Docker入门

Docker简介

 Docker是开发人员和系统管理员构建、发布和运行分布式应用程序的开放平台。是应用容器（Application Container），是可以为应用提供可运行容器的一个平台。Docker看作一条船，船上的每一个集装箱就是一个容器(每个容器中都有一个Linux系统)。

Docker还有一重要的用处，就是可以保证开发，测试和生产环境的一致。

1、Docker安装

安装一组工具

sudo yum install -y yum-utils

设置 yum 仓库地址，设置2个仓库地址，一个失败会使用另外一个仓库。

sudo yum-config-manager --add-repo https://download.docker.com/linux/centos/docker-ce.repo
    
sudo yum-config-manager --add-repo http://mirrors.aliyun.com/docker-ce/linux/centos/docker-ce.repo

更新 yum 缓存

sudo yum makecache fast

安装新版 docker

sudo yum install -y docker-ce docker-ce-cli containerd.io

2、Docker入门

启动docker

sudo systemctl start docker

重启docker

sudo systemctl restart docker

设置 docker 开机启动

sudo systemctl enable docker

镜像加速

由于国内网络问题，需要配置加速器来加速。
修改配置文件：vi /etc/docker/daemon.json

{
	"registry-mirrors": [
		"https://docker.mirrors.ustc.edu.cn",
		"http://hub-mirror.c.163.com"
	],
	"max-concurrent-downloads": 10,
	"log-driver": "json-file",
	"log-level": "warn",
	"log-opts": {
		"max-size": "10m",
		"max-file": "3"
	},
	"data-root": "/var/lib/docker"
}

重新加载docker配置

sudo systemctl daemon-reload

重启docker服务

sudo systemctl restart docker

查看镜像配置

docker info

可以看到上面配置的仓库地址已经修为https://docker.mirrors.ustc.edu.cn/

运行 hello-world 镜像，当没有hello-world这个镜像，他会到我们设置的仓库地址去下载这个镜像。

sudo docker run hello-world

检查docker 镜像

docker images

 发现有一个hello-world，是上面运行后，本地没有，然后去仓库中下载的。

#查看正在运行的容器
docker ps

假如希望查看所有镜像，包含没有运行的镜像容器，可以执行如下指令：

docker ps -all

停止docker服务

docker stop 服务id

 删除docker 镜像

docker image rm hello-world

假如镜像被占用着是不可以直接被删除的，需要先删除应用此镜像的容器，例如

#查询容器
docker ps -all
#删除容器
docker container rm 容器名或容器id

3、概念

镜像(可以认为是一个容器的可执行文件，可以使用docker命令执行启动，启动后就是容器)

Docker 镜像是一个特殊的文件系统，就是容器的运行文件，除了提供容器运行时所需的程序、库、资源、配置等文件外，还包含了一些为运行时准备的一些配置参数（如匿名卷、环境变量、用户等）。镜像不包含任何动态数据，其内容在构建之后也不会被改变。

镜像只是一个虚拟的概念，其实际体现并非由一个文件组成，而是由一组文件系统组成，或者说，由多层文件系统联合组成。

镜像构建时，会一层层构建，前一层是后一层的基础。每一层构建完就不会再发生改变，后一层上的任何改变只发生在自己这一层。比如，删除前一层文件的操作，实际不是真的删除前一层的文件，而是仅在当前层标记为该文件已删除。在最终容器运行的时候，虽然不会看到这个文件，但是实际上该文件会一直跟随镜像。因此，在构建镜像的时候，需要额外小心，每一层尽量只包含该层需要添加的东西，任何额外的东西应该在该层构建结束前清理掉。

分层存储的特征还使得镜像的复用、定制变的更为容易。甚至可以用之前构建好的镜像作为基础层，然后进一步添加新的层，以定制自己所需的内容，构建新的镜像。

从仓库拉取镜像

docker pull 镜像名称
或者
docker pull 镜像名称:版本号

查看有哪些镜像

docker images

删除镜像

docker image rm 镜像id

 如果镜像已经执行启动成一个容器，需要先删除这个容器。

启动运行镜像，启动后就是一个容器。

docker run -it xxxx bash

 -d: 后台运行容器，并返回容器ID。
-it:在伪输入终端以交互模式运行容器。-i交互，-t终端。
-p:指定端口映射，格式为：主机(宿主)端口:容器端口
-v 用于指定挂载目录,格式为：宿主机目录:容器目录

--restart always  设置容器随宿主机的开机而自启动
-p 80:80 指端口映射，访问宿主机端口80，相当于访问的是nginx容器的80端口，
--name 给容器设置一个名字，若没有设置默为镜像名。
-v 指挂载，比如将 宿主机目录/usr/local/nginx/挂载到容器目录/etc/nginx/
-d 后台运行 
nginx:1.22.0 要运行的容器名:版本号
 

一般运行镜像时，需要挂载主机目录，防止停止运行后数据丢失 

docker run -it -v /usr/app:/opt/app centos:7 bash

 将宿主机目录/usr/app挂载到容器的/opt/app目录

其中：
1)/usr/app：为宿主机目录
2)/opt/app: 为启动容器的一个目录
3)-v 用于指定挂载目录，如果本地目录(宿主机目录)不存在， Docker 会自动为你按照挂载目录进行目录的创建。

镜像导出 

docker save jdk:8 | gzip > /root/jdk8.tar.gz

 镜像导入

docker load < /root/jdk8.tar.gz

容器（每个容器中都有一个独立的Linux操作系统）

镜像（Image）和容器（Container）的关系，就像是光盘和光驱，容器是镜像运行时的载体，镜像运行启动后就是一个容器。容器可以被创建、启动、停止、删除、暂停等。

容器的本质是进程，但与直接在宿主机执行的进程不同，容器进程运行于属于自己的独立的 命名空间。因此容器可以拥有自己的 root 文件系统、自己的网络配置、自己的进程空间，甚至自己的用户 ID 空间。容器内的进程是运行在一个隔离的环境里，使用起来，就好像是在一个独立于宿主的系统下操作一样。这种特性使得容器封装的应用比直接在宿主运行更加安全。

 镜像文件启动后就是一个容器，容器里面有操作系统、有组件，启动容器的时候默认还会执行一个命令，让组件在操作系统中运行。

docker history 镜像id或者镜像名

 可以看到容器启动后，会在容器的操作系统中执行 catalina.sh 命令，这个命令就会启动tomcat组件。

docker container xx 命令  可以简写为 docker xx 

查看正在运行的镜像容器

docker ps

查看所有镜像容器，包含没有运行的镜像容器

docker ps -all

进入指定容器，退出exit

sudo docker exec -it 容器id或者容器名 bash

 停止镜像容器

docker container stop 容器id或者容器名
或者
docker stop 容器id或者容器名

启动镜像容器

docker container start 容器id或者容器名
或者
docker start 容器id或者容器名

 设置容器开机自启动

docker update 容器名或容器id --restart=always

重启容器

docker container restart 容器名或容器id
或者
docker restart 容器名或容器id

查看容器安装到哪了?

whereis 容器名或容器id

查看容器启动时的日志

docker container logs 容器名或容器id

删除镜像容器

docker container rm 容器名或容器id

强制删除容器

docker rm -f 容器名或容器id

清除那些已经没有使用的容器

docker container prune

 后台执行容器里的 jar包，因为容器不能直接访问宿主机里面的目录，还需要挂载一个目录。

docker run -dit -p 宿主机端口:容器端口 -v 宿主机目录:容器目录 容器名 java -jar 要运行的jar包路径
#例如
docker run -dit -p 8081:8081 -v /root:/root jdk:8 java -jar /root/xx.jar

容器打包镜像

docker commit -m="描述信息" -a="作者" 容器id 目标镜像名:[TAG]

docker commit -m="描述信息" -a="作者" b6ef283d6a47 myjdk:88

 

数据卷

镜像使用的是分层存储方式，容器也是如此。每一个容器运行时，是以镜像为基础层，在其上创建一个当前容器的存储层(我们可以称这个为容器运行时执行读写操作而准备的存储层)
容器存储层的生存周期和容器一样，容器消亡时，容器存储层也随之消亡。因此，任何保存于容器存储层的信息都会随容器删除而丢失。
按照 Docker 最佳实践的要求，容器不应该向其存储层内写入任何数据，容器存储层要保持无状态化。所有的文件写入操作，都应该使用 数据卷（Volume）、或者绑定宿主目录，在这些位置的读写会跳过容器存储层，直接对宿主（或网络存储）发生读写，其性能和稳定性更高。
数据卷的生存周期独立于容器，容器消亡，数据卷不会消亡。因此，使用数据卷后，容器删除或者重新运行之后，数据却不会丢失。数据卷是一个可供一个或多个容器使用的特殊目录。默认会一直存在，即使容器被删除。也是存储在宿主机上。

就是说容器是一个独立的操作系统，当容器消失后，容器这个操作系统也消失了，里面的数据文件比如web的日志也没了，为了解决这个问题，使用数据卷或者将容器操作系统的数据文件挂载在宿主目录，这样好处就是容器消亡，数据文件不会消亡。

#创建数据卷
docker volume create 数据卷名称
#查看所有数据卷
docker volume ls
#查看指定 数据卷 的信息
docker volume inspect 数据卷名称
 
#启动挂载数据卷的容器
docker run -it --mount source=数据卷名称,target=/root centos:7 bash
# 或者：
docker run -it -v 数据卷名称:/root centos:7 bash
 
-v container-vol:/root 把数据卷 container-vol 挂载到容器的 /root 目录
 
#删除数据卷(如果数据卷被容器使用则无法删除)
docker volume rm 数据卷名称
 
#清理无主数据卷
docker volume prune

挂载主机目录（常用）

作用和数据卷差不多

docker run -it -v /usr/app:/opt/app centos:7 bash

其中：
1)/usr/app：为宿主机目录
2)/opt/app: 为启动容器的一个目录
3)-v 用于指定挂载目录，如果本地目录(宿主机目录)不存在， Docker 会自动为你按照挂载目录进行目录的创建。

查看挂载目录信息

docker inspect 容器名或容器id

4、Docker镜像操作

下载 Docker镜像，其实就是下载一个CentOS 镜像。

假如是自己制作镜像，都会先下载一个空的centos镜像,假如后面我们要自己做镜像，都需要这样的一个空的系统镜像文件。

冒号:7表示指定版本。

docker pull centos:7

查看centos7镜像文件

docker images

运行镜像

通过docker启动运行 centos7镜像

docker run -it xxxx bash

xxxx - 镜像名, 或 image id 
-it 这是两个参数，一个是 -i：交互式操作，一个是 -t 终端。-d表示后台运行。我们这里打算进入 bash 执行一些命令并查看返回结果，因此我们需要交互式终端。
bash 放在镜像名后的是命令，这里我们希望有个交互式 Shell，因此用的是 bash。

比如通过名字启动：docker run -it centos:7 bash
比如通过image id启动：docker run -it eeb6ee3f44bd bash

 

 可以看到，启动容器以后，直接就进入了容器系统这个操作系统中了。

后面的操作，其实就是在容器系统这个操作系统中操作了，exit退出，就会退出容器那个操作系统，回到宿主系统中。

5、数据卷操作（了解）

创建数据卷

docker volume create container-vol

查看所有数据卷

docker volume ls

查看指定 数据卷 的信息

docker volume inspect container-vol

启动挂载数据卷的容器

docker run -it --mount source=container-vol,target=/root centos:7 bash

简写：

docker run -it -v container-vol:/root centos:7 bash

 -v container-vol:/root 把数据卷 container-vol 挂载到容器的 /root 目录

 删除数据卷(如果数据卷被容器使用则无法删除)

docker volume rm container-vol

清理无主数据卷（就是把数据卷在宿主机上的目录给删除了，比如上面的/var/lib/docker/volumes/container-vol/_data）

docker volume prune

6、挂载主机目录（常用）

docker run -it -v /usr/app:/opt/app centos:7 bash

其中：
1)/usr/app：为宿主机目录
2)/opt/app: 为启动容器的一个目录

3)-v 用于指定挂载目录，如果本地目录(宿主机目录)不存在， Docker 会自动为你按照挂载目录进行目录的创建。

比如将宿主机目录/usr/local/docker/test挂载到容器的/root目录

docker run -it -v /usr/local/docker/test:/root centos:7 bash

查看挂载目录信息

docker ps -all
docker inspect  容器id

 

 7、镜像制作-Dockerfile文件

Dockerfile 是一个用来构建镜像的文本文件,文本内容包含了一条条构建镜像所需的指令和说明。我们通常会基于此文件创建docker镜像。

准备工作

1)centos:7镜像 (所有的镜像文件创建时都需要有一个空的centos镜像，就类似通过一个空的光盘或u盘创建一个系统启动盘是一样的)

docker pull centos:7

2)jdk压缩包jdk-8u311-linux-x64.tar.gz(可以从官网去下载:oracle.org)，基于此压缩包，制作jdk镜像。

Dockerfile文件
在创建新的镜像时都需要有一个Dockerfile文件(文件名一定要注意大小写)，这个文件要与你的资源放在一起(例如你下载的jdk)

编辑Dockerfile文件

vi Dockerfile

FROM centos:7
ADD jdk-8u311-linux-x64.tar.gz /usr/local/docker
ENV JAVA_HOME=/usr/local/docker/jdk1.8.0_311 \
    PATH=/usr/local/docker/jdk1.8.0_311/bin:$PATH
CMD ['bash']

编写FROM语句(关键字一定要大写，例如FROM不能写小写)
FROM centos:7
通过ADD命令将宿主机中的压缩包传入镜像容器中的指定目录,并同时解压缩
ADD jdk-8u311-linux-x64.tar.gz /usr/local/docker
设置环境变量(通过ENV关键字实现，目录启动容器中的目录) 注意：\表示换行。:$PATH表示保留以前的path
ENV JAVA_HOME=/usr/local/docker/jdk1.8.0_311 \
    PATH=/usr/local/docker/jdk1.8.0_311/bin:$PATH
指定命令行操作(所有指令与后面内容要有空格)
CMD ['bash']

使用 Dockerfile 构建镜像(在Dockerfile所在目录执行docker指令)

docker build -t jdk:8 .

注意末尾的点,表示构建过程中从当前目录寻找文件，jdk:8为我们创建的镜像名。

我们制作的这个镜像，依赖了一个空白的centos:7镜像，所以我们制作的jdk:8镜像是已经包含了centos:7镜像。

8、运行镜像文件 

docker run -it jdk:8 bash

java -version 

也可以不进入 bash ，直接运行 java version命令

docker run -it jdk:8 java -version

 

9、镜像导出导入操作

镜像导出，导出后给他人使用

docker save jdk:8 | gzip > /root/jdk8.tar.gz

镜像导入

docker load < /root/jdk8.tar.gz

 或者

docker load -i /root/jdk8.tar.gz

 

Docker 镜像资源安装

安装MySql数据库

在https://hub.docker.com/上搜索 mysql 镜像

 拉取版本指定版本mysql

docker pull mysql:8.0.23

 启动运行mysql镜像

docker run -p 3307:3306 --name mysql \
-v /usr/local/mysql/mysql-files:/var/lib/mysql-files \
-v /usr/local/mysql/conf:/etc/mysql \
-v /usr/local/mysql/logs:/var/log/mysql \
-v /usr/local/mysql/data:/var/lib/mysql \
-e MYSQL_ROOT_PASSWORD=root \
-d mysql:8.0.23

-p 3307:3306 指端口映射，访问宿主机端口3307，相当于访问的是mysql容器的3306端口，
--name 给容器设置一个名字，若没有设置默为镜像名。
-v 指挂载，比如将 宿主机目录/usr/local/docker/mysql/mysql-files挂载到容器目录/var/lib/mysql-files
-e 给mysql设置密码为root
-d 后台运行 
mysql:8.0.23 要运行的容器名:版本号

#停止mysql服务
docker stop mysql
 
#启动mysql服务
docker start mysql
 
#设置mysql开机自启动
docker update mysql --restart=always

查看正则运行的容器

docker ps

 进入容器 (退出容器用exit)

sudo docker exec -it mysql bash

登陆mysql(上面设置的密码为root)

mysql -uroot -proot

 外部连接mysql

#创建mysql账户。用户名和密码都是tony
create user 'tony'@'%' identified by 'tony';
#授权
grant all on *.* to 'tony'@'%'

出现Plugin caching_sha2_password could not be load错误（出现这个错误往往与数据库的版本有关系,mysql8.0以后改变对远程客户端的校验方式）分别执行如下三个指令 

ALTER USER 'tony'@'%' IDENTIFIED BY 'tony' PASSWORD EXPIRE NEVER;
ALTER USER 'tony'@'%' IDENTIFIED WITH mysql_native_password BY 'tony'; 
FLUSH  PRIVILEGES; 

 开启宿主机端口3307

#开启端口3307
firewall-cmd --permanent --add-port=3307/tcp
#重启防火墙是修改生效
firewall-cmd --reload
#查询有哪些端口是开启的
firewall-cmd --list-port

安装Nacos

在https://hub.docker.com/上搜索 nacos镜像

 拉取指定版本nacos

docker pull nacos/nacos-server:1.4.1

​在nacos官网https://github.com/alibaba/nacos/releases下载nacos-server.zip后解压，需要根据conf/nacos-mysql.sql创建nacos需要用到的数据库和表结构。
GitHub网速不好点这里下载https://download.csdn.net/download/u014644574/86730745

由于上面安装MySQL宿主机挂载的目录是/usr/local/mysql/conf，这里将nacos-server.zip后解压后的conf/nacos-mysql.sql文件上传到宿主机的/usr/local/mysql/conf目录。

进入MySQL容器

docker exec -it mysql bash

登录mysql

mysql -uroot -proot

 导入nacos依赖的数据库sql

source /etc/mysql/nacos-mysql.sql

 

 

 创建nacos容器

docker run  \
-e TZ="Asia/Shanghai" \
-e MODE=standalone \
-e SPRING_DATASOURCE_PLATFORM=mysql \
-e MYSQL_DATABASE_NUM=1 \
-e MYSQL_SERVICE_HOST=192.168.111.199 \
-e MYSQL_SERVICE_PORT=3307 \
-e MYSQL_SERVICE_USER=root \
-e MYSQL_SERVICE_PASSWORD=root \
-e MYSQL_SERVICE_DB_NAME=nacos_config \
-p 8848:8848 \
--name nacos \
--restart=always \
-d nacos/nacos-server:1.4.1

-e 指定容器环境变量
TZ，指定时区。
MODE=standalone，单机模式
SPRING_DATASOURCE_PLATFORM=mysql 连接数据库类型为mysql|
MYSQL_SERVICE_HOST=192.168.111.199连接数据库地址(这里是docker的宿主机地址)
MYSQL_SERVICE_PORT=3307 数据库端口号，这里注意，容器之间不能直接访问，需要使用宿主机的映射端口。
MYSQL_SERVICE_USER=root 数据库用户名
MYSQL_SERVICE_PASSWORD=root 数据库密码
MYSQL_SERVICE_DB_NAME=nacos_config 数据库名
-p 8848:8848 指端口映射，访问宿主机端口8848，相当于访问的是nacos容器的8848端口
--name 给容器设置一个名字，若没有设置默为镜像名。
--restart always  设置容器开机自启动
-d 后台运行
nacos/nacos-server:1.4.1 要运行的容器名:版本号

请求地址：http://192.168.111.199:8848/nacos
用户名/密码：nacos/nacos

 

如果想保存nacos的配置文件和日志，可以做后面操作。后面步骤可以不管，一般不需要保存nacos。

保存nacos的配置文件，这一步把就是 cp （复制）指令，将容器中的/home/nacos 目录复制到宿主机的/usr/local/nacos目录下。

docker cp -a nacos:/home/nacos /usr/local/nacos

 停止nacos容器，并删除

docker stop  nacos
docker rm nacos

 nacos容器启动配置，这次将上面保存/usr/local/nacos下的配置文件挂载在nacos容器中

docker run  \
-e TZ="Asia/Shanghai" \
-e MODE=standalone \
-e SPRING_DATASOURCE_PLATFORM=mysql \
-e MYSQL_DATABASE_NUM=1 \
-e MYSQL_SERVICE_HOST=192.168.111.199 \
-e MYSQL_SERVICE_PORT=3307 \
-e MYSQL_SERVICE_USER=root \
-e MYSQL_SERVICE_PASSWORD=root \
-e MYSQL_SERVICE_DB_NAME=nacos_config \
-v /usr/local/nacos:/home/nacos \
-p 8848:8848 \
--name nacos \
--restart=always \
-d nacos/nacos-server:1.4.1

-v 挂载目录，宿主机目录:容器目录

安装Redis

在https://hub.docker.com/上搜索 redis镜像

  拉取版本指定版本redis

docker pull redis:5.0.14

创建redis配置文件目录

mkdir -p /usr/local/redis/conf

在配置文件录下创建redis.conf配置文件,

touch /usr/local/redis/conf/redis.conf

 redis.conf可以在官网下载

# Redis configuration file example.
#
# Note that in order to read the configuration file, Redis must be
# started with the file path as first argument:
#
# ./redis-server /path/to/redis.conf
 
# Note on units: when memory size is needed, it is possible to specify
# it in the usual form of 1k 5GB 4M and so forth:
#
# 1k => 1000 bytes
# 1kb => 1024 bytes
# 1m => 1000000 bytes
# 1mb => 1024*1024 bytes
# 1g => 1000000000 bytes
# 1gb => 1024*1024*1024 bytes
#
# units are case insensitive so 1GB 1Gb 1gB are all the same.
 
################################## INCLUDES ###################################
 
# Include one or more other config files here.  This is useful if you
# have a standard template that goes to all Redis servers but also need
# to customize a few per-server settings.  Include files can include
# other files, so use this wisely.
#
# Notice option "include" won't be rewritten by command "CONFIG REWRITE"
# from admin or Redis Sentinel. Since Redis always uses the last processed
# line as value of a configuration directive, you'd better put includes
# at the beginning of this file to avoid overwriting config change at runtime.
#
# If instead you are interested in using includes to override configuration
# options, it is better to use include as the last line.
#
# include /path/to/local.conf
# include /path/to/other.conf
 
################################## MODULES #####################################
 
# Load modules at startup. If the server is not able to load modules
# it will abort. It is possible to use multiple loadmodule directives.
#
# loadmodule /path/to/my_module.so
# loadmodule /path/to/other_module.so
 
################################## NETWORK #####################################
 
# By default, if no "bind" configuration directive is specified, Redis listens
# for connections from all the network interfaces available on the server.
# It is possible to listen to just one or multiple selected interfaces using
# the "bind" configuration directive, followed by one or more IP addresses.
#
# Examples:
#
# bind 192.168.1.100 10.0.0.1
# bind 127.0.0.1 ::1
#
# ~~~ WARNING ~~~ If the computer running Redis is directly exposed to the
# internet, binding to all the interfaces is dangerous and will expose the
# instance to everybody on the internet. So by default we uncomment the
# following bind directive, that will force Redis to listen only into
# the IPv4 loopback interface address (this means Redis will be able to
# accept connections only from clients running into the same computer it
# is running).
#
# IF YOU ARE SURE YOU WANT YOUR INSTANCE TO LISTEN TO ALL THE INTERFACES
# JUST COMMENT THE FOLLOWING LINE.
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
bind 127.0.0.1
 
# Protected mode is a layer of security protection, in order to avoid that
# Redis instances left open on the internet are accessed and exploited.
#
# When protected mode is on and if:
#
# 1) The server is not binding explicitly to a set of addresses using the
#    "bind" directive.
# 2) No password is configured.
#
# The server only accepts connections from clients connecting from the
# IPv4 and IPv6 loopback addresses 127.0.0.1 and ::1, and from Unix domain
# sockets.
#
# By default protected mode is enabled. You should disable it only if
# you are sure you want clients from other hosts to connect to Redis
# even if no authentication is configured, nor a specific set of interfaces
# are explicitly listed using the "bind" directive.
protected-mode yes
 
# Accept connections on the specified port, default is 6379 (IANA #815344).
# If port 0 is specified Redis will not listen on a TCP socket.
port 6379
 
# TCP listen() backlog.
#
# In high requests-per-second environments you need an high backlog in order
# to avoid slow clients connections issues. Note that the Linux kernel
# will silently truncate it to the value of /proc/sys/net/core/somaxconn so
# make sure to raise both the value of somaxconn and tcp_max_syn_backlog
# in order to get the desired effect.
tcp-backlog 511
 
# Unix socket.
#
# Specify the path for the Unix socket that will be used to listen for
# incoming connections. There is no default, so Redis will not listen
# on a unix socket when not specified.
#
# unixsocket /tmp/redis.sock
# unixsocketperm 700
 
# Close the connection after a client is idle for N seconds (0 to disable)
timeout 0
 
# TCP keepalive.
#
# If non-zero, use SO_KEEPALIVE to send TCP ACKs to clients in absence
# of communication. This is useful for two reasons:
#
# 1) Detect dead peers.
# 2) Take the connection alive from the point of view of network
#    equipment in the middle.
#
# On Linux, the specified value (in seconds) is the period used to send ACKs.
# Note that to close the connection the double of the time is needed.
# On other kernels the period depends on the kernel configuration.
#
# A reasonable value for this option is 300 seconds, which is the new
# Redis default starting with Redis 3.2.1.
tcp-keepalive 300
 
################################# GENERAL #####################################
 
# By default Redis does not run as a daemon. Use 'yes' if you need it.
# Note that Redis will write a pid file in /var/run/redis.pid when daemonized.
daemonize no
 
# If you run Redis from upstart or systemd, Redis can interact with your
# supervision tree. Options:
#   supervised no      - no supervision interaction
#   supervised upstart - signal upstart by putting Redis into SIGSTOP mode
#   supervised systemd - signal systemd by writing READY=1 to $NOTIFY_SOCKET
#   supervised auto    - detect upstart or systemd method based on
#                        UPSTART_JOB or NOTIFY_SOCKET environment variables
# Note: these supervision methods only signal "process is ready."
#       They do not enable continuous liveness pings back to your supervisor.
supervised no
 
# If a pid file is specified, Redis writes it where specified at startup
# and removes it at exit.
#
# When the server runs non daemonized, no pid file is created if none is
# specified in the configuration. When the server is daemonized, the pid file
# is used even if not specified, defaulting to "/var/run/redis.pid".
#
# Creating a pid file is best effort: if Redis is not able to create it
# nothing bad happens, the server will start and run normally.
pidfile /var/run/redis_6379.pid
 
# Specify the server verbosity level.
# This can be one of:
# debug (a lot of information, useful for development/testing)
# verbose (many rarely useful info, but not a mess like the debug level)
# notice (moderately verbose, what you want in production probably)
# warning (only very important / critical messages are logged)
loglevel notice
 
# Specify the log file name. Also the empty string can be used to force
# Redis to log on the standard output. Note that if you use standard
# output for logging but daemonize, logs will be sent to /dev/null
logfile ""
 
# To enable logging to the system logger, just set 'syslog-enabled' to yes,
# and optionally update the other syslog parameters to suit your needs.
# syslog-enabled no
 
# Specify the syslog identity.
# syslog-ident redis
 
# Specify the syslog facility. Must be USER or between LOCAL0-LOCAL7.
# syslog-facility local0
 
# Set the number of databases. The default database is DB 0, you can select
# a different one on a per-connection basis using SELECT  where
# dbid is a number between 0 and 'databases'-1
databases 16
 
# By default Redis shows an ASCII art logo only when started to log to the
# standard output and if the standard output is a TTY. Basically this means
# that normally a logo is displayed only in interactive sessions.
#
# However it is possible to force the pre-4.0 behavior and always show a
# ASCII art logo in startup logs by setting the following option to yes.
always-show-logo yes
 
################################ SNAPSHOTTING  ################################
#
# Save the DB on disk:
#
#   save  
#
#   Will save the DB if both the given number of seconds and the given
#   number of write operations against the DB occurred.
#
#   In the example below the behaviour will be to save:
#   after 900 sec (15 min) if at least 1 key changed
#   after 300 sec (5 min) if at least 10 keys changed
#   after 60 sec if at least 10000 keys changed
#
#   Note: you can disable saving completely by commenting out all "save" lines.
#
#   It is also possible to remove all the previously configured save
#   points by adding a save directive with a single empty string argument
#   like in the following example:
#
#   save ""
 
save 900 1
save 300 10
save 60 10000
 
# By default Redis will stop accepting writes if RDB snapshots are enabled
# (at least one save point) and the latest background save failed.
# This will make the user aware (in a hard way) that data is not persisting
# on disk properly, otherwise chances are that no one will notice and some
# disaster will happen.
#
# If the background saving process will start working again Redis will
# automatically allow writes again.
#
# However if you have setup your proper monitoring of the Redis server
# and persistence, you may want to disable this feature so that Redis will
# continue to work as usual even if there are problems with disk,
# permissions, and so forth.
stop-writes-on-bgsave-error yes
 
# Compress string objects using LZF when dump .rdb databases?
# For default that's set to 'yes' as it's almost always a win.
# If you want to save some CPU in the saving child set it to 'no' but
# the dataset will likely be bigger if you have compressible values or keys.
rdbcompression yes
 
# Since version 5 of RDB a CRC64 checksum is placed at the end of the file.
# This makes the format more resistant to corruption but there is a performance
# hit to pay (around 10%) when saving and loading RDB files, so you can disable it
# for maximum performances.
#
# RDB files created with checksum disabled have a checksum of zero that will
# tell the loading code to skip the check.
rdbchecksum yes
 
# The filename where to dump the DB
dbfilename dump.rdb
 
# The working directory.
#
# The DB will be written inside this directory, with the filename specified
# above using the 'dbfilename' configuration directive.
#
# The Append Only File will also be created inside this directory.
#
# Note that you must specify a directory here, not a file name.
dir ./
 
################################# REPLICATION #################################
 
# Master-Replica replication. Use replicaof to make a Redis instance a copy of
# another Redis server. A few things to understand ASAP about Redis replication.
#
#   +------------------+      +---------------+
#   |      Master      | ---> |    Replica    |
#   | (receive writes) |      |  (exact copy) |
#   +------------------+      +---------------+
#
# 1) Redis replication is asynchronous, but you can configure a master to
#    stop accepting writes if it appears to be not connected with at least
#    a given number of replicas.
# 2) Redis replicas are able to perform a partial resynchronization with the
#    master if the replication link is lost for a relatively small amount of
#    time. You may want to configure the replication backlog size (see the next
#    sections of this file) with a sensible value depending on your needs.
# 3) Replication is automatic and does not need user intervention. After a
#    network partition replicas automatically try to reconnect to masters
#    and resynchronize with them.
#
# replicaof  
 
# If the master is password protected (using the "requirepass" configuration
# directive below) it is possible to tell the replica to authenticate before
# starting the replication synchronization process, otherwise the master will
# refuse the replica request.
#
# masterauth 
 
# When a replica loses its connection with the master, or when the replication
# is still in progress, the replica can act in two different ways:
#
# 1) if replica-serve-stale-data is set to 'yes' (the default) the replica will
#    still reply to client requests, possibly with out of date data, or the
#    data set may just be empty if this is the first synchronization.
#
# 2) if replica-serve-stale-data is set to 'no' the replica will reply with
#    an error "SYNC with master in progress" to all the kind of commands
#    but to INFO, replicaOF, AUTH, PING, SHUTDOWN, REPLCONF, ROLE, CONFIG,
#    SUBSCRIBE, UNSUBSCRIBE, PSUBSCRIBE, PUNSUBSCRIBE, PUBLISH, PUBSUB,
#    COMMAND, POST, HOST: and LATENCY.
#
replica-serve-stale-data yes
 
# You can configure a replica instance to accept writes or not. Writing against
# a replica instance may be useful to store some ephemeral data (because data
# written on a replica will be easily deleted after resync with the master) but
# may also cause problems if clients are writing to it because of a
# misconfiguration.
#
# Since Redis 2.6 by default replicas are read-only.
#
# Note: read only replicas are not designed to be exposed to untrusted clients
# on the internet. It's just a protection layer against misuse of the instance.
# Still a read only replica exports by default all the administrative commands
# such as CONFIG, DEBUG, and so forth. To a limited extent you can improve
# security of read only replicas using 'rename-command' to shadow all the
# administrative / dangerous commands.
replica-read-only yes
 
# Replication SYNC strategy: disk or socket.
#
# -------------------------------------------------------
# WARNING: DISKLESS REPLICATION IS EXPERIMENTAL CURRENTLY
# -------------------------------------------------------
#
# New replicas and reconnecting replicas that are not able to continue the replication
# process just receiving differences, need to do what is called a "full
# synchronization". An RDB file is transmitted from the master to the replicas.
# The transmission can happen in two different ways:
#
# 1) Disk-backed: The Redis master creates a new process that writes the RDB
#                 file on disk. Later the file is transferred by the parent
#                 process to the replicas incrementally.
# 2) Diskless: The Redis master creates a new process that directly writes the
#              RDB file to replica sockets, without touching the disk at all.
#
# With disk-backed replication, while the RDB file is generated, more replicas
# can be queued and served with the RDB file as soon as the current child producing
# the RDB file finishes its work. With diskless replication instead once
# the transfer starts, new replicas arriving will be queued and a new transfer
# will start when the current one terminates.
#
# When diskless replication is used, the master waits a configurable amount of
# time (in seconds) before starting the transfer in the hope that multiple replicas
# will arrive and the transfer can be parallelized.
#
# With slow disks and fast (large bandwidth) networks, diskless replication
# works better.
repl-diskless-sync no
 
# When diskless replication is enabled, it is possible to configure the delay
# the server waits in order to spawn the child that transfers the RDB via socket
# to the replicas.
#
# This is important since once the transfer starts, it is not possible to serve
# new replicas arriving, that will be queued for the next RDB transfer, so the server
# waits a delay in order to let more replicas arrive.
#
# The delay is specified in seconds, and by default is 5 seconds. To disable
# it entirely just set it to 0 seconds and the transfer will start ASAP.
repl-diskless-sync-delay 5
 
# Replicas send PINGs to server in a predefined interval. It's possible to change
# this interval with the repl_ping_replica_period option. The default value is 10
# seconds.
#
# repl-ping-replica-period 10
 
# The following option sets the replication timeout for:
#
# 1) Bulk transfer I/O during SYNC, from the point of view of replica.
# 2) Master timeout from the point of view of replicas (data, pings).
# 3) Replica timeout from the point of view of masters (REPLCONF ACK pings).
#
# It is important to make sure that this value is greater than the value
# specified for repl-ping-replica-period otherwise a timeout will be detected
# every time there is low traffic between the master and the replica.
#
# repl-timeout 60
 
# Disable TCP_NODELAY on the replica socket after SYNC?
#
# If you select "yes" Redis will use a smaller number of TCP packets and
# less bandwidth to send data to replicas. But this can add a delay for
# the data to appear on the replica side, up to 40 milliseconds with
# Linux kernels using a default configuration.
#
# If you select "no" the delay for data to appear on the replica side will
# be reduced but more bandwidth will be used for replication.
#
# By default we optimize for low latency, but in very high traffic conditions
# or when the master and replicas are many hops away, turning this to "yes" may
# be a good idea.
repl-disable-tcp-nodelay no
 
# Set the replication backlog size. The backlog is a buffer that accumulates
# replica data when replicas are disconnected for some time, so that when a replica
# wants to reconnect again, often a full resync is not needed, but a partial
# resync is enough, just passing the portion of data the replica missed while
# disconnected.
#
# The bigger the replication backlog, the longer the time the replica can be
# disconnected and later be able to perform a partial resynchronization.
#
# The backlog is only allocated once there is at least a replica connected.
#
# repl-backlog-size 1mb
 
# After a master has no longer connected replicas for some time, the backlog
# will be freed. The following option configures the amount of seconds that
# need to elapse, starting from the time the last replica disconnected, for
# the backlog buffer to be freed.
#
# Note that replicas never free the backlog for timeout, since they may be
# promoted to masters later, and should be able to correctly "partially
# resynchronize" with the replicas: hence they should always accumulate backlog.
#
# A value of 0 means to never release the backlog.
#
# repl-backlog-ttl 3600
 
# The replica priority is an integer number published by Redis in the INFO output.
# It is used by Redis Sentinel in order to select a replica to promote into a
# master if the master is no longer working correctly.
#
# A replica with a low priority number is considered better for promotion, so
# for instance if there are three replicas with priority 10, 100, 25 Sentinel will
# pick the one with priority 10, that is the lowest.
#
# However a special priority of 0 marks the replica as not able to perform the
# role of master, so a replica with priority of 0 will never be selected by
# Redis Sentinel for promotion.
#
# By default the priority is 100.
replica-priority 100
 
# It is possible for a master to stop accepting writes if there are less than
# N replicas connected, having a lag less or equal than M seconds.
#
# The N replicas need to be in "online" state.
#
# The lag in seconds, that must be <= the specified value, is calculated from
# the last ping received from the replica, that is usually sent every second.
#
# This option does not GUARANTEE that N replicas will accept the write, but
# will limit the window of exposure for lost writes in case not enough replicas
# are available, to the specified number of seconds.
#
# For example to require at least 3 replicas with a lag <= 10 seconds use:
#
# min-replicas-to-write 3
# min-replicas-max-lag 10
#
# Setting one or the other to 0 disables the feature.
#
# By default min-replicas-to-write is set to 0 (feature disabled) and
# min-replicas-max-lag is set to 10.
 
# A Redis master is able to list the address and port of the attached
# replicas in different ways. For example the "INFO replication" section
# offers this information, which is used, among other tools, by
# Redis Sentinel in order to discover replica instances.
# Another place where this info is available is in the output of the
# "ROLE" command of a master.
#
# The listed IP and address normally reported by a replica is obtained
# in the following way:
#
#   IP: The address is auto detected by checking the peer address
#   of the socket used by the replica to connect with the master.
#
#   Port: The port is communicated by the replica during the replication
#   handshake, and is normally the port that the replica is using to
#   listen for connections.
#
# However when port forwarding or Network Address Translation (NAT) is
# used, the replica may be actually reachable via different IP and port
# pairs. The following two options can be used by a replica in order to
# report to its master a specific set of IP and port, so that both INFO
# and ROLE will report those values.
#
# There is no need to use both the options if you need to override just
# the port or the IP address.
#
# replica-announce-ip 5.5.5.5
# replica-announce-port 1234
 
################################## SECURITY ###################################
 
# Require clients to issue AUTH  before processing any other
# commands.  This might be useful in environments in which you do not trust
# others with access to the host running redis-server.
#
# This should stay commented out for backward compatibility and because most
# people do not need auth (e.g. they run their own servers).
#
# Warning: since Redis is pretty fast an outside user can try up to
# 150k passwords per second against a good box. This means that you should
# use a very strong password otherwise it will be very easy to break.
#
# requirepass foobared
 
# Command renaming.
#
# It is possible to change the name of dangerous commands in a shared
# environment. For instance the CONFIG command may be renamed into something
# hard to guess so that it will still be available for internal-use tools
# but not available for general clients.
#
# Example:
#
# rename-command CONFIG b840fc02d524045429941cc15f59e41cb7be6c52
#
# It is also possible to completely kill a command by renaming it into
# an empty string:
#
# rename-command CONFIG ""
#
# Please note that changing the name of commands that are logged into the
# AOF file or transmitted to replicas may cause problems.
 
################################### CLIENTS ####################################
 
# Set the max number of connected clients at the same time. By default
# this limit is set to 10000 clients, however if the Redis server is not
# able to configure the process file limit to allow for the specified limit
# the max number of allowed clients is set to the current file limit
# minus 32 (as Redis reserves a few file descriptors for internal uses).
#
# Once the limit is reached Redis will close all the new connections sending
# an error 'max number of clients reached'.
#
# maxclients 10000
 
############################## MEMORY MANAGEMENT ################################
 
# Set a memory usage limit to the specified amount of bytes.
# When the memory limit is reached Redis will try to remove keys
# according to the eviction policy selected (see maxmemory-policy).
#
# If Redis can't remove keys according to the policy, or if the policy is
# set to 'noeviction', Redis will start to reply with errors to commands
# that would use more memory, like SET, LPUSH, and so on, and will continue
# to reply to read-only commands like GET.
#
# This option is usually useful when using Redis as an LRU or LFU cache, or to
# set a hard memory limit for an instance (using the 'noeviction' policy).
#
# WARNING: If you have replicas attached to an instance with maxmemory on,
# the size of the output buffers needed to feed the replicas are subtracted
# from the used memory count, so that network problems / resyncs will
# not trigger a loop where keys are evicted, and in turn the output
# buffer of replicas is full with DELs of keys evicted triggering the deletion
# of more keys, and so forth until the database is completely emptied.
#
# In short... if you have replicas attached it is suggested that you set a lower
# limit for maxmemory so that there is some free RAM on the system for replica
# output buffers (but this is not needed if the policy is 'noeviction').
#
# maxmemory 
 
# MAXMEMORY POLICY: how Redis will select what to remove when maxmemory
# is reached. You can select among five behaviors:
#
# volatile-lru -> Evict using approximated LRU among the keys with an expire set.
# allkeys-lru -> Evict any key using approximated LRU.
# volatile-lfu -> Evict using approximated LFU among the keys with an expire set.
# allkeys-lfu -> Evict any key using approximated LFU.
# volatile-random -> Remove a random key among the ones with an expire set.
# allkeys-random -> Remove a random key, any key.
# volatile-ttl -> Remove the key with the nearest expire time (minor TTL)
# noeviction -> Don't evict anything, just return an error on write operations.
#
# LRU means Least Recently Used
# LFU means Least Frequently Used
#
# Both LRU, LFU and volatile-ttl are implemented using approximated
# randomized algorithms.
#
# Note: with any of the above policies, Redis will return an error on write
#       operations, when there are no suitable keys for eviction.
#
#       At the date of writing these commands are: set setnx setex append
#       incr decr rpush lpush rpushx lpushx linsert lset rpoplpush sadd
#       sinter sinterstore sunion sunionstore sdiff sdiffstore zadd zincrby
#       zunionstore zinterstore hset hsetnx hmset hincrby incrby decrby
#       getset mset msetnx exec sort
#
# The default is:
#
# maxmemory-policy noeviction
 
# LRU, LFU and minimal TTL algorithms are not precise algorithms but approximated
# algorithms (in order to save memory), so you can tune it for speed or
# accuracy. For default Redis will check five keys and pick the one that was
# used less recently, you can change the sample size using the following
# configuration directive.
#
# The default of 5 produces good enough results. 10 Approximates very closely
# true LRU but costs more CPU. 3 is faster but not very accurate.
#
# maxmemory-samples 5
 
# Starting from Redis 5, by default a replica will ignore its maxmemory setting
# (unless it is promoted to master after a failover or manually). It means
# that the eviction of keys will be just handled by the master, sending the
# DEL commands to the replica as keys evict in the master side.
#
# This behavior ensures that masters and replicas stay consistent, and is usually
# what you want, however if your replica is writable, or you want the replica to have
# a different memory setting, and you are sure all the writes performed to the
# replica are idempotent, then you may change this default (but be sure to understand
# what you are doing).
#
# Note that since the replica by default does not evict, it may end using more
# memory than the one set via maxmemory (there are certain buffers that may
# be larger on the replica, or data structures may sometimes take more memory and so
# forth). So make sure you monitor your replicas and make sure they have enough
# memory to never hit a real out-of-memory condition before the master hits
# the configured maxmemory setting.
#
# replica-ignore-maxmemory yes
 
############################# LAZY FREEING ####################################
 
# Redis has two primitives to delete keys. One is called DEL and is a blocking
# deletion of the object. It means that the server stops processing new commands
# in order to reclaim all the memory associated with an object in a synchronous
# way. If the key deleted is associated with a small object, the time needed
# in order to execute the DEL command is very small and comparable to most other
# O(1) or O(log_N) commands in Redis. However if the key is associated with an
# aggregated value containing millions of elements, the server can block for
# a long time (even seconds) in order to complete the operation.
#
# For the above reasons Redis also offers non blocking deletion primitives
# such as UNLINK (non blocking DEL) and the ASYNC option of FLUSHALL and
# FLUSHDB commands, in order to reclaim memory in background. Those commands
# are executed in constant time. Another thread will incrementally free the
# object in the background as fast as possible.
#
# DEL, UNLINK and ASYNC option of FLUSHALL and FLUSHDB are user-controlled.
# It's up to the design of the application to understand when it is a good
# idea to use one or the other. However the Redis server sometimes has to
# delete keys or flush the whole database as a side effect of other operations.
# Specifically Redis deletes objects independently of a user call in the
# following scenarios:
#
# 1) On eviction, because of the maxmemory and maxmemory policy configurations,
#    in order to make room for new data, without going over the specified
#    memory limit.
# 2) Because of expire: when a key with an associated time to live (see the
#    EXPIRE command) must be deleted from memory.
# 3) Because of a side effect of a command that stores data on a key that may
#    already exist. For example the RENAME command may delete the old key
#    content when it is replaced with another one. Similarly SUNIONSTORE
#    or SORT with STORE option may delete existing keys. The SET command
#    itself removes any old content of the specified key in order to replace
#    it with the specified string.
# 4) During replication, when a replica performs a full resynchronization with
#    its master, the content of the whole database is removed in order to
#    load the RDB file just transferred.
#
# In all the above cases the default is to delete objects in a blocking way,
# like if DEL was called. However you can configure each case specifically
# in order to instead release memory in a non-blocking way like if UNLINK
# was called, using the following configuration directives:
 
lazyfree-lazy-eviction no
lazyfree-lazy-expire no
lazyfree-lazy-server-del no
replica-lazy-flush no
 
############################## APPEND ONLY MODE ###############################
 
# By default Redis asynchronously dumps the dataset on disk. This mode is
# good enough in many applications, but an issue with the Redis process or
# a power outage may result into a few minutes of writes lost (depending on
# the configured save points).
#
# The Append Only File is an alternative persistence mode that provides
# much better durability. For instance using the default data fsync policy
# (see later in the config file) Redis can lose just one second of writes in a
# dramatic event like a server power outage, or a single write if something
# wrong with the Redis process itself happens, but the operating system is
# still running correctly.
#
# AOF and RDB persistence can be enabled at the same time without problems.
# If the AOF is enabled on startup Redis will load the AOF, that is the file
# with the better durability guarantees.
#
# Please check http://redis.io/topics/persistence for more information.
 
appendonly no
 
# The name of the append only file (default: "appendonly.aof")
 
appendfilename "appendonly.aof"
 
# The fsync() call tells the Operating System to actually write data on disk
# instead of waiting for more data in the output buffer. Some OS will really flush
# data on disk, some other OS will just try to do it ASAP.
#
# Redis supports three different modes:
#
# no: don't fsync, just let the OS flush the data when it wants. Faster.
# always: fsync after every write to the append only log. Slow, Safest.
# everysec: fsync only one time every second. Compromise.
#
# The default is "everysec", as that's usually the right compromise between
# speed and data safety. It's up to you to understand if you can relax this to
# "no" that will let the operating system flush the output buffer when
# it wants, for better performances (but if you can live with the idea of
# some data loss consider the default persistence mode that's snapshotting),
# or on the contrary, use "always" that's very slow but a bit safer than
# everysec.
#
# More details please check the following article:
# http://antirez.com/post/redis-persistence-demystified.html
#
# If unsure, use "everysec".
 
# appendfsync always
appendfsync everysec
# appendfsync no
 
# When the AOF fsync policy is set to always or everysec, and a background
# saving process (a background save or AOF log background rewriting) is
# performing a lot of I/O against the disk, in some Linux configurations
# Redis may block too long on the fsync() call. Note that there is no fix for
# this currently, as even performing fsync in a different thread will block
# our synchronous write(2) call.
#
# In order to mitigate this problem it's possible to use the following option
# that will prevent fsync() from being called in the main process while a
# BGSAVE or BGREWRITEAOF is in progress.
#
# This means that while another child is saving, the durability of Redis is
# the same as "appendfsync none". In practical terms, this means that it is
# possible to lose up to 30 seconds of log in the worst scenario (with the
# default Linux settings).
#
# If you have latency problems turn this to "yes". Otherwise leave it as
# "no" that is the safest pick from the point of view of durability.
 
no-appendfsync-on-rewrite no
 
# Automatic rewrite of the append only file.
# Redis is able to automatically rewrite the log file implicitly calling
# BGREWRITEAOF when the AOF log size grows by the specified percentage.
#
# This is how it works: Redis remembers the size of the AOF file after the
# latest rewrite (if no rewrite has happened since the restart, the size of
# the AOF at startup is used).
#
# This base size is compared to the current size. If the current size is
# bigger than the specified percentage, the rewrite is triggered. Also
# you need to specify a minimal size for the AOF file to be rewritten, this
# is useful to avoid rewriting the AOF file even if the percentage increase
# is reached but it is still pretty small.
#
# Specify a percentage of zero in order to disable the automatic AOF
# rewrite feature.
 
auto-aof-rewrite-percentage 100
auto-aof-rewrite-min-size 64mb
 
# An AOF file may be found to be truncated at the end during the Redis
# startup process, when the AOF data gets loaded back into memory.
# This may happen when the system where Redis is running
# crashes, especially when an ext4 filesystem is mounted without the
# data=ordered option (however this can't happen when Redis itself
# crashes or aborts but the operating system still works correctly).
#
# Redis can either exit with an error when this happens, or load as much
# data as possible (the default now) and start if the AOF file is found
# to be truncated at the end. The following option controls this behavior.
#
# If aof-load-truncated is set to yes, a truncated AOF file is loaded and
# the Redis server starts emitting a log to inform the user of the event.
# Otherwise if the option is set to no, the server aborts with an error
# and refuses to start. When the option is set to no, the user requires
# to fix the AOF file using the "redis-check-aof" utility before to restart
# the server.
#
# Note that if the AOF file will be found to be corrupted in the middle
# the server will still exit with an error. This option only applies when
# Redis will try to read more data from the AOF file but not enough bytes
# will be found.
aof-load-truncated yes
 
# When rewriting the AOF file, Redis is able to use an RDB preamble in the
# AOF file for faster rewrites and recoveries. When this option is turned
# on the rewritten AOF file is composed of two different stanzas:
#
#   [RDB file][AOF tail]
#
# When loading Redis recognizes that the AOF file starts with the "REDIS"
# string and loads the prefixed RDB file, and continues loading the AOF
# tail.
aof-use-rdb-preamble yes
 
################################ LUA SCRIPTING  ###############################
 
# Max execution time of a Lua script in milliseconds.
#
# If the maximum execution time is reached Redis will log that a script is
# still in execution after the maximum allowed time and will start to
# reply to queries with an error.
#
# When a long running script exceeds the maximum execution time only the
# SCRIPT KILL and SHUTDOWN NOSAVE commands are available. The first can be
# used to stop a script that did not yet called write commands. The second
# is the only way to shut down the server in the case a write command was
# already issued by the script but the user doesn't want to wait for the natural
# termination of the script.
#
# Set it to 0 or a negative value for unlimited execution without warnings.
lua-time-limit 5000
 
################################ REDIS CLUSTER  ###############################
 
# Normal Redis instances can't be part of a Redis Cluster; only nodes that are
# started as cluster nodes can. In order to start a Redis instance as a
# cluster node enable the cluster support uncommenting the following:
#
# cluster-enabled yes
 
# Every cluster node has a cluster configuration file. This file is not
# intended to be edited by hand. It is created and updated by Redis nodes.
# Every Redis Cluster node requires a different cluster configuration file.
# Make sure that instances running in the same system do not have
# overlapping cluster configuration file names.
#
# cluster-config-file nodes-6379.conf
 
# Cluster node timeout is the amount of milliseconds a node must be unreachable
# for it to be considered in failure state.
# Most other internal time limits are multiple of the node timeout.
#
# cluster-node-timeout 15000
 
# A replica of a failing master will avoid to start a failover if its data
# looks too old.
#
# There is no simple way for a replica to actually have an exact measure of
# its "data age", so the following two checks are performed:
#
# 1) If there are multiple replicas able to failover, they exchange messages
#    in order to try to give an advantage to the replica with the best
#    replication offset (more data from the master processed).
#    Replicas will try to get their rank by offset, and apply to the start
#    of the failover a delay proportional to their rank.
#
# 2) Every single replica computes the time of the last interaction with
#    its master. This can be the last ping or command received (if the master
#    is still in the "connected" state), or the time that elapsed since the
#    disconnection with the master (if the replication link is currently down).
#    If the last interaction is too old, the replica will not try to failover
#    at all.
#
# The point "2" can be tuned by user. Specifically a replica will not perform
# the failover if, since the last interaction with the master, the time
# elapsed is greater than:
#
#   (node-timeout * replica-validity-factor) + repl-ping-replica-period
#
# So for example if node-timeout is 30 seconds, and the replica-validity-factor
# is 10, and assuming a default repl-ping-replica-period of 10 seconds, the
# replica will not try to failover if it was not able to talk with the master
# for longer than 310 seconds.
#
# A large replica-validity-factor may allow replicas with too old data to failover
# a master, while a too small value may prevent the cluster from being able to
# elect a replica at all.
#
# For maximum availability, it is possible to set the replica-validity-factor
# to a value of 0, which means, that replicas will always try to failover the
# master regardless of the last time they interacted with the master.
# (However they'll always try to apply a delay proportional to their
# offset rank).
#
# Zero is the only value able to guarantee that when all the partitions heal
# the cluster will always be able to continue.
#
# cluster-replica-validity-factor 10
 
# Cluster replicas are able to migrate to orphaned masters, that are masters
# that are left without working replicas. This improves the cluster ability
# to resist to failures as otherwise an orphaned master can't be failed over
# in case of failure if it has no working replicas.
#
# Replicas migrate to orphaned masters only if there are still at least a
# given number of other working replicas for their old master. This number
# is the "migration barrier". A migration barrier of 1 means that a replica
# will migrate only if there is at least 1 other working replica for its master
# and so forth. It usually reflects the number of replicas you want for every
# master in your cluster.
#
# Default is 1 (replicas migrate only if their masters remain with at least
# one replica). To disable migration just set it to a very large value.
# A value of 0 can be set but is useful only for debugging and dangerous
# in production.
#
# cluster-migration-barrier 1
 
# By default Redis Cluster nodes stop accepting queries if they detect there
# is at least an hash slot uncovered (no available node is serving it).
# This way if the cluster is partially down (for example a range of hash slots
# are no longer covered) all the cluster becomes, eventually, unavailable.
# It automatically returns available as soon as all the slots are covered again.
#
# However sometimes you want the subset of the cluster which is working,
# to continue to accept queries for the part of the key space that is still
# covered. In order to do so, just set the cluster-require-full-coverage
# option to no.
#
# cluster-require-full-coverage yes
 
# This option, when set to yes, prevents replicas from trying to failover its
# master during master failures. However the master can still perform a
# manual failover, if forced to do so.
#
# This is useful in different scenarios, especially in the case of multiple
# data center operations, where we want one side to never be promoted if not
# in the case of a total DC failure.
#
# cluster-replica-no-failover no
 
# In order to setup your cluster make sure to read the documentation
# available at http://redis.io web site.
 
########################## CLUSTER DOCKER/NAT support  ########################
 
# In certain deployments, Redis Cluster nodes address discovery fails, because
# addresses are NAT-ted or because ports are forwarded (the typical case is
# Docker and other containers).
#
# In order to make Redis Cluster working in such environments, a static
# configuration where each node knows its public address is needed. The
# following two options are used for this scope, and are:
#
# * cluster-announce-ip
# * cluster-announce-port
# * cluster-announce-bus-port
#
# Each instruct the node about its address, client port, and cluster message
# bus port. The information is then published in the header of the bus packets
# so that other nodes will be able to correctly map the address of the node
# publishing the information.
#
# If the above options are not used, the normal Redis Cluster auto-detection
# will be used instead.
#
# Note that when remapped, the bus port may not be at the fixed offset of
# clients port + 10000, so you can specify any port and bus-port depending
# on how they get remapped. If the bus-port is not set, a fixed offset of
# 10000 will be used as usually.
#
# Example:
#
# cluster-announce-ip 10.1.1.5
# cluster-announce-port 6379
# cluster-announce-bus-port 6380
 
################################## SLOW LOG ###################################
 
# The Redis Slow Log is a system to log queries that exceeded a specified
# execution time. The execution time does not include the I/O operations
# like talking with the client, sending the reply and so forth,
# but just the time needed to actually execute the command (this is the only
# stage of command execution where the thread is blocked and can not serve
# other requests in the meantime).
#
# You can configure the slow log with two parameters: one tells Redis
# what is the execution time, in microseconds, to exceed in order for the
# command to get logged, and the other parameter is the length of the
# slow log. When a new command is logged the oldest one is removed from the
# queue of logged commands.
 
# The following time is expressed in microseconds, so 1000000 is equivalent
# to one second. Note that a negative number disables the slow log, while
# a value of zero forces the logging of every command.
slowlog-log-slower-than 10000
 
# There is no limit to this length. Just be aware that it will consume memory.
# You can reclaim memory used by the slow log with SLOWLOG RESET.
slowlog-max-len 128
 
################################ LATENCY MONITOR ##############################
 
# The Redis latency monitoring subsystem samples different operations
# at runtime in order to collect data related to possible sources of
# latency of a Redis instance.
#
# Via the LATENCY command this information is available to the user that can
# print graphs and obtain reports.
#
# The system only logs operations that were performed in a time equal or
# greater than the amount of milliseconds specified via the
# latency-monitor-threshold configuration directive. When its value is set
# to zero, the latency monitor is turned off.
#
# By default latency monitoring is disabled since it is mostly not needed
# if you don't have latency issues, and collecting data has a performance
# impact, that while very small, can be measured under big load. Latency
# monitoring can easily be enabled at runtime using the command
# "CONFIG SET latency-monitor-threshold " if needed.
latency-monitor-threshold 0
 
############################# EVENT NOTIFICATION ##############################
 
# Redis can notify Pub/Sub clients about events happening in the key space.
# This feature is documented at http://redis.io/topics/notifications
#
# For instance if keyspace events notification is enabled, and a client
# performs a DEL operation on key "foo" stored in the Database 0, two
# messages will be published via Pub/Sub:
#
# PUBLISH __keyspace@0__:foo del
# PUBLISH __keyevent@0__:del foo
#
# It is possible to select the events that Redis will notify among a set
# of classes. Every class is identified by a single character:
#
#  K     Keyspace events, published with __keyspace@__ prefix.
#  E     Keyevent events, published with __keyevent@__ prefix.
#  g     Generic commands (non-type specific) like DEL, EXPIRE, RENAME, ...
#  $     String commands
#  l     List commands
#  s     Set commands
#  h     Hash commands
#  z     Sorted set commands
#  x     Expired events (events generated every time a key expires)
#  e     Evicted events (events generated when a key is evicted for maxmemory)
#  A     Alias for g$lshzxe, so that the "AKE" string means all the events.
#
#  The "notify-keyspace-events" takes as argument a string that is composed
#  of zero or multiple characters. The empty string means that notifications
#  are disabled.
#
#  Example: to enable list and generic events, from the point of view of the
#           event name, use:
#
#  notify-keyspace-events Elg
#
#  Example 2: to get the stream of the expired keys subscribing to channel
#             name __keyevent@0__:expired use:
#
#  notify-keyspace-events Ex
#
#  By default all notifications are disabled because most users don't need
#  this feature and the feature has some overhead. Note that if you don't
#  specify at least one of K or E, no events will be delivered.
notify-keyspace-events ""
 
############################### ADVANCED CONFIG ###############################
 
# Hashes are encoded using a memory efficient data structure when they have a
# small number of entries, and the biggest entry does not exceed a given
# threshold. These thresholds can be configured using the following directives.
hash-max-ziplist-entries 512
hash-max-ziplist-value 64
 
# Lists are also encoded in a special way to save a lot of space.
# The number of entries allowed per internal list node can be specified
# as a fixed maximum size or a maximum number of elements.
# For a fixed maximum size, use -5 through -1, meaning:
# -5: max size: 64 Kb  <-- not recommended for normal workloads
# -4: max size: 32 Kb  <-- not recommended
# -3: max size: 16 Kb  <-- probably not recommended
# -2: max size: 8 Kb   <-- good
# -1: max size: 4 Kb   <-- good
# Positive numbers mean store up to _exactly_ that number of elements
# per list node.
# The highest performing option is usually -2 (8 Kb size) or -1 (4 Kb size),
# but if your use case is unique, adjust the settings as necessary.
list-max-ziplist-size -2
 
# Lists may also be compressed.
# Compress depth is the number of quicklist ziplist nodes from *each* side of
# the list to *exclude* from compression.  The head and tail of the list
# are always uncompressed for fast push/pop operations.  Settings are:
# 0: disable all list compression
# 1: depth 1 means "don't start compressing until after 1 node into the list,
#    going from either the head or tail"
#    So: [head]->node->node->...->node->[tail]
#    [head], [tail] will always be uncompressed; inner nodes will compress.
# 2: [head]->[next]->node->node->...->node->[prev]->[tail]
#    2 here means: don't compress head or head->next or tail->prev or tail,
#    but compress all nodes between them.
# 3: [head]->[next]->[next]->node->node->...->node->[prev]->[prev]->[tail]
# etc.
list-compress-depth 0
 
# Sets have a special encoding in just one case: when a set is composed
# of just strings that happen to be integers in radix 10 in the range
# of 64 bit signed integers.
# The following configuration setting sets the limit in the size of the
# set in order to use this special memory saving encoding.
set-max-intset-entries 512
 
# Similarly to hashes and lists, sorted sets are also specially encoded in
# order to save a lot of space. This encoding is only used when the length and
# elements of a sorted set are below the following limits:
zset-max-ziplist-entries 128
zset-max-ziplist-value 64
 
# HyperLogLog sparse representation bytes limit. The limit includes the
# 16 bytes header. When an HyperLogLog using the sparse representation crosses
# this limit, it is converted into the dense representation.
#
# A value greater than 16000 is totally useless, since at that point the
# dense representation is more memory efficient.
#
# The suggested value is ~ 3000 in order to have the benefits of
# the space efficient encoding without slowing down too much PFADD,
# which is O(N) with the sparse encoding. The value can be raised to
# ~ 10000 when CPU is not a concern, but space is, and the data set is
# composed of many HyperLogLogs with cardinality in the 0 - 15000 range.
hll-sparse-max-bytes 3000
 
# Streams macro node max size / items. The stream data structure is a radix
# tree of big nodes that encode multiple items inside. Using this configuration
# it is possible to configure how big a single node can be in bytes, and the
# maximum number of items it may contain before switching to a new node when
# appending new stream entries. If any of the following settings are set to
# zero, the limit is ignored, so for instance it is possible to set just a
# max entires limit by setting max-bytes to 0 and max-entries to the desired
# value.
stream-node-max-bytes 4096
stream-node-max-entries 100
 
# Active rehashing uses 1 millisecond every 100 milliseconds of CPU time in
# order to help rehashing the main Redis hash table (the one mapping top-level
# keys to values). The hash table implementation Redis uses (see dict.c)
# performs a lazy rehashing: the more operation you run into a hash table
# that is rehashing, the more rehashing "steps" are performed, so if the
# server is idle the rehashing is never complete and some more memory is used
# by the hash table.
#
# The default is to use this millisecond 10 times every second in order to
# actively rehash the main dictionaries, freeing memory when possible.
#
# If unsure:
# use "activerehashing no" if you have hard latency requirements and it is
# not a good thing in your environment that Redis can reply from time to time
# to queries with 2 milliseconds delay.
#
# use "activerehashing yes" if you don't have such hard requirements but
# want to free memory asap when possible.
activerehashing yes
 
# The client output buffer limits can be used to force disconnection of clients
# that are not reading data from the server fast enough for some reason (a
# common reason is that a Pub/Sub client can't consume messages as fast as the
# publisher can produce them).
#
# The limit can be set differently for the three different classes of clients:
#
# normal -> normal clients including MONITOR clients
# replica  -> replica clients
# pubsub -> clients subscribed to at least one pubsub channel or pattern
#
# The syntax of every client-output-buffer-limit directive is the following:
#
# client-output-buffer-limit    
#
# A client is immediately disconnected once the hard limit is reached, or if
# the soft limit is reached and remains reached for the specified number of
# seconds (continuously).
# So for instance if the hard limit is 32 megabytes and the soft limit is
# 16 megabytes / 10 seconds, the client will get disconnected immediately
# if the size of the output buffers reach 32 megabytes, but will also get
# disconnected if the client reaches 16 megabytes and continuously overcomes
# the limit for 10 seconds.
#
# By default normal clients are not limited because they don't receive data
# without asking (in a push way), but just after a request, so only
# asynchronous clients may create a scenario where data is requested faster
# than it can read.
#
# Instead there is a default limit for pubsub and replica clients, since
# subscribers and replicas receive data in a push fashion.
#
# Both the hard or the soft limit can be disabled by setting them to zero.
client-output-buffer-limit normal 0 0 0
client-output-buffer-limit replica 256mb 64mb 60
client-output-buffer-limit pubsub 32mb 8mb 60
 
# Client query buffers accumulate new commands. They are limited to a fixed
# amount by default in order to avoid that a protocol desynchronization (for
# instance due to a bug in the client) will lead to unbound memory usage in
# the query buffer. However you can configure it here if you have very special
# needs, such us huge multi/exec requests or alike.
#
# client-query-buffer-limit 1gb
 
# In the Redis protocol, bulk requests, that are, elements representing single
# strings, are normally limited ot 512 mb. However you can change this limit
# here.
#
# proto-max-bulk-len 512mb
 
# Redis calls an internal function to perform many background tasks, like
# closing connections of clients in timeout, purging expired keys that are
# never requested, and so forth.
#
# Not all tasks are performed with the same frequency, but Redis checks for
# tasks to perform according to the specified "hz" value.
#
# By default "hz" is set to 10. Raising the value will use more CPU when
# Redis is idle, but at the same time will make Redis more responsive when
# there are many keys expiring at the same time, and timeouts may be
# handled with more precision.
#
# The range is between 1 and 500, however a value over 100 is usually not
# a good idea. Most users should use the default of 10 and raise this up to
# 100 only in environments where very low latency is required.
hz 10
 
# Normally it is useful to have an HZ value which is proportional to the
# number of clients connected. This is useful in order, for instance, to
# avoid too many clients are processed for each background task invocation
# in order to avoid latency spikes.
#
# Since the default HZ value by default is conservatively set to 10, Redis
# offers, and enables by default, the ability to use an adaptive HZ value
# which will temporary raise when there are many connected clients.
#
# When dynamic HZ is enabled, the actual configured HZ will be used as
# as a baseline, but multiples of the configured HZ value will be actually
# used as needed once more clients are connected. In this way an idle
# instance will use very little CPU time while a busy instance will be
# more responsive.
dynamic-hz yes
 
# When a child rewrites the AOF file, if the following option is enabled
# the file will be fsync-ed every 32 MB of data generated. This is useful
# in order to commit the file to the disk more incrementally and avoid
# big latency spikes.
aof-rewrite-incremental-fsync yes
 
# When redis saves RDB file, if the following option is enabled
# the file will be fsync-ed every 32 MB of data generated. This is useful
# in order to commit the file to the disk more incrementally and avoid
# big latency spikes.
rdb-save-incremental-fsync yes
 
# Redis LFU eviction (see maxmemory setting) can be tuned. However it is a good
# idea to start with the default settings and only change them after investigating
# how to improve the performances and how the keys LFU change over time, which
# is possible to inspect via the OBJECT FREQ command.
#
# There are two tunable parameters in the Redis LFU implementation: the
# counter logarithm factor and the counter decay time. It is important to
# understand what the two parameters mean before changing them.
#
# The LFU counter is just 8 bits per key, it's maximum value is 255, so Redis
# uses a probabilistic increment with logarithmic behavior. Given the value
# of the old counter, when a key is accessed, the counter is incremented in
# this way:
#
# 1. A random number R between 0 and 1 is extracted.
# 2. A probability P is calculated as 1/(old_value*lfu_log_factor+1).
# 3. The counter is incremented only if R < P.
#
# The default lfu-log-factor is 10. This is a table of how the frequency
# counter changes with a different number of accesses with different
# logarithmic factors:
#
# +--------+------------+------------+------------+------------+------------+
# | factor | 100 hits   | 1000 hits  | 100K hits  | 1M hits    | 10M hits   |
# +--------+------------+------------+------------+------------+------------+
# | 0      | 104        | 255        | 255        | 255        | 255        |
# +--------+------------+------------+------------+------------+------------+
# | 1      | 18         | 49         | 255        | 255        | 255        |
# +--------+------------+------------+------------+------------+------------+
# | 10     | 10         | 18         | 142        | 255        | 255        |
# +--------+------------+------------+------------+------------+------------+
# | 100    | 8          | 11         | 49         | 143        | 255        |
# +--------+------------+------------+------------+------------+------------+
#
# NOTE: The above table was obtained by running the following commands:
#
#   redis-benchmark -n 1000000 incr foo
#   redis-cli object freq foo
#
# NOTE 2: The counter initial value is 5 in order to give new objects a chance
# to accumulate hits.
#
# The counter decay time is the time, in minutes, that must elapse in order
# for the key counter to be divided by two (or decremented if it has a value
# less <= 10).
#
# The default value for the lfu-decay-time is 1. A Special value of 0 means to
# decay the counter every time it happens to be scanned.
#
# lfu-log-factor 10
# lfu-decay-time 1
 
########################### ACTIVE DEFRAGMENTATION #######################
#
# WARNING THIS FEATURE IS EXPERIMENTAL. However it was stress tested
# even in production and manually tested by multiple engineers for some
# time.
#
# What is active defragmentation?
# -------------------------------
#
# Active (online) defragmentation allows a Redis server to compact the
# spaces left between small allocations and deallocations of data in memory,
# thus allowing to reclaim back memory.
#
# Fragmentation is a natural process that happens with every allocator (but
# less so with Jemalloc, fortunately) and certain workloads. Normally a server
# restart is needed in order to lower the fragmentation, or at least to flush
# away all the data and create it again. However thanks to this feature
# implemented by Oran Agra for Redis 4.0 this process can happen at runtime
# in an "hot" way, while the server is running.
#
# Basically when the fragmentation is over a certain level (see the
# configuration options below) Redis will start to create new copies of the
# values in contiguous memory regions by exploiting certain specific Jemalloc
# features (in order to understand if an allocation is causing fragmentation
# and to allocate it in a better place), and at the same time, will release the
# old copies of the data. This process, repeated incrementally for all the keys
# will cause the fragmentation to drop back to normal values.
#
# Important things to understand:
#
# 1. This feature is disabled by default, and only works if you compiled Redis
#    to use the copy of Jemalloc we ship with the source code of Redis.
#    This is the default with Linux builds.
#
# 2. You never need to enable this feature if you don't have fragmentation
#    issues.
#
# 3. Once you experience fragmentation, you can enable this feature when
#    needed with the command "CONFIG SET activedefrag yes".
#
# The configuration parameters are able to fine tune the behavior of the
# defragmentation process. If you are not sure about what they mean it is
# a good idea to leave the defaults untouched.
 
# Enabled active defragmentation
# activedefrag yes
 
# Minimum amount of fragmentation waste to start active defrag
# active-defrag-ignore-bytes 100mb
 
# Minimum percentage of fragmentation to start active defrag
# active-defrag-threshold-lower 10
 
# Maximum percentage of fragmentation at which we use maximum effort
# active-defrag-threshold-upper 100
 
# Minimal effort for defrag in CPU percentage
# active-defrag-cycle-min 5
 
# Maximal effort for defrag in CPU percentage
# active-defrag-cycle-max 75
 
# Maximum number of set/hash/zset/list fields that will be processed from
# the main dictionary scan
# active-defrag-max-scan-fields 1000
 
# It is possible to pin different threads and processes of Redis to specific
# CPUs in your system, in order to maximize the performances of the server.
# This is useful both in order to pin different Redis threads in different
# CPUs, but also in order to make sure that multiple Redis instances running
# in the same host will be pinned to different CPUs.
#
# Normally you can do this using the "taskset" command, however it is also
# possible to this via Redis configuration directly, both in Linux and FreeBSD.
#
# You can pin the server/IO threads, bio threads, aof rewrite child process, and
# the bgsave child process. The syntax to specify the cpu list is the same as
# the taskset command:
#
# Set redis server/io threads to cpu affinity 0,2,4,6:
# server_cpulist 0-7:2
#
# Set bio threads to cpu affinity 1,3:
# bio_cpulist 1,3
#
# Set aof rewrite child process to cpu affinity 8,9,10,11:
# aof_rewrite_cpulist 8-11
#
# Set bgsave child process to cpu affinity 1,10,11
# bgsave_cpulist 1,10-11
 
# In some cases redis will emit warnings and even refuse to start if it detects
# that the system is in bad state, it is possible to suppress these warnings
# by setting the following config which takes a space delimited list of warnings
# to suppress
#
# ignore-warnings ARM64-COW-BUG

 启动运行 redis镜像

docker run -p 6379:6379 --name redis \
-v /usr/local/redis/data:/data \
-v /usr/local/redis/conf/redis.conf:/etc/redis/redis.conf \
-d redis:5.0.14 redis-server /etc/redis/redis.conf 

-p 6379:6379指端口映射，访问宿主机端口6379，相当于访问的是redis容器的6379端口，
--name 给容器设置一个名字，若没有设置默为镜像名。
-v 指挂载，比如将 宿主机目录/usr/local/redis/data挂载到容器目录/data
-d 后台运行 
redis:5.0.14 要运行的容器名:版本号
redis-server 在容器中启动redis的命令
/etc/redis/redis.conf 在容器中启动redis的参数

 进入容器 (退出容器用exit)

docker exec -it redis bash

安装Ngnix

在https://hub.docker.com/上搜索 nginx 镜像

 拉取版本指定版本nginx

docker pull nginx:1.22.0

简单启动(这个目的是为了拿到 nginx的默认资源文件，默认会释放到/etc/nginx目录)

docker run --name nginx -d nginx:1.22.0

拷贝容器中安装好的nginx配置文件 到宿主机中

docker cp -a 容器名:容器目录 宿主机目录
#例如
docker cp -a nginx:/etc/nginx /usr/local/nginx

强制卸载刚刚安装的nginx

docker rm -f nginx

 启动运行 nginx镜像

docker run -p 80:80 --restart always --name nginx \
-v /usr/local/nginx/:/etc/nginx/ \
-v /usr/local/nginx/conf.d:/etc/nginx/conf.d \
-d nginx:1.22.0

--restart always  设置容器开机自启动
-p 80:80 指端口映射，访问宿主机端口80，相当于访问的是nginx容器的80端口，
--name 给容器设置一个名字，若没有设置默为镜像名。
-v 指挂载，比如将 宿主机目录/usr/local/nginx/挂载到容器目录/etc/nginx/
-d 后台运行 
nginx:1.22.0 要运行的容器名:版本号

Nginx配置

docker中nginx配置文件 nginx.conf 有一个导入 include /etc/nginx/conf.d/*.conf;(这里地址不是错误的，因为已经挂载到了容器)的操作，说明docker nginx使用了局部配置文件，我们以后要在nginx/conf.d/目录下配置nginx。这里使用的是nginx/conf.d/default.conf

运行3个测试jar包

docker run -p 8901:8901 --name tomcat8901 \
-v /root/servers:/usr/local/tomcat \
-d jdk:8 \
java -jar /usr/local/tomcat/tomcat8901.jar

docker run -p 8902:8902 --name tomcat8902 \
-v /root/servers:/usr/local/tomcat \
-d jdk:8 \
java -jar /usr/local/tomcat/tomcat8902.jar

docker run -p 8903:8903 --name tomcat8903 \
-v /root/servers:/usr/local/tomcat \
-d jdk:8 \
java -jar /usr/local/tomcat/tomcat8903.jar

反向代理负载均衡配置 vi nginx/conf.d/default.conf

upstream myserver{
  server 192.168.111.199:8901;
  server 192.168.111.199:8902;
  server 192.168.111.199:8903;
}

    location / {
        proxy_pass http://myserver;
    }

 

 修改好配置文件后，重启ngingx命令

docker restart nginx

浏览器访问http://192.168.111.199/hello

在容器中运行jar包

第一步：将zikin，sentinel拷贝宿主机指定目录，例如/root/servers目录(servers目录不存在可以自己创建)。
第二步：启动镜像容器，通过java执行运行web服务

清除已经没有使用的容器：docker container prune
查询容器日志：docker container logs 容器id

基于jdk:8镜像启动运行zipkin服务(服务启动后可在宿主机通过localhost:9411进行访问).

docker run -p 9411:9411 --name zipkin \
-v /root/servers:/usr/local/zipkin \
-d jdk:8 \
java -jar /usr/local/zipkin/zipkin-server-2.23.16-exec.jar

请求地址http://192.168.111.199:9411/zipkin/

基于jdk:8镜像启动运行sentinel服务(服务启动后可在宿主机通过localhost:8180进行访问)

docker run -p 8180:8080 --name sentinel \
-v /root/servers:/usr/local/sentinel \
-d jdk:8 \
java -jar /usr/local/sentinel/sentinel-dashboard-1.8.0.jar

请求地址http://192.168.111.199:8180/
用户名/密码：sentinel/sentinel

虚拟网络

二、虚拟网络

容器键互联可以使用 Docker 的虚拟网络来连接。

在 Docker 中可以创建任意多个虚拟网络，容器之间可以通过虚拟网络互联互通。创建虚拟网络时宿主机也会连接到虚拟网络。

 

# 新建虚拟网络 my-net
docker network create my-net
 
# 查看虚拟网络
docker network ls
 
# 查看网络描述信息
docker inspect my-net
 
# 查看宿主机新建的虚拟网卡
ifconfig
 
# 清理容器
docker rm -f $(docker ps -aq)
 
# 新建两个容器 cat1 和 cat2
# 连接到虚拟网络 my-net
docker run -d --name cat1 \
--net my-net \
tomcat
 
docker run -d --name cat2 \
--net my-net \
tomcat
 
# 查看两个容器的虚拟网络ip
docker inspect cat1
docker inspect cat2
 
# 测试网络能否互联互通
# 从宿主机ping两个容器
ping 172.18.0.2
ping 172.18.0.3
 
# 进入cat1，ping宿主机和cat2
docker exec -it cat1 ping 172.18.0.1
docker exec -it cat1 ping 172.18.0.3
# 从容器访问另一个容器，可以使用容器名称访问，容器内部实现了解析环境
docker exec -it cat1 ping cat2