Architecture Guide

Modern markets require high efficiency, flexibility, and reliability in trading systems. To achieve these goals, companies actively employ composite architectures, including microservices and advanced data storage tools like Redis. In this article, we will explore how a composite architecture with the integration of microservices and Redis can enhance a trading system, and we will also delve into the roles of different services within this architecture: trading provider, strategy service, trade display terminal, and risk management service.

Advantages of a composite architecture with microservices and Redis

A composite architecture represents an approach in which complex systems are built by combining individual components. In the context of trading systems, this means splitting functionality into separate microservices, each performing a specific task. This approach offers several advantages:

1. Flexibility and scalability

Microservices can be developed, scaled, and updated independently of one another. This enables quicker adaptation to changing market requirements.

2. Distributed nature

Distributing functionality across microservices allows for load distribution and enhances system fault tolerance.

3. Simplified deployment

Microservices can be deployed independently, simplifying the development and testing processes.

4. Isolation and security

Each microservice can run in its isolated environment, enhancing security and preventing the spread of failures.

5. Team scalability

Development teams can work on individual microservices, improving project organization and management.

Roles and functions of services in the architecture

1. Trading provider

This service handles communication with market platforms, fetching data about quotes and trading operations. It can also aggregate data from various markets and offer a unified interface for other services.

2. Strategy service

This service implements trading strategies and algorithms. It receives market data from the trading provider, analyzes it, and makes decisions regarding trades. Machine learning and analytics can be employed here to enhance trading efficiency.

3. Trade display terminal

This service is responsible for displaying data about current and past trades, quotes, and other relevant information for traders and system users.

4. Risk management service

It oversees risk control and portfolio management. The service monitors trading operations, analyzes potential risks, and takes measures to minimize losses.

Integrating Redis into the architecture

Redis is a fast and scalable open-source database that can be used for various purposes, including caching, session storage, message publishing and subscription, among others. In a trading system, Redis can be utilized for:

- Data caching

Infrequently changing data, such as market quotes, can be cached in Redis to expedite access and reduce the load on other services.

- Temporary data storage

Redis is suitable for storing temporary data, such as user sessions, strategy states, and temporary aggregated data.

- Publish-subscribe mechanism

Redis provides a publish-subscribe mechanism, which can be employed for instant dissemination of trade and quote data between various services.

A composite architecture with microservices and Redis provides modern trading systems with high flexibility, scalability, and reliability. Integrating various services like the trading provider, strategy service, trade display terminal, and risk management service creates a comprehensive system capable of effectively responding to dynamic market changes and ensuring successful trading. The use of Redis as a data storage tool complements the architecture, providing swift access to critical information and enhancing overall system performance.

Let's consider an example of a simple trading system architecture using microservices and Redis in pseudocode.

Trading provider - Python

# trading_provider.py

class TradingProvider:
    def fetch_quotes(self, symbol):
        # Fetch quotes from market platform
        quotes = self._fetch_quotes_from_exchange(symbol)
        # Store quotes in Redis cache
        redis.set(f"quotes:{symbol}", quotes)
        return quotes

    def _fetch_quotes_from_exchange(self, symbol):
        # Fetch quotes from the exchange
        return exchange_api.fetch_quotes(symbol)

# Usage
trading_provider = TradingProvider()
quotes = trading_provider.fetch_quotes("AAPL")
print(quotes)

Strategy service - JavaScript

// strategy_service.js

class StrategyService {
    constructor() {
        this.redisClient = new RedisClient();
    }

    analyze_market_data(symbol) {
        const quotes = this.redisClient.get(`quotes:${symbol}`);
        // Implement strategy analysis logic
        const decisions = this._analyze(quotes);
        return decisions;
    }

    _analyze(quotes) {
        // Strategy analysis logic
        // ...
        return decisions;
    }
}

// Usage
const strategyService = new StrategyService();
const decisions = strategyService.analyze_market_data("AAPL");
console.log(decisions);

Trade display terminal - HTML/CSS/JavaScript

<!-- trade_display_terminal.html -->

<!DOCTYPE html>
<html>
<head>
    <title>Trade Display Terminal</title>
    <link rel="stylesheet" type="text/css" href="styles.css">
</head>
<body>
    <div id="trade-list">
        <!-- Trade data will be displayed here -->
    </div>
    <script src="trade_display_terminal.js"></script>
</body>
</html>

// trade_display_terminal.js

class TradeDisplayTerminal {
    constructor() {
        this.redisClient = new RedisClient();
    }

    display_trades() {
        const trades = this.redisClient.get("recent_trades");
        this._render(trades);
    }

    _render(trades) {
        const tradeList = document.getElementById("trade-list");
        tradeList.innerHTML = ""; // Clear previous data
        trades.forEach(trade => {
            const tradeDiv = document.createElement("div");
            tradeDiv.textContent = `Trade: ${trade.symbol} - Price: ${trade.price}`;
            tradeList.appendChild(tradeDiv);
        });
    }
}

// Usage
const terminal = new TradeDisplayTerminal();
terminal.display_trades();

Risk Management Service - Java

// RiskManagementService.java

public class RiskManagementService {
    private RedisClient redisClient = new RedisClient();

    public void monitor_risk(String tradeId) {
        Trade trade = redisClient.get(tradeId);
        // Implement risk analysis logic
        boolean isHighRisk = this._analyze_risk(trade);
        if (isHighRisk) {
            // Take appropriate actions
            this._take_action(trade);
        }
    }

    private boolean _analyze_risk(Trade trade) {
        // Risk analysis logic
        // ...
    }

    private void _take_action(Trade trade) {
        // Action to mitigate risk
        // ...
    }
}

// Usage
RiskManagementService riskService = new RiskManagementService();
riskService.monitor_risk("trade123");

Please note that this is pseudocode and may require further refinement to work correctly. In this example, we demonstrated how each of the services could interact with Redis for data storage and retrieval.