<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Argo Events on 黄文卓 | DevOps Engineer</title><link>https://socake.github.io/tags/argo-events/</link><description>Recent content in Argo Events on 黄文卓 | DevOps Engineer</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><managingEditor>17691281867@163.com (Wenzhuo Huang)</managingEditor><webMaster>17691281867@163.com (Wenzhuo Huang)</webMaster><copyright>© 2026 Wenzhuo Huang</copyright><lastBuildDate>Sun, 12 Apr 2026 11:00:00 +0800</lastBuildDate><atom:link href="https://socake.github.io/tags/argo-events/index.xml" rel="self" type="application/rss+xml"/><item><title>Argo Workflows 工作流实战：批处理与 ML Pipeline</title><link>https://socake.github.io/posts/argo-workflows-practice/</link><pubDate>Sun, 12 Apr 2026 11:00:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/argo-workflows-practice/</guid><description>Argo Workflows 是 Kubernetes 原生的工作流引擎，适合批处理和 ML Pipeline 场景。本文涵盖与 Airflow/Temporal 的选型对比、核心资源模型、三个完整实战（DAG 数据处理、ML 训练 Pipeline、定时备份）、资源管控（Semaphore/Node Selector）、Argo Events 事件驱动触发，以及 Prometheus 监控和常见问题处理。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/argo-workflows-practice/featured.jpg"/></item></channel></rss>