<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Logging on Commentary of Takao</title><link>https://takao.blog/en/tags/logging/</link><description>Recent content in Logging on Commentary of Takao</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>Commentary of Takao</copyright><lastBuildDate>Sat, 13 Jun 2026 23:11:50 +0900</lastBuildDate><atom:link href="https://takao.blog/en/tags/logging/index.xml" rel="self" type="application/rss+xml"/><item><title>Node.js Logging Best Practices: Structured and Scalable</title><link>https://takao.blog/en/web/nodejs-logging/</link><pubDate>Tue, 06 Aug 2024 00:00:00 +0900</pubDate><guid>https://takao.blog/en/web/nodejs-logging/</guid><description>&lt;img src="https://takao.blog/img/thumnail.webp" alt="Featured image of post Node.js Logging Best Practices: Structured and Scalable" /&gt;&lt;p&gt;Production-grade logging is one of the most overlooked aspects of Node.js application development. While &lt;code&gt;console.log&lt;/code&gt; works for debugging locally, it falls apart in distributed environments where logs must be searchable, structured, and actionable. This article covers the essential patterns for building a logging strategy that scales.&lt;/p&gt;
&lt;h2 id="why-structured-logging"&gt;Why Structured Logging
&lt;/h2&gt;&lt;p&gt;Traditional unstructured logging outputs plain text that is difficult to parse programmatically. Consider &lt;code&gt;console.log(&amp;quot;User logged in:&amp;quot;, userId)&lt;/code&gt;. Grepping this across hundreds of service instances is slow and error-prone. Structured logging outputs each log event as a JSON object, making it machine-readable and queryable by log aggregation systems.&lt;/p&gt;</description></item></channel></rss>