<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ACK on 黄文卓 | DevOps Engineer</title><link>https://socake.github.io/tags/ack/</link><description>Recent content in ACK 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>Thu, 30 Apr 2026 16:00:00 +0800</lastBuildDate><atom:link href="https://socake.github.io/tags/ack/index.xml" rel="self" type="application/rss+xml"/><item><title>Playbook：K8s 成本优化实战——Karpenter + 弹性占位 + 精细 NodePool 的组合拳</title><link>https://socake.github.io/playbook/k8s-cost-optimization-karpenter/</link><pubDate>Thu, 30 Apr 2026 16:00:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/playbook/k8s-cost-optimization-karpenter/</guid><description>Karpenter 不是开箱即用的省钱按钮。把它跑出真实收益，需要先做 NodePool 按 workload 分层，再处理 sandbox/gpu 这类不被 K8s 识别的工作负载，最后用 placeholder 占位 Pod 弥合「扩容慢但缩容快」的体验缺口。本文给出可直接 kubectl apply 的完整 yaml 与可 chmod +x 直接跑的脚本，覆盖安装、四类 NodePool、弹性占位、S3 Gateway Endpoint、MQ 降级、监控与告警。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/playbook/k8s-cost-optimization-karpenter/featured.jpg"/></item><item><title>Playbook：K8s 集群三合一实战——QA / PRE / AI Sandbox 合并的完整可执行手册</title><link>https://socake.github.io/playbook/k8s-cluster-consolidation/</link><pubDate>Thu, 30 Apr 2026 13:00:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/playbook/k8s-cluster-consolidation/</guid><description>集群合并的好处显性，坏处隐性。本 Playbook 不再停留在『讲个思路』，每段 yaml 都是完整 manifest（含 Namespace / ServiceAccount / RBAC / Secret），每段脚本都能 chmod +x 直接跑，每个步骤含前置 / 执行 / 验证 / 回滚四件套，并附一次真实事故的完整修复 SQL。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/playbook/k8s-cluster-consolidation/featured.jpg"/></item></channel></rss>