<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ArgoCD on StackSimplify | DevOps &amp; Cloud Education by Kalyan Reddy</title><link>https://stacksimplify.com/tags/argocd/</link><description>Recent content in ArgoCD on StackSimplify | DevOps &amp; Cloud Education by Kalyan Reddy</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Tue, 14 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://stacksimplify.com/tags/argocd/index.xml" rel="self" type="application/rss+xml"/><item><title>CI/CD for ML: Same GitHub Actions, Different Artifact</title><link>https://stacksimplify.com/blog/cicd-for-ml/</link><pubDate>Tue, 14 Apr 2026 00:00:00 +0000</pubDate><guid>https://stacksimplify.com/blog/cicd-for-ml/</guid><description>Your CI/CD pipeline deploys code. Ours deploys models. Same tools.
GitHub Actions. ArgoCD. Docker. DVC. MLflow. Same stack you already run. The only difference is what triggers the pipeline and what gets deployed.
Code pipeline: git push &amp;gt; build &amp;gt; test &amp;gt; deploy ML pipeline: data change &amp;gt; retrain &amp;gt; evaluate &amp;gt; deploy
The 7-Job ML Pipeline Job What It Does Failure Action 0. Preflight 7 infra checks in 5 min (MLflow up?</description></item></channel></rss>