<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Home on Assemblu</title><link>https://localhost:1313/</link><description>Recent content in Home on Assemblu</description><generator>Hugo -- gohugo.io</generator><language>en</language><managingEditor>info@assemb.lu (Assemblu)</managingEditor><webMaster>info@assemb.lu (Assemblu)</webMaster><copyright>© 2025 Assemblu</copyright><lastBuildDate>Mon, 27 Oct 2025 14:38:44 +0100</lastBuildDate><atom:link href="https://localhost:1313/index.xml" rel="self" type="application/rss+xml"/><item><title>Thread-Safe Hyperliquid Ingestion With Real-Time Freshness</title><link>https://localhost:1313/posts/thread-safe-hyperliquid-ingestion-real-time-freshness/</link><pubDate>Mon, 27 Oct 2025 14:38:44 +0100</pubDate><author>info@assemb.lu (Assemblu)</author><guid>https://localhost:1313/posts/thread-safe-hyperliquid-ingestion-real-time-freshness/</guid><description>&lt;p&gt;Shipping market data out of Hyperliquid looks simple until the pipes clog. My ingestion service was running inside a single container with three moving parts: a WebSocket listener, a PostgreSQL batch writer, and a NATS publisher. The new monitoring thread I introduced last week caught stalled pipelines in minutes, but it also uncovered a couple of subtle threading bugs and a nasty freshness regression. This post walks through what went wrong, how I fixed it in C++, and why the service now holds a rock-solid one second stale-data delta.&lt;/p&gt;</description></item></channel></rss>