<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Monitoring on Commentary of Takao</title><link>https://takao.blog/en/tags/monitoring/</link><description>Recent content in Monitoring 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/monitoring/index.xml" rel="self" type="application/rss+xml"/><item><title>Node.js Performance Monitoring: Metrics That Matter</title><link>https://takao.blog/en/web/nodejs-performance/</link><pubDate>Wed, 18 Dec 2024 00:00:00 +0900</pubDate><guid>https://takao.blog/en/web/nodejs-performance/</guid><description>&lt;img src="https://takao.blog/img/thumnail.webp" alt="Featured image of post Node.js Performance Monitoring: Metrics That Matter" /&gt;&lt;p&gt;Node.js performance monitoring requires a different approach than traditional server environments. The single-threaded event loop, garbage-collected memory model, and asynchronous I/O create unique failure modes that generic CPU and memory metrics alone cannot capture. This article covers the essential metrics and tools you need to keep Node.js applications running smoothly in production.&lt;/p&gt;
&lt;h2 id="why-nodejs-performance-monitoring-is-different"&gt;Why Node.js Performance Monitoring Is Different
&lt;/h2&gt;&lt;p&gt;Unlike multi-threaded servers where a slow operation blocks only one thread, a single CPU-heavy operation in Node.js blocks the entire event loop, stalling all concurrent requests. Garbage collection pauses can introduce unpredictable latency spikes. Common failure modes include event loop starvation, memory leaks from uncleaned closures, callback thrashing, and unhandled promise rejections silently swallowing errors. Understanding these characteristics is the first step toward effective monitoring.&lt;/p&gt;</description></item><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>