<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:media="http://search.yahoo.com/mrss/"><channel><title>Practice on Shaowen Chen's Website</title><link>https://www.chenshaowen.com/en/tags/practice/</link><description>Recent content in Practice on Shaowen Chen's Website</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>&amp;copy;2016 - {year}, All Rights Reserved.</copyright><lastBuildDate>Mon, 05 Feb 2024 00:00:00 +0000</lastBuildDate><sy:updatePeriod>weekly</sy:updatePeriod><atom:link href="https://www.chenshaowen.com/en/tags/practice/atom.xml" rel="self" type="application/rss+xml"/><item><title>A Practical Guide to kind</title><link>https://www.chenshaowen.com/en/blog/practice-guide-to-kind.html</link><pubDate>Mon, 05 Feb 2024 00:00:00 +0000</pubDate><atom:modified>Mon, 05 Feb 2024 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/practice-guide-to-kind.html</guid><description>1. Project Overview kind is a tool for managing Kubernetes clusters using containers. Project address https://github.com/kubernetes-sigs/kind .
It is mainly used for:
Local development environments Temporary environments for learning Automated testing 2. Installing kind macOS 1 brew install kind Linux 1 2 curl -Lo /usr/local/bin/kind https://kind.sigs.k8s.io/dl/v0.21.0/kind-linux-amd64 chmod +x /usr/local/bin/kind 3. Creating a kind Cluster If you have a PROXY configured locally, it is recommended to reset the environment variables before creating:</description><dc:creator>微信公众号</dc:creator><category>Kubernetes</category><category>kind</category><category>Practice</category><category>Operations</category></item><item><title>Distributing Cluster Images with Dragonfly V2</title><link>https://www.chenshaowen.com/en/blog/distributing-image-with-dragonfly-v2.html</link><pubDate>Sat, 13 Jan 2024 11:22:55 +0000</pubDate><atom:modified>Sat, 13 Jan 2024 11:22:55 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/distributing-image-with-dragonfly-v2.html</guid><description>1. Introduction to Dragonfly The Dragonfly documentation at https://d7y.io/zh/docs/ already covers things in detail. Here is just a brief introduction to the main components of V2:
Manager, which provides the UI, user management, cluster monitoring, task management, and other features Scheduler, which schedules traffic between Peers and provides preheating and other features Seed Peer, the back-to-source node used to download data from origin sites (Harbor, Docker.</description><dc:creator>微信公众号</dc:creator><category>AI</category><category>Dragonfly</category><category>Kubernetes</category><category>Images</category><category>Image</category><category>Nydus</category><category>Configuration</category><category>Practice</category><category>Operations</category></item><item><title>Nydus Lazy-Loading Image Configuration and Practice</title><link>https://www.chenshaowen.com/en/blog/nydus-configuration-and-practice.html</link><pubDate>Sat, 06 Jan 2024 11:22:55 +0000</pubDate><atom:modified>Sat, 06 Jan 2024 11:22:55 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/nydus-configuration-and-practice.html</guid><description>Statistics show that most files inside a container are never used. Based on this characteristic, Nydus defines a custom filesystem in the Rafs format, enabling on-demand loading of image files to solve the slow startup and storage consumption caused by large images. In AI scenarios, whether for inference or training, images often start at several GB, or even tens of GB, so Nydus is very well suited.</description><dc:creator>微信公众号</dc:creator><category>AI</category><category>Nydus</category><category>Docker</category><category>Images</category><category>Configuration</category><category>Practice</category><category>Operations</category></item><item><title>Integrating GPT Services into WeChat and Official Accounts</title><link>https://www.chenshaowen.com/en/blog/how-to-access-gpt-service-on-wechat.html</link><pubDate>Tue, 26 Dec 2023 00:00:00 +0000</pubDate><atom:modified>Tue, 26 Dec 2023 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/how-to-access-gpt-service-on-wechat.html</guid><description>Paid integration service available at 200 RMB/year; technical support is also available at 200 RMB per session, capped at 1 hour. Follow the official account to get contact details. 1. Information You Need to Provide Go to https://mp.weixin.qq.com/ and open 【Settings and</description><dc:creator>微信公众号</dc:creator><category>LLM</category><category>GPT</category><category>Official Account</category><category>WeChat</category><category>AI</category><category>R&amp;D</category><category>Learning</category><category>Integration</category><category>OpenAI</category><category>Practice</category></item><item><title>Chaos Engineering and Putting It into Practice</title><link>https://www.chenshaowen.com/en/blog/chaos-engineering-and-practice.html</link><pubDate>Sat, 16 Dec 2023 11:15:11 +0000</pubDate><atom:modified>Sat, 16 Dec 2023 11:15:11 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/chaos-engineering-and-practice.html</guid><description>Two months ago, I gave a talk to a business team about chaos engineering in practice. This post mainly organizes the content of that talk.
Click to view the presentation
1. The Origin of Chaos 1.1 The Birth of the Discipline of Chaos Before discussing chaos, let us first think about the relationship between chaos, chaos engineering, and our production services.</description><dc:creator>微信公众号</dc:creator><category>Chaos</category><category>Practice</category><category>Process</category><category>Conventions</category><category>Chaos Engineering</category><category>Operations</category><category>Reliability</category><category>Learning</category><category>Fault Drills</category></item><item><title>Common Commands for Cleaning Up Kubernetes Cluster Resources</title><link>https://www.chenshaowen.com/en/blog/common-commands-for-cleaning-up-kubernetes-cluster-resources.html</link><pubDate>Wed, 08 Dec 2021 00:00:00 +0000</pubDate><atom:modified>Wed, 08 Dec 2021 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/common-commands-for-cleaning-up-kubernetes-cluster-resources.html</guid><description>Clusters that run for a long time often face various kinds of resource exhaustion. On top of that, when disk space runs low, Kubelet will proactively clean up images on its own, adding another source of uncertainty. This article provides some command snippets for cleanup work.
1. Cleaning Up Basic Kubernetes Objects Clean up Pods in Evicted state 1 sudo kubectl get pods --all-namespaces -o wide | grep Evicted | awk &amp;#39;{print $1,$2}&amp;#39; | sudo xargs -L1 kubectl delete pod -n Clean up Pods in Error state 1 sudo kubectl get pods --all-namespaces -o wide | grep Error | awk &amp;#39;{print $1,$2}&amp;#39; | sudo xargs -L1 kubectl delete pod -n Clean up Pods in Completed state 1 sudo kubectl get pods --all-namespaces -o wide | grep Completed | awk &amp;#39;{print $1,$2}&amp;#39; | sudo xargs -L1 kubectl delete pod -n Clean up unused PVs 1 sudo kubectl describe -A pvc | grep -E &amp;#34;^Name:.</description><dc:creator>微信公众号</dc:creator><category>Kubernetes</category><category>Practice</category><category>Cleanup</category><category>Operations</category><category>Learning</category><category>kubectl</category><category>Troubleshooting</category><category>Resource Management</category></item><item><title>Kubernetes Complex Stateful Application Management Framework -- Operator</title><link>https://www.chenshaowen.com/en/blog/complex-application-management-framework-operator-for-kubernetes.html</link><pubDate>Thu, 25 Jul 2019 00:00:00 +0000</pubDate><atom:modified>Thu, 25 Jul 2019 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/complex-application-management-framework-operator-for-kubernetes.html</guid><description>1. Origins Originally, two CoreOS employees, in order to make deploying etcd clusters easier, bound corresponding logical operations to the create, delete, and update events of the etcdCluster object, using Kubernetes to automate etcd cluster management.
A few months later, at a KubeCon conference, they shared this approach, which they called Operator, and it received a strong response from the community.</description><dc:creator>微信公众号</dc:creator><category>Kubernetes</category><category>Helm</category><category>Practice</category><category>Operator</category><category>Operations</category><category>Stateful Applications</category><category>Learning</category></item><item><title>Kubernetes' Package Manager -- Helm</title><link>https://www.chenshaowen.com/en/blog/package-manager-helm-of-kubernetes.html</link><pubDate>Wed, 24 Jul 2019 00:00:00 +0000</pubDate><atom:modified>Wed, 24 Jul 2019 00:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/package-manager-helm-of-kubernetes.html</guid><description>1. Why Helm Is Needed One important design philosophy in Kubernetes is declarative operation. Users change the system by setting the system&amp;rsquo;s expected state. For example, the current replica count is 2 and it needs to be adjusted to 3. The declarative way is to modify the replica count in</description><dc:creator>微信公众号</dc:creator><category>Kubernetes</category><category>Helm</category><category>Practice</category><category>Operations</category><category>Package Management</category><category>Learning</category><category>Chart</category><category>Deployment</category></item><item><title>A Practical Guide to kubectl</title><link>https://www.chenshaowen.com/en/blog/practice-guide-to-kubectl.html</link><pubDate>Fri, 19 Jul 2019 01:00:00 +0000</pubDate><atom:modified>Fri, 19 Jul 2019 01:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/practice-guide-to-kubectl.html</guid><description>1. What Is kubectl kubectl is the command-line tool for Kubernetes. It interacts with the cluster through the API server.
2. Configuring kubectl kubectl can be configured through ~/.kube/config to connect to one or more clusters.
For details on how to configure it, see: Configure Access to Multiple Clusters. If you need to configure a remote cluster, see: Building a Remote Kubernetes Development Environment.</description><dc:creator>微信公众号</dc:creator><category>Kubernetes</category><category>kubectl</category><category>Practice</category><category>Learning</category><category>Operations</category></item></channel></rss>