TechPrufer
Get started
Jane Street
Jane Street logoJane Street · Feature trail

Messaging

1 post · Oct 2026

What this trail covers

This post extends the messaging capability by detailing optimizations to Aria, an internal messaging framework. It introduces a new indexing strategy for tip recovery, reducing CPU usage by 30% and addressing server overload. Additionally, it details an adaptive splitting algorithm for subtree stores to improve initial recovery performance by intelligently distributing messages based on volume, mitigating issues with filtering excess data and allowing users to structure topics more intuitively. The work involved benchmarking, using AI agents for heap implementation selection and UI visualization, and implementing a greedy clustering algorithm with binary search for adaptive splitting.

All Jane Street trails
  1. Scaling and benchmarking a critical message bus using a new indexing strategyIntroduced a new indexing strategy for Aria's tip recovery, utilizing topic partitions and a min-heap (optimized via AI-driven heap implementation selection) to efficiently filter messages, resulting in a 30% CPU usage reduction. Developed an adaptive splitting algorithm for subtree stores, combining a greedy clustering algorithm with binary search, to intelligently distribute messages based on volume and improve initial recovery performance.