<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Karpenter on 黄文卓 | DevOps Engineer</title><link>https://socake.github.io/tags/karpenter/</link><description>Recent content in Karpenter 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/karpenter/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><item><title>FinOps 实践：Kubernetes 成本治理体系建设</title><link>https://socake.github.io/posts/finops-kubernetes-cost-governance/</link><pubDate>Sun, 12 Apr 2026 10:00:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/finops-kubernetes-cost-governance/</guid><description>一套完整的 Kubernetes FinOps 落地路径：如何识别僵尸资源、配置成本分摊模型、利用 Karpenter 降低节点成本，以及如何将月账单从 $50k 压到 $30k。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/finops-kubernetes-cost-governance/featured.jpg"/></item><item><title>Karpenter 弹性节点管理实战</title><link>https://socake.github.io/docs/kubernetes/karpenter-%E5%BC%B9%E6%80%A7%E8%8A%82%E7%82%B9/</link><pubDate>Mon, 08 Dec 2025 13:00:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/docs/kubernetes/karpenter-%E5%BC%B9%E6%80%A7%E8%8A%82%E7%82%B9/</guid><description>Karpenter 替代 Cluster Autoscaler 的完整实践：NodePool 约束配置、EC2NodeClass 实例选型、consolidation 节点整合降本、Spot 实例容错，以及多套集群配置的组织方式。</description></item><item><title>Kubernetes 成本优化实战：系统性降本的四条路径</title><link>https://socake.github.io/posts/k8s-%E6%88%90%E6%9C%AC%E4%BC%98%E5%8C%96%E5%AE%9E%E6%88%98/</link><pubDate>Mon, 18 Aug 2025 13:07:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/k8s-%E6%88%90%E6%9C%AC%E4%BC%98%E5%8C%96%E5%AE%9E%E6%88%98/</guid><description>真实的降本案例：从发现成本异常到分析根因，通过 Karpenter 节点弹性伸缩、资源请求规格治理、大机型收敛等手段，系统性降低 AWS EC2 成本。包含具体配置和执行思路。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/k8s-%E6%88%90%E6%9C%AC%E4%BC%98%E5%8C%96%E5%AE%9E%E6%88%98/featured.jpg"/></item><item><title>Karpenter 深度解析：下一代 K8s 节点自动扩缩</title><link>https://socake.github.io/posts/karpenter-deep-dive/</link><pubDate>Wed, 11 Jun 2025 11:33:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/karpenter-deep-dive/</guid><description>从 Cluster Autoscaler 迁移到 Karpenter 之后，集群扩容速度和节点利用率都有明显提升。本文详细拆解 Karpenter 的核心机制、关键配置项，以及在多套生产集群运行中踩过的坑。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/karpenter-deep-dive/featured.jpg"/></item></channel></rss>