📄️ Building a Basic Order Book in C++
Step-by-step implementation of a basic order book in C++ with order matching, buy/sell queues, and real-time market depth. Foundation for building trading system infrastructure.
📄️ Building an Order Execution Engine: Simulating EVM-Based Trading
Building an advanced order execution engine in C++ that simulates EVM-based trading, with order matching, fill prices, gas cost tracking, and slippage metrics — critical for evaluating trading performance.
📄️ Is Python Too Slow for Crypto Trading? We Ran the Numbers.
Everyone says Python is too slow for trading. We benchmarked pure Python vs NumPy vs Pandas on 1M rows, then compared the results to actual on-chain block times. The answer depends entirely on which chain you're trading.
📄️ Colocation and Latency for Crypto Trading: Same-Provider vs Cross-Provider, Cross-Region
We benchmark latency from EC2 in Tokyo and US East 1 to AWS and GCP Europe endpoints using TCP/TLS timing. From AWS US East 1, connect time to AWS Europe is ~74–104 ms and to GCP Europe ~87–99 ms. From Tokyo to the same endpoints it is ~216–225 ms (AWS) and ~248–262 ms (GCP). Same provider is lower than cross-provider. Here's the methodology and how to run the script yourself.
📄️ Diagnosing and Fixing Kafka Consumer Connection Issues in Java
Diagnosing Kafka consumer connection failures in Java caused by IPv6/IPv4 dual-stack networking conflicts. Covers cryptic authentication errors, Maven dependency resolution bugs, and systematic fixes.
📄️ 6 ML Model Mistakes People Make With Crypto Data (And How to Fix Them)
Most crypto ML models fail before training ends. Here are the six mistakes killing model performance: raw inputs, wrong architectures, bad targets, and more.