The engineering behind quantitative finance: algorithms, systems & infrastructure

The Hidden DAG Behind Every Modern Trading System: How Market Data Is Ingested at Scale

Posted on Sat 24 January 2026 | Part 5 of Distributed Systems in Finance | 17 min read

Modern trading systems rely on directed acyclic graphs (DAGs) that branch, merge, and transform real-time feeds into many parallel consumers: matching engines, risk checks, analytics, surveillance, and storage. These ingestion DAGs exist to isolate failure, control fan-out, and preserve latency and correctness under extreme market conditions.

Flow Control in Low-Latency Systems: Batching, Conflation, and Backpressure

Posted on Sat 10 January 2026 | Part 3 of Low-Latency Fundamentals | 15 min read

Low-latency systems fail when work becomes unbounded. Batching, conflation, and backpressure are mechanisms that keep systems stable under bursty, adversarial load. Without them, tail latency and cascading failures are inevitable.

Observability at Scale: Distributed Telemetry for Modern Trading Infrastructure

Posted on Sat 13 December 2025 | Part 4 of Distributed Systems in Finance | 22 min read

How do trading systems observe themselves in real time? This article breaks down the telemetry architecture that keeps distributed systems visible under extreme latency pressure.

How Exchanges Turn Order Books into Distributed Logs

Posted on Sat 06 December 2025 | Part 1 of Market Microstructure & Global Systems | 22 min read

Every modern exchange is a distributed database in disguise. This article reveals how trading engines transform chaotic streams of buy and sell orders into a perfectly ordered, replayable log, ensuring fairness, determinism, and market data reliability.

Latency Profiling in Python: From Code Bottlenecks to Observability

Posted on Sat 29 November 2025 | Part 2 of Low-Latency Fundamentals | 19 min read

Learn how to pinpoint where time disappears in Python systems, from CPU and I/O bottlenecks to Prometheus metrics and continuous profilers. Explore the tools that turn raw measurements into observability dashboards revealing real performance patterns.

Understanding Latency: From Wire to Code

Posted on Sat 15 November 2025 | Part 1 of Low-Latency Fundamentals | 12 min read

Every microsecond counts, but where do they actually go?

This article traces the hidden journey of a message from the network wire to the application's code, revealing how the NIC, interrupts, syscalls, and runtimes introduce delay at every hop.

Dissecting the Infra of DeFi Protocols

Posted on Sat 08 November 2025 | Part 2 of DeFi Engineering | 15 min read

Most DeFi discussions stop at smart contracts. This article goes deeper: through the data pipelines, executors, keepers, and coordination layers that make protocols run. If you're a software engineer, you'll see how DeFi architecture mirrors the systems you already know.

What Database Scaling Looks Like When Milliseconds Mean Millions

Posted on Sat 01 November 2025 | Part 3 of Distributed Systems in Finance | 12 min read

Financial systems process billions of time-series data points with sub-millisecond query requirements: constraints that break traditional databases.

Learn the architectural patterns that actually work: vertical scaling strategies, intelligent sharding schemes, and why market data demands different trade-offs than web applications.

Introduction to DeFi Engineering

Posted on Thu 23 October 2025 | Part 1 of DeFi Engineering | 14 min read

An introduction to the engineering landscape in DeFi protocols: the distinct engineering roles (protocol, infrastructure, execution), the complete technology stack from smart contracts to off-chain systems, core primitives like liquidity pools and oracles, and what makes building in this space fundamentally different from traditional fintech.

How to Build Execution Systems for Crypto Trading at Scale

Posted on Sun 12 October 2025 | Part 3 of Building Real Trading Systems | 35 min read

How do you execute $100M orders across 10+ crypto exchanges without moving the market? This deep-dive covers the infrastructure behind institutional trading systems: market data pipelines, smart order routing, execution quality metrics, and building for failure.

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