<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Kubernetes-Manifests on No Semicolons</title><link>https://nosemicolons.com/tags/kubernetes-manifests/</link><description>Recent content in Kubernetes-Manifests on No Semicolons</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 13 Jul 2026 10:51:48 +0000</lastBuildDate><atom:link href="https://nosemicolons.com/tags/kubernetes-manifests/index.xml" rel="self" type="application/rss+xml"/><item><title>The AI Code Generation Kubernetes Disaster: How Generated Manifests Are Breaking Production Clusters</title><link>https://nosemicolons.com/posts/ai-generated-kubernetes-manifests-production-disasters/</link><pubDate>Mon, 13 Jul 2026 10:51:48 +0000</pubDate><guid>https://nosemicolons.com/posts/ai-generated-kubernetes-manifests-production-disasters/</guid><description>&lt;p>Ever copy-pasted a Kubernetes manifest from ChatGPT and watched your deployment succeed, only to find your cluster slowly bleeding resources three days later? You&amp;rsquo;re not alone.&lt;/p>
&lt;p>I&amp;rsquo;ve been there. Last month, I trusted an AI-generated deployment manifest for a microservice that looked perfect on the surface. Clean YAML, proper indentation, even had resource limits. But buried in those innocent-looking lines was a ticking time bomb: missing liveness probes and a restart policy that would spiral out of control under load.&lt;/p></description></item></channel></rss>