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LICENSE

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README.md

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# Kubectl-debug
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> Pod debugging made easy
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![license](https://img.shields.io/hexpm/l/plug.svg)
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[![travis](https://travis-ci.org/aylei/kubectl-debug.svg?branch=master)](https://travis-ci.org/aylei/kubectl-debug)
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[![Go Report Card](https://goreportcard.com/badge/github.com/aylei/kubectl-debug)](https://goreportcard.com/report/github.com/aylei/kubectl-debug)
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[![docker](https://img.shields.io/docker/pulls/aylei/debug-agent.svg)](https://hub.docker.com/r/aylei/debug-agent)
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`kubectl-debug` is an out-of-tree solution for [troubleshooting running pods](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/node/troubleshoot-running-pods.md), which allows you to run new containers in running pod for debugging purpose. `kubectl-debug` is pretty simple and capable for all versions* of k8s.
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[中文文档](./docs/zh-cn.md)
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`*`: I've tested `kubectl-debug` with kubectl version v1.13.1 and kubernetes version v1.9.1. I don't have an environment to test more versions but I suppose that `kubectl-debug` is compatible with all versions of kubernetes and kubectl 1.12.0 or higher. Please [file an issue] if you find `kubectl-debug` do not work.
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`kubectl-debug` is an out-of-tree solution for [troubleshooting running pods](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/node/troubleshoot-running-pods.md), which allows you to run a new container in running pods for debugging purpose. The new container will join the `pid`, `network`, `user` and `ipc` namespaces of the target container, so you can use arbitrary trouble-shooting tools without pre-install them in your production container image.
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> Compatibility: I've tested `kubectl-debug` with kubectl v1.13.1 and kubernetes v1.9.1. I don't have an environment to test more versions but I suppose that `kubectl-debug` is compatible with all versions of kubernetes and kubectl 1.12.0+. Please [file an issue](https://github.com/aylei/kubectl-debug/issues/new) if you find `kubectl-debug` do not work.
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# Quick Start
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WIP
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Install the debug agent DaemonSet in your cluster, which is responsible to run the "new container":
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```bash
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kubectl apply -f https://raw.githubusercontent.com/aylei/kubectl-debug/master/scripts/agent_daemonset.yml
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```
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Install the kubectl debug plugin:
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```bash
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curl
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```
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Try it out!
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```bash
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kubectl debug POD_NAME
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# learn more with
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kubectl debug -h
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```
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# TODO
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# Default image and entrypoint
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- [ ] DaemonSet YAML and helm chart for agent
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`kubectl-debug` use [nicolaka/netshoot](https://github.com/nicolaka/netshoot) as the default image to run debug container, and use `bash` as default entrypoint.
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nice to have:
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You can override the default image and entrypoint with cli flag, or even better, with config file `~/.kube/debug-config`:
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- [ ] bash completion
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- [ ] `kubectl debug list`: list debug containers, we might need this because the debug container is not discovered by kubernetes.
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- [ ] security: security is import, but not a consideration in current stage
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```yaml
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agent_port: 10027
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image: nicolaka/netshoot:latest
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command:
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- '/bin/bash'
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- '-l'
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```
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# Design
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PS: `kubectl-debug` will always override the entrypoint of the container, which is by design to avoid users running an unwanted service by mistake(of course you can always do this explicitly).
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# Details
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`kubectl-debug` consists of 2 components:
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8. Jobs done, user close the SPDY connection.
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9. The node agent close the SPDY connection, then wait the `debug contaienr` exit and do the cleanup.
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# Reference
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[sample-cli-plugin](https://github.com/kubernetes/sample-cli-plugin)
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# Contribute
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[docker api](https://godoc.org/github.com/docker/docker/client)
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Feel free to open issues and pull requests. Any feedback will be highly appreciated!

docs/zh-cn.md

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# Kubectl debug
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`kubectl-debug` 是一个简单的 kubectl 插件, 能够帮助你便捷地进行 Kubernetes 上的 Pod 排障诊断. 背后做的事情很简单: 在运行中的 Pod 上额外起一个新容器, 并将新容器加入到目标容器的 `pid`, `network`, `user` 以及 `ipc` namespace 中, 这时我们就可以在新容器中直接用 `netstat`, `tcpdump` 这些熟悉的工具来解决问题了, 而旧容器可以保持最小化, 不需要预装任何额外的排障工具.
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# Quick Start
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`kubectl-debug` 包含两部分, 一部分是用户侧的 kubectl 插件, 另一部分是部署在所有 k8s 节点上的 agent(用于启动"新容器", 同时也作为 SPDY 连接的中继). 因此首先要部署 agent.
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推荐以 DaemonSet 的形式部署:
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```bash
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kubectl apply -f https://raw.githubusercontent.com/aylei/kubectl-debug/master/scripts/agent_daemonset.yml
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```
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接下来, 安装 kubectl 插件:
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装完之后就可以试试看了:
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```bash
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kubectl debug POD_NAME
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# learn more with
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kubectl debug -h
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```
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# 默认镜像和 Entrypoint
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`kubectl-debug` 使用 [nicolaka/netshoot](https://github.com/nicolaka/netshoot) 作为默认镜像. 默认镜像和指令都可以通过命令行参数进行覆盖. 考虑到每次都指定有点麻烦, 也可以通过文件配置的形式进行覆盖, 编辑 `~/.kube/debug-config` 文件:
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```bash
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agent_port: 10027
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image: nicolaka/netshoot:latest
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command:
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- '/bin/bash'
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- '-l'
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```
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> `kubectl-debug` 会将容器的 entrypoint 直接覆盖掉, 这是为了避免在 debug 时不小心启动非 shell 进程.
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# 实现细节
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主要参照了 `kubectl exec` 的实现, 但 `exec` 要复杂很多, `debug` 的链路还是很简单的:
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1. 根据指令找到 Pod 的 HostIP, 以及目标容器的 ContainerID
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2. 对 HostIP 上的 agent 发起 http 请求, 请求会携带上 image, command 这些参数
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3. agent 返回一个协议升级响应, 在 client 与 agent 之间建立 SPDY 连接
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4. agent 确认目标容器是否正常运行, 若否, 返回一个错误
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5. agent 启动一个新容器, 加入到目标容器的 `pid`, `network`, `ipc` 以及 `user` namespace 中
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6. 容器启动完成后, agent 将 server 侧 SPDY 的 stdin, stdout, tty 绑定到新容器的 stdin, stdout 和 tty 上
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7. 一切就绪, 可以开始 debug 了
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8. debug 完毕, 关闭连接, agent 做一些清理操作, 关闭并移除容器

pkg/agent/runtime.go

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}
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defer out.Close()
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// write pull progress to user
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term.DisplayDockerJsonStream(out, stdout)
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term.DisplayJSONMessagesStream(out, stdout, 1, true, nil)
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return nil
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}
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