In algorithmic trading, real-time responsiveness is critical. A typical architecture includes:

• Market event ingestion: Real-time price feeds, order books, and trades are captured as events.
• Stream processing: Events are processed with minimal latency to trigger algorithmic decisions (buy/sell orders, position updates).
• Event streaming platforms: Kafka or Kinesis handle high-throughput, low-latency message delivery between components.
• Data capture: Snowplow can log trade execution events, user interactions, and market conditions to provide observability and backtesting data.

This architecture ensures timely reactions to market fluctuations while maintaining a historical event log for analytics and compliance.