Cyberapper

Essay · · 3 min

Cadenza design note

An architecture sketch for a large trading engine: client, gateway, matching and risk layers joined by HTTP, WebSocket and FIX.

By Sonami

Contents
  1. High-Level Architecture
    1. Client Layer
    2. Gateway Layer
    3. Load Balancer
    4. Trading Core
    5. Market Data Layer
    6. Liquidity Provider Layer
    7. Data Storage Layer
    8. Monitoring and Logging
    9. Security Layer
  2. Detailed Components
    1. Client Layer
    2. Gateway Layer
    3. Load Balancer
    4. Trading Core
    5. Market Data Layer
    6. Liquidity Provider Layer
    7. Data Storage Layer
    8. Monitoring and Logging
    9. Security Layer
  3. Scalability Considerations
  4. Example Technology Stack

Creating a large-scale trading engine requires careful architectural planning to ensure high performance, low latency, and scalability. Below is a high-level architecture design for your trading engine that leverages HTTP, WebSocket, and FIX protocol.

High-Level Architecture

Client Layer

  • HTTP API: For standard request-response interactions.
  • WebSocket API: For real-time data delivery and bi-directional communication.
  • FIX API: For institutional clients and high-frequency trading.

Gateway Layer

  • API Gateway: Handles and routes HTTP and WebSocket requests. This layer ensures security (authentication and authorization), rate limiting, and request validation.

Load Balancer

  • Load Balancer: Distributes incoming connections from clients to multiple instances of trading servers to ensure even load distribution and high availability.

Trading Core

  • Trading Engine: High-performance, low-latency engine that handles order matching, order book management, and execution.
  • Quote Aggregator: Aggregates quotes from liquidity providers in real-time.
  • Order Router: Routes orders to the appropriate liquidity provider based on the best available price and execution policies.

Market Data Layer

  • Market Data Feeds: Consumes and processes real-time market data from multiple liquidity providers.
  • Normalization Layer: Normalizes data from various formats to a unified format.
  • Market Data Distributor: Distributes processed market data to clients via WebSocket or HTTP endpoints.

Liquidity Provider Layer

  • FIX Connectors: Connects to liquidity providers using FIX protocol.
  • WebSocket/HTTP Connectors: Connects to liquidity providers using WebSocket or HTTP APIs.

Data Storage Layer

  • High-Performance Databases: For storing order books, trade history, and market data.
  • Use in-memory databases (e.g., Redis) for real-time data.
  • Use relational databases (e.g., PostgreSQL) for transactional data.
  • Use NoSQL databases (e.g., Cassandra) for scalable market data storage.

Monitoring and Logging

  • Monitoring Tools: Tools like Prometheus and Grafana to monitor system health, performance metrics, and alerting.
  • Centralized Logging: Utilizing ELK Stack (Elasticsearch, Logstash, Kibana) for log aggregation and analysis.

Security Layer

  • DDoS Protection: To protect against distributed denial-of-service attacks.
  • WAF (Web Application Firewall): To filter and monitor HTTP/HTTPS requests.
  • Encryption: SSL/TLS for data-in-transit and encryption for data-at-rest.

Detailed Components

Client Layer

  • Clients: Various clients such as web platforms, mobile apps, and institutional traders use the HTTP, WebSocket, and FIX APIs to interact with the trading engine.

Gateway Layer

  • API Gateway: Manages all incoming API requests. Examples: Kong, NGINX, AWS API Gateway.
  • Authentication & Authorization: JWT tokens, OAuth.
  • Rate Limiting: To prevent abuse and ensure fair usage.

Load Balancer

  • Load Balancer: Examples: HAProxy, NGINX, AWS Elastic Load Balancing, Google Cloud Load Balancing.

Trading Core

  • Trading Engine: Developed with languages known for high performance (e.g., C++, Java).
  • Order Matching Algorithm: FIFO, Pro-Rata, etc.
  • Quote Aggregator: Receives and aggregates quotes from liquidity providers continuously.
  • Order Router: Implements smart order routing (SOR) to achieve optimal execution.

Market Data Layer

  • Market Data Feeds: Interfaces with market data providers.
  • Normalization Layer: Unifies data formats across different providers.
  • Market Data Distributor: Distributes real-time data to subscribed clients.

Liquidity Provider Layer

  • FIX Connectors: Handles connections to liquidity providers via the FIX protocol.
  • WebSocket/HTTP Connectors: Manages connections using WebSocket or HTTP APIs.

Data Storage Layer

  • In-memory Databases: For high-speed data access (e.g., Redis).
  • Relational Databases: For reliable transactional data storage (e.g., PostgreSQL).
  • NoSQL Databases: Handles large volumes of market data (e.g., Cassandra).

Monitoring and Logging

  • Prometheus/Grafana: Metric collection and visualization.
  • ELK Stack: Centralized logging and log analysis.

Security Layer

  • DDoS Protection: Services like Cloudflare.
  • WAF: Protection against web attacks.
  • Encryption: Ensuring secure data transfer and storage.

Scalability Considerations

  • Horizontal Scalability: Adding more servers to handle increased loads.
  • Microservices Architecture: Decoupling services to independently scale and manage.
  • Auto-Scaling: Leveraging cloud auto-scaling features to dynamically manage resources based on load.

Example Technology Stack

  • Languages: C++, Java, Node.js, Python.
  • APIs: REST, GraphQL, FIX protocol.
  • Databases: PostgreSQL, Redis, Cassandra.
  • Servers: NGINX, HAProxy.
  • Hosting: AWS, Google Cloud, Azure.

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