<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Scalability on Mechanical Snail</title><link>https://mechanicalsnail.com/tags/scalability/</link><description>Recent content in Scalability on Mechanical Snail</description><image><title>Mechanical Snail</title><url>https://mechanicalsnail.com/images/logo.png</url><link>https://mechanicalsnail.com/images/logo.png</link></image><generator>Hugo -- 0.152.2</generator><language>en-us</language><lastBuildDate>Wed, 10 Jul 2024 13:00:00 +0100</lastBuildDate><atom:link href="https://mechanicalsnail.com/tags/scalability/index.xml" rel="self" type="application/rss+xml"/><item><title>Feed Ranking Architecture &amp; Operations (Part 5 of 6)</title><link>https://mechanicalsnail.com/posts/recommendation-systems-part5/</link><pubDate>Wed, 10 Jul 2024 13:00:00 +0100</pubDate><guid>https://mechanicalsnail.com/posts/recommendation-systems-part5/</guid><description>Part 5 of 6: a reference feed-ranking architecture — request flow, latency budgets, ads blending, two-tower retrieval and ranking implementations, and production monitoring.</description></item><item><title>Recommendation Systems in Production (Part 3 of 6)</title><link>https://mechanicalsnail.com/posts/recommendation-systems-part3/</link><pubDate>Wed, 10 Jul 2024 11:00:00 +0100</pubDate><guid>https://mechanicalsnail.com/posts/recommendation-systems-part3/</guid><description>Part 3 of 6: running recommenders in production — offline ranking metrics, A/B testing statistics, distributed training, model serving and compression, cold start, and drift.</description></item><item><title>Social Media Platform Architecture at Scale</title><link>https://mechanicalsnail.com/posts/social-media-architecture/</link><pubDate>Sun, 08 Oct 2023 13:00:00 +0100</pubDate><guid>https://mechanicalsnail.com/posts/social-media-architecture/</guid><description>Systems architecture for an Instagram-scale social platform: fan-out on write versus read, graph sharding, feed caching, and absorbing celebrity-tier traffic spikes.</description></item><item><title>Building a Time Series Database in Go</title><link>https://mechanicalsnail.com/posts/timeseries-database-go/</link><pubDate>Sun, 11 Jun 2023 14:00:00 +0100</pubDate><guid>https://mechanicalsnail.com/posts/timeseries-database-go/</guid><description>Inside a high-performance time series database in Go: LSM-style storage, delta-of-delta and Gorilla compression, inverted label indexes, and range query execution.</description></item></channel></rss>