docker常用指令

一、目录

1. docker 指令
   1. 创建镜像
   2. 保存镜像
   3. 加载镜像
   4. 删除容器
   5. 删除镜像
   6. 查看容器日志
   7. 查看docker 占用内存情况
   8. 查看docker 根目录(安装路径)
   9. 创建一个容器

二、实现

1. docker指令
   1 创建镜像

   docker commit  fd69960ed65f  jyf：0.0.1

2. 保存镜像

   docker save -o my.tar hello-word:latest

3. 加载镜像

   docker load -i my.tar

4. 删除容器

   docker rm CONTAINER-ID #删除容器id, 或者>>docker rm name #容器名字
   批量删除
   docker rm $(docker ps -a -q)

5. 删除镜像

   docker rmi image-id #删除镜像id

6. 查看容器日志

   docker logs CONTAINER-ID #容器id

7. 查看docker 占用内存情况

   [root@localhost ~]# docker system df
   TYPE TOTAL ACTIVE SIZE RECLAIMABLE
   Images 81 41 37.12GB 18.87GB (50%)
   Containers 58 18 33.98GB 32.39GB (95%)
   Local Volumes 42 25 1.598GB 1.492GB (93%)
   Build Cache 130 0 562.7MB 562.7MB

8. 查看docker 根目录(安装路径)

root@dockermain \~\]# docker info Client: Docker Engine - Community Version: 24.0.1 Context: default Debug Mode: false Plugins: buildx: Docker Buildx (Docker Inc.) Version: v0.10.4 Path: /usr/libexec/docker/cli-plugins/docker-buildx compose: Docker Compose (Docker Inc.) Version: v2.18.1 Path: /usr/libexec/docker/cli-plugins/docker-compose scan: Docker Scan (Docker Inc.) Version: v0.23.0 Path: /usr/libexec/docker/cli-plugins/docker-scan Server: Containers: 58 Running: 21 Paused: 0 Stopped: 37 Images: 141 Server Version: 24.0.1 Storage Driver: overlay2 Backing Filesystem: xfs Supports d_type: true Using metacopy: false Native Overlay Diff: true userxattr: false Logging Driver: json-file Cgroup Driver: systemd Cgroup Version: 2 Plugins: Volume: local Network: bridge host ipvlan macvlan null overlay Log: awslogs fluentd gcplogs gelf journald json-file local logentries splunk syslog Swarm: inactive Runtimes: io.containerd.runc.v2 runc Default Runtime: runc Init Binary: docker-init containerd version: 3dce8eb055cbb6872793272b4f20ed16117344f8 runc version: v1.1.7-0-g860f061 init version: de40ad0 Security Options: seccomp Profile: builtin cgroupns Kernel Version: 5.14.0-284.11.1.el9_2.x86_64 Operating System: AlmaLinux 9.2 (Turquoise Kodkod) OSType: linux Architecture: x86_64 CPUs: 16 Total Memory: 31.09GiB Name: dockermain ID: b1b354b2-ccd6-4204-9c1d-78ca30da0712 Docker Root Dir: /home/dockerdata #根目录 Debug Mode: false Experimental: false Insecure Registries: 10.120.130.49:5000 127.0.0.0/8 Registry Mirrors: http://hub-mirror.c.163.com/ Live Restore Enabled: false

9. 创建一个容器

   镜像选取：docker pull pytorch/pytorch:1.9.1-cuda11.1-cudnn8-devel
   docker run -it --gpus '"device=1,2"' --name leinao -v /tmp:/tmp pytorch/pytorch:pytorch:1.9.1-cuda11.1-cudnn8-devel /bin/bash
   docker run -it --gpus '"device=2,3"' -v /jiayafei_linux/:/home/ --name llm_g pytorch/pytorch:2.1.0-cuda12.1-cudnn8-devel /bin/bash

   docker run -it --gpus '"device=0"' -v /jiayafei_linux/:/home/ --name nodes_0 -p8201:8010 pytorch/pytorch:2.1.0-cuda12.1-cudnn8-devel /bin/bash
   docker run -it --gpus '"device=1"' -v /jiayafei_linux/:/home/ --name nodes_1 -p8202:8010 pytorch/pytorch:2.1.0-cuda12.1-cudnn8-devel /bin/bash

   docker run -it --gpus all --name llm-01 -v /:/home -p8011:8011 -p8012:8012 -p8013:8013 -p8014:8014 pytorch/pytorch:2.1.0-cuda12.1-cudnn8-devel /bin/bash