<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Go on Shai Asher</title><link>https://slow-is-smooth.io/tags/go/</link><description>Recent content in Go on Shai Asher</description><generator>Hugo</generator><language>en-gb</language><lastBuildDate>Sun, 06 Sep 2026 09:00:00 +0300</lastBuildDate><atom:link href="https://slow-is-smooth.io/tags/go/index.xml" rel="self" type="application/rss+xml"/><item><title>The cache was working perfectly. That was the problem.</title><link>https://slow-is-smooth.io/blog/cache-stampede-war-story/</link><pubDate>Sun, 06 Sep 2026 09:00:00 +0300</pubDate><guid>https://slow-is-smooth.io/blog/cache-stampede-war-story/</guid><description>&lt;h2 id="0247"&gt;02:47&lt;/h2&gt;&#10;&lt;p&gt;Falafel Corp runs a one-person on-call rotation, which is a staffing decision that looks&#10;efficient right up until the night it isn&amp;rsquo;t. Tonight it is your turn, and the phone goes off&#10;on the nightstand, and you are awake before you are conscious.&lt;/p&gt;</description></item><item><title>Finding Errors in Log Streams</title><link>https://slow-is-smooth.io/blog/finding-errors-in-log-streams/</link><pubDate>Sat, 05 Sep 2026 12:00:00 +0300</pubDate><guid>https://slow-is-smooth.io/blog/finding-errors-in-log-streams/</guid><description>&lt;p&gt;Two questions come up constantly when processing large log files:&lt;/p&gt;&#10;&lt;blockquote&gt;&#10;&lt;p&gt;&lt;strong&gt;Where is the 1000th error?&lt;/strong&gt;&lt;/p&gt;&#10;&lt;p&gt;&lt;strong&gt;How many errors happened before this timestamp?&lt;/strong&gt;&lt;/p&gt;&#10;&lt;/blockquote&gt;&#10;&lt;p&gt;They look trivial. At scale they are not. The obvious implementation scans the&#10;whole dataset for every question, and with ten million entries that is ten&#10;million comparisons to answer one of them.&lt;/p&gt;</description></item><item><title>SIMD-Optimized Bloom Filter in Go: An In-Depth Exploration</title><link>https://slow-is-smooth.io/blog/simd-optimized-bloom-filter-in-go-an-in-depth-exploration/</link><pubDate>Mon, 22 Sep 2025 07:03:20 +0000</pubDate><guid>https://slow-is-smooth.io/blog/simd-optimized-bloom-filter-in-go-an-in-depth-exploration/</guid><description>&lt;p&gt;&lt;strong&gt;Project Repository:&lt;/strong&gt; &lt;a href="https://github.com/shaia/BloomFilter"&gt;https://github.com/shaia/BloomFilter&lt;/a&gt;&lt;/p&gt;&#10;&lt;h3 id="from-go-to-assembly"&gt;From Go to Assembly&lt;/h3&gt;&#10;&lt;p&gt;When we think of Go, we think of concurrency, simplicity, and &amp;ldquo;good enough&amp;rdquo; performance. But what happens when &amp;ldquo;good enough&amp;rdquo; isn&amp;rsquo;t good enough? What happens when you need to squeeze every last drop of performance out of the CPU for a critical, hot-path operation?&lt;/p&gt;</description></item></channel></rss>