Notify, QuickNode, or Moralis (by choice)
• Onchain monitoring for DeFi and dapp development

Timeline and cost

Timeline — 7–12 working days depending on the number of supported chains and integration depth. On average, projects cost $8,000–$15,000 and pay for themselves in 2-3 months through reduced manual monitoring overhead (saving $1,000–$3,000 per month) and fewer missed opportunities. Contact us for a preliminary estimate — we'll prepare the architecture and optimize the budget for your stack. Schedule a consultation to discuss details.

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.