Crypto Trading Platform Performance Optimization

Project Overview

A white-label cryptocurrency trading platform was experiencing severe performance issues. Built with legacy Redux patterns (class components, connect HOCs, massive reducers), the UI struggled with real-time data updates from WebSocket feeds.

The Challenge

//Legacy Architecture Issues

The existing codebase suffered from:

• Monolithic Redux store with 50+ interconnected reducers
• Class component architecture with complex lifecycle methods
• Excessive re-renders during real-time price updates
• Bundle bloat from outdated dependencies
• Memory leaks from improper WebSocket handling

//Performance Metrics (Before)

Our Approach

//Phase 1: Architecture Analysis

We conducted a comprehensive audit of the existing codebase:

// Legacy pattern causing re-renders
const mapStateToProps = (state) => ({
  allOrders: state.orders.list,
  allTrades: state.trades.history,
  allPrices: state.prices.current,
  // Every component subscribed to everything
});

//Phase 2: Zustand Store Design

We designed atomic stores for different domains:

// New Zustand architecture
export const usePriceStore = create<PriceStore>((set) => ({
  prices: {},
  updatePrice: (symbol, price) => 
    set((state) => ({
      prices: { ...state.prices, [symbol]: price }
    })),
}));

export const useOrderStore = create<OrderStore>((set) => ({
  orders: [],
  addOrder: (order) => 
    set((state) => ({ 
      orders: [...state.orders, order] 
    })),
}));

// Components subscribe to only what they need
const BTC_Price = usePriceStore((s) => s.prices['BTC']);

//Phase 3: Wrapper Pattern for Legacy Compatibility

Rather than a complete rewrite, we wrapped legacy Redux with Zustand:

// Bridge layer - gradual migration
const useLegacyReduxBridge = () => {
  const dispatch = useDispatch();
  const zustandStore = useTradeStore();
  
  // Sync Zustand to Redux for legacy components
  useEffect(() => {
    const unsubscribe = zustandStore.subscribe((state) => {
      dispatch(syncFromZustand(state));
    });
    return unsubscribe;
  }, []);
};

//Phase 4: WebSocket Optimization

Implemented efficient WebSocket handling with batched updates:

// Batched updates for high-frequency data
const priceBuffer = new Map();
let rafId: number;

ws.onmessage = (event) => {
  const { symbol, price } = JSON.parse(event.data);
  priceBuffer.set(symbol, price);
  
  if (!rafId) {
    rafId = requestAnimationFrame(() => {
      usePriceStore.getState().batchUpdate(
        Object.fromEntries(priceBuffer)
      );
      priceBuffer.clear();
      rafId = 0;
    });
  }
};

Results

//Performance Metrics (After)

//User Experience Impact

• Trade execution feels instant - Users can react to market movements faster
• Smooth chart rendering - TradingView integration no longer stutters
• Mobile performance - Previously unusable, now fluid
• Reduced bounce rate - 35% improvement in session duration

Key Takeaways

1. Incremental migration works - The wrapper pattern allowed gradual transition
2. Atomic stores prevent cascading re-renders - Zustand's selector pattern is powerful
3. Batch high-frequency updates - RAF batching is essential for real-time data
4. Measure everything - Performance budgets guided our decisions