一、docker内存控制
这里还没写好
二、对cpu的控制
1、系统对cpu的控制
1）查看系统的cgroup，cpu和memory
cgroup的介绍：
查看cgroup
[root@foundation38 kiosk]# cd /sys/fs/cgroup/
[root@foundation38 cgroup]# ls
blkio cpu,cpuacct freezer net_cls perf_event
cpu cpuset hugetlb net_cls,net_prio pids
cpuacct devices memory net_prio systemd查看cpu
[root@foundation38 cgroup]# cd cpu
[root@foundation38 cpu]# ls
cgroup.clone_children cpuacct.usage cpu.rt_runtime_us release_agent
cgroup.event_control cpuacct.usage_percpu cpu.shares system.slice
cgroup.procs cpu.cfs_period_us cpu.stat tasks
cgroup.sane_behavior cpu.cfs_quota_us machine.slice user.slice
cpuacct.stat cpu.rt_period_us notify_on_release查看memory
[root@foundation38 cpu]# cd ../memory/
[root@foundation38 memory]# ls
cgroup.clone_children memory.memsw.failcnt
cgroup.event_control memory.memsw.limit_in_bytes
cgroup.procs memory.memsw.max_usage_in_bytes
cgroup.sane_behavior memory.memsw.usage_in_bytes
machine.slice memory.move_charge_at_immigrate
memory.failcnt memory.numa_stat
memory.force_empty memory.oom_control
memory.kmem.failcnt memory.pressure_level
memory.kmem.limit_in_bytes memory.soft_limit_in_bytes
memory.kmem.max_usage_in_bytes memory.stat
memory.kmem.slabinfo memory.swappiness
memory.kmem.tcp.failcnt memory.usage_in_bytes
memory.kmem.tcp.limit_in_bytes memory.use_hierarchy
memory.kmem.tcp.max_usage_in_bytes notify_on_release
memory.kmem.tcp.usage_in_bytes release_agent
memory.kmem.usage_in_bytes system.slice
memory.limit_in_bytes tasks
memory.max_usage_in_bytes user.slice2）、在cpu目录下创建目录，会继承cpu的内容
[root@foundation38 memory]# cd ../cpu
[root@foundation38 cpu]# mkdir x1
[root@foundation38 cpu]# cd x1/
[root@foundation38 x1]# ls
cgroup.clone_children cpuacct.usage_percpu cpu.shares
cgroup.event_control cpu.cfs_period_us cpu.stat
cgroup.procs cpu.cfs_quota_us notify_on_release
cpuacct.stat cpu.rt_period_us tasks
cpuacct.usage cpu.rt_runtime_us
[root@foundation38 x1]# cat cpu.cfs_period_us ##cpu分配的周期（微秒），默认为100000份
100000
[root@foundation38 x1]# cat cpu.cfs_quota_us ##表示该control group限制占用的时间，默认-1不限制
-1[root@foundation38 x1]# echo 20000 > cpu.cfs_quota_us
[root@foundation38 x1]# dd if=/dev/zero of=/dev/null & ##占用资源，
[1] 5071测试
1、使用top查看，会发现占用百分百资源 ##top命令，按1显示cpu，按q退出
2、将限制放入任务中，会变为百分之20
[root@foundation38 x1]# echo 5071 > tasks
2、docker对cpu的控制
1）不限制
[root@foundation38 images]# docker run -it --name vm2 --rm ubuntu
root@ea19644b0ed7:/# dd if=/dev/zero of=/dev/null &
[1] 172）限制
[root@foundation38 images]# docker run -it --name vm1 --cpu-quota=20000 ubuntu
root@bfc257073173:/# dd if=/dev/zero of=/dev/null &
[1] 17
三、磁盘的控制
1、容器权限的提供
1)、原始的容器是没有权限的
[root@foundation38 images]# docker run -it --rm ubuntu
root@c628b3f55ce4:/# fdisk -l
root@9469fd2074da:/# ip addr
1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN group default qlen 1
link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
inet 127.0.0.1/8 scope host lo
valid_lft forever preferred_lft forever
31: eth0@if32: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc noqueue state UP group default
link/ether 02:42:ac:11:00:02 brd ff:ff:ff:ff:ff:ff
inet 172.17.0.2/16 brd 172.17.255.255 scope global eth0
valid_lft forever preferred_lft forever
root@9469fd2074da:/# ip addr add 172.17.0.3/24 dev eth0
RTNETLINK answers: Operation not permitted2）给与所有权限
[root@foundation38 images]# docker run -it --rm --privileged=true ubuntu
root@03a147043820:/# fdisk -lDisk /dev/sda: 320.1 GB, 320072933376 bytes
255 heads, 63 sectors/track, 38913 cylinders, total 625142448 sectors
Units = sectors of 1 * 512 = 512 bytes
Sector size (logical/physical): 512 bytes / 4096 bytes
I/O size (minimum/optimal): 4096 bytes / 4096 bytes
Disk identifier: 0x000d7490 Device Boot Start End Blocks Id System
/dev/sda1 * 2048 617275391 308636672 83 Linux
/dev/sda2 617275392 625141759 3933184 82 Linux swap / Solaris3）只给与网络权限
[root@foundation38 images]# docker run -it --rm --cap-add=NET_ADMIN ubuntu
root@9718a15093f6:/# ip addr add 172.17.0.3/24 dev eth0
root@9718a15093f6:/# ip addr
1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN group default qlen 1
link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
inet 127.0.0.1/8 scope host lo
valid_lft forever preferred_lft forever
33: eth0@if34: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc noqueue state UP group default
link/ether 02:42:ac:11:00:02 brd ff:ff:ff:ff:ff:ff
inet 172.17.0.2/16 brd 172.17.255.255 scope global eth0
valid_lft forever preferred_lft forever
inet 172.17.0.3/24 scope global eth0
valid_lft forever preferred_lft forever
root@9718a15093f6:/#2、磁盘写入速度的限制
[root@foundation38 dev]# docker run -it --rm --device-write-bps /dev/sda:30MB ubuntu
root@539fb0318ea2:/# dd if=/dev/zero of=file bs=1M count=100 oflag=direct
100+0 records in
100+0 records out
104857600 bytes (105 MB) copied, 3.31911 s, 31.6 MB/s3、实现磁盘的分离
1）、安装软件
yum install -y lxcfs-2.0.5-3.el7.centos.x86_64.rpm
[root@server1 ~]# cd /var/lib/lxcfs/
[root@server1 lxcfs]# ls
[root@server1 lxcfs]# cd2）、创建目录
[root@server1 ~]# lxcfs /var/lib/lxcfs/ &
[1] 2733
[root@server1 ~]# hierarchies:
0: fd: 5: devices
1: fd: 6: cpuset
2: fd: 7: memory
3: fd: 8: hugetlb
4: fd: 9: cpuacct,cpu
5: fd: 10: perf_event
6: fd: 11: blkio
7: fd: 12: pids
8: fd: 13: freezer
9: fd: 14: net_prio,net_cls
10: fd: 15: name=systemd[root@server1 ~]# cd /var/lib/lxcfs/
[root@server1 lxcfs]# ls
cgroup proc3）、运行容器并挂载目录，发现容器的磁盘与主机的磁盘隔离
[root@server1 ~]# docker run -it --name vm1 -m 200m -v /var/lib/lxcfs/proc/cpuinfo:/proc/cpuinfo -v /var/lib/lxcfs/proc/diskstats:/proc/diskstats -v /var/lib/lxcfs/proc/meminfo:/proc/meminfo -v /var/lib/lxcfs/proc/stat:/proc/stat -v /var/lib/lxcfs/proc/swaps:/proc/swaps -v /var/lib/lxcfs/proc/uptime:/proc/uptime ubuntu
root@33b59e1f219f:/# free -m
total used free shared buffers cached
Mem: 200 5 194 8 0 0
-/+ buffers/cache: 5 194
Swap: 200 0 200
root@33b59e1f219f:/#
三、docker compose
一群容器的上下线
Docker Compose 将所管理的容器分为三层,工程(project),服务(service)以及容器
(contaienr)。Docker Compose 运行的目录下的所有文件(docker-compose.yml, extends 文
件或环境变量文件等)组成一个工程,若无特殊指定工程名即为当前目录名。一个工程当
中可包含多个服务,每个服务中定义了容器运行的镜像,参数,依赖。一个服务当中可包
括多个容器实例,Docker Compose 并没有解决负载均衡的问题,因此需要借助其他工具实
现服务发现及负载均衡。
Docker Compose 是一个用来创建和运行多容器应用的工具。使用 Compose 首先需要编写
Compose 文件来描述多个容器服务以及之间的关联,然后通过命令根据配置启动所有的容
器。
Dockerfile 可以定义一个容器,而一个 Compose 的模板文件(YAML 格式)可以定义一个
包含多个相互关联容器的应用。Compose 项目使用 python 编写,基于后面的实验中我们
将学习的 Docker API 实现。
1)、将docker-compose放到二进制目录下
[root@server1 ~]# ls
docker lxcfs-2.0.5-3.el7.centos.x86_64.rpm
docker-compose-Linux-x86_64-1.22.0 nginx.tar
haproxy.tar ubuntu.tar
[root@server1 ~]# mv docker-compose-Linux-x86_64-1.22.0 /usr/local/bin/docker-compose
[root@server1 compose]# chmod +x /usr/local/bin/docker-compose2）、创建docker-compose的配置文件
[root@server1 ~]# cd /tmp/
[root@server1 tmp]# ls
[root@server1 tmp]# mkdir docker
[root@server1 tmp]# cd docker/
[root@server1 docker]# mkdir compose
[root@server1 docker]# cd compose/
[root@server1 compose]# vim docker-compose.yml编辑如下
web1:
image: nginx
expose:
- 80
volumes:
- ./web1:/usr/share/nginx/html
web2:
image: nginx
expose:
- 80
volumes:
- ./web2:/usr/share/nginx/html
haproxy:
image: haproxy
volumes:
- ./haproxy/haproxy.cfg:/usr/local/etc/haproxy/haproxy.cfg:ro
links:
- web1
- web2
ports:
- "80:80"
expose:
- "80"
3）编辑各个服务器的目录，并编辑发布目录
web1和web2的默认发布目录
[root@server1 compose]# mkdir web1
[root@server1 compose]# mkdir web2
[root@server1 compose]# echo web1 > web1/index.html
[root@server1 compose]# echo web2 > web2/index.html
[root@server1 compose]# ls web1/
index.htmlhaproxy的目录
[root@server1 compose]# mkdir haproxy
[root@server1 compose]# cd haproxy/
[root@server1 haproxy]# vim haproxy.cfg编辑如下
global
log 127.0.0.1 local0
log 127.0.0.1 local1 noticedefaults
log global
mode http
option httplog
option dontlognull
timeout connect 5000ms
timeout client 50000ms
timeout server 50000ms
stats uri /statusfrontend balancer
bind 0.0.0.0:80
default_backend web_backendsbackend web_backends
balance roundrobin
server server1 web1:80 check
server server2 web2:80 check [root@server1 haproxy]# cd ..
[root@server1 compose]# pwd
/tmp/docker/compose
[root@server1 compose]# ls
docker-compose.yml haproxy web1 web2
4）加载镜像
[root@server1 compose]# cd
[root@server1 ~]# docker load -i nginx.tar
Loaded image: nginx:latest
[root@server1 ~]# docker load -i haproxy.tar
[root@server1 ~]# docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
nginx latest e548f1a579cf 13 months ago 109MB
westos.org/nginx latest e548f1a579cf 13 months ago 109MB
westos.org/game2048 latest 19299002fdbe 2 years ago 55.5MB
haproxy latest fbd1f55f79b3 3 years ago 139MB
ubuntu latest 07c86167cdc4 3 years ago 188MB5）启动docker-compose
[root@server1 ~]# cd -
/tmp/docker/compose
[root@server1 compose]# docker-compose up -d
Creating compose_web1_1 ... done
Creating compose_web2_1 ... done
Creating compose_haproxy_1 ... done查看日志
[root@server1 compose]# docker-compose logs
Attaching to compose_haproxy_1, compose_web2_1, compose_web1_1
haproxy_1 | <7>haproxy-systemd-wrapper: executing /usr/local/sbin/haproxy -p /run/haproxy.pid -f /usr/local/etc/haproxy/haproxy.cfg -Ds测试：
1、访问172.25.38.1，实现论寻
2、访问172.25.38.1/status 查看状态
3、关闭，删除与重新设定
[root@server1 compose]# docker-compose stop
Stopping compose_haproxy_1 ... done
Stopping compose_web2_1 ... done
Stopping compose_web1_1 ... done[root@server1 compose]# docker-compose rm
Going to remove compose_haproxy_1, compose_web2_1, compose_web1_1
Are you sure? [yN] y
Removing compose_haproxy_1 ... done
Removing compose_web2_1 ... done
Removing compose_web1_1 ... done[root@server1 compose]# docker-compose up -d
Creating compose_web1_1 ... done
Creating compose_web2_1 ... done
Creating compose_haproxy_1 ... done五、docker swam 集群
docker公司的三剑客：
- Docker Machine
- Docker Compose
- Docker Swarm
1、集群搭建实现论寻
1)初始化swarm
[root@server1 ~]# docker swarm init
Swarm initialized: current node (ww7t8yqzki2y98lbt4uu3ccoc) is now a manager.To add a worker to this swarm, run the following command:
docker swarm join --token SWMTKN-1-4yt97m3e0pax24k4bz31cvngcxkpekjz1d07m68dt1oyiao8h6-4mf26myoh7d6f5pvfte92vadb 172.25.38.1:2377
To add a manager to this swarm, run 'docker swarm join-token manager' and follow the instructions.2）加入节点
[root@server2 ~]# docker swarm join --token SWMTKN-1-4yt97m3e0pax24k4bz31cvngcxkpekjz1d07m68dt1oyiao8h6-4mf26myoh7d6f5pvfte92vadb 172.25.38.1:2377
This node joined a swarm as a worker.[root@server3 ~]# docker swarm join --token SWMTKN-1-4yt97m3e0pax24k4bz31cvngcxkpekjz1d07m68dt1oyiao8h6-4mf26myoh7d6f5pvfte92vadb 172.25.38.1:2377
This node joined a swarm as a worker.查看节点
[root@server1 ~]# docker node ls
ID HOSTNAME STATUS AVAILABILITY MANAGER STATUS ENGINE VERSION
ww7t8yqzki2y98lbt4uu3ccoc * server1 Ready Active Leader 18.06.1-ce
ow4ovviw59r7atnwy0aibin5i server2 Ready Active 18.06.1-ce
j2dw9g4kbuw5ttf91i48ffhtj server3 Ready Active 18.06.1-ce
yum install -y bridge-utils
[root@server1 ~]# brctl show
bridge name bridge id STP enabled interfaces
docker0 8000.024288de750f no
docker_gwbridge 8000.0242ce2f3f24 no veth19e11d1
veth5c13cf63）创建server集群
创建自己使用的网络
[root@server1 ~]# docker network create -d overlay my_net1
xhvxuojeoj70ce4lk7bwgqz09创建集群
[root@server1 ~]# docker service create --name web --network my_net1 --publish 80:80 --replicas 3 nginx
image nginx:latest could not be accessed on a registry to record
its digest. Each node will access nginx:latest independently,
possibly leading to different nodes running different
versions of the image.4hjwk703scdph55pyhmzsqa7f
overall progress: 3 out of 3 tasks
1/3: running
2/3: running
3/3: running
verify: Service converged [root@server1 ~]# docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
87ac069e074a nginx:latest "nginx -g 'daemon of…" 37 seconds ago Up 31 seconds 80/tcp web.3.jf1vo5t6dtn7alx392augzpvl
[root@server1 ~]vim index.html
[root@server1 ~]# docker cp index.html 87ac069e074a:/usr/share/nginx/html [root@server2 ~]# docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
ce594e709682 nginx:latest "nginx -g 'daemon of…" About a minute ago Up About a minute 80/tcp web.1.lvdauqh8es80uyztenlawfcmt
[root@server2 ~]vim index.html
[root@server2 ~]# docker cp index.html ce594e709682:/usr/share/nginx/html[root@server3 ~]# docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
acf39493ac1b nginx:latest "nginx -g 'daemon of…" About a minute ago Up About a minute 80/tcp web.2.akmftvlbc02m3kjl19m1agplq
[root@server3 ~]vim index.html
[root@server3 ~]# docker cp index.html acf39493ac1b:/usr/share/nginx/html测试：
注意关闭防火墙
[root@foundation38 images]# for i in {1..10}; do curl 172.25.38.1; done
<h1>server1</h1>
<h1>server3</h1>
<h1>server2</h1>
<h1>server1</h1>
<h1>server3</h1>
<h1>server2</h1>
<h1>server1</h1>
<h1>server3</h1>
<h1>server2</h1>
<h1>server1</h1>2、对集群的监控
1）载入镜像
[root@server1 ~]# docker load -i visualizer.tar
5bef08742407: Loading layer 4.221MB/4.221MB
5f70bf18a086: Loading layer 1.024kB/1.024kB
0a19bde117a5: Loading layer 60.01MB/60.01MB
f7e883283ebc: Loading layer 3.942MB/3.942MB
dfd8ee95c7e7: Loading layer 1.536kB/1.536kB
300a6cad969a: Loading layer 8.704kB/8.704kB
d1627040da6d: Loading layer 489kB/489kB
00ed018016c5: Loading layer 2.56kB/2.56kB
d5aa1ab1b431: Loading layer 4.096kB/4.096kB
2d6a463420f7: Loading layer 4.608kB/4.608kB
53888d7f4cca: Loading layer 2.56kB/2.56kB
ea93ed99abca: Loading layer 2.598MB/2.598MB
fa467b43abc0: Loading layer 4.096kB/4.096kB
94cd25765710: Loading layer 96.48MB/96.48MB
Loaded image: dockersamples/visualizer:latest
2）创立监控容器
[root@server1 ~]# docker service create \
> --name=viz \
> --publish=8080:8080/tcp \
> --constraint=node.role==manager \
> --mount=type=bind,src=/var/run/docker.sock,dst=/var/run/docker.sock \
> dockersamples/visualizer
image dockersamples/visualizer:latest could not be accessed on a registry to record
its digest. Each node will access dockersamples/visualizer:latest independently,
possibly leading to different nodes running different
versions of the image.6xyuht1m47qecekwsxzf9nlxm
overall progress: 1 out of 1 tasks
1/1: running
verify: Service converged3）查看容器
[root@server1 ~]# docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
5344c9353ebf dockersamples/visualizer:latest "npm start" About a minute ago Up About a minute (healthy) 8080/tcp viz.1.poim25hfey3doplbaq4drp8sp
87ac069e074a nginx:latest "nginx -g 'daemon of…" 10 minutes ago Up 10 minutes 80/tcp web.3.jf1vo5t6dtn7alx392augzpvl测试：
1、访问：172.25.38.1：8080
2、修改服务的规模为6
[root@server1 ~]# docker service scale web=6
web scaled to 6
overall progress: 6 out of 6 tasks
1/6: running
2/6: running
3/6: running
4/6: running
5/6: running
6/6: running
verify: Service converged查看监控
3、更新服务内容
1）重命名镜像，模拟新的服务
[root@server1 ~]# docker tag nginx:latest nginx2:v22）更新服务
--update-delay 5s ##每5秒更新一次
--update-parallelism 2 web ##每次更新两个[root@server1 ~]# docker service update --image nginx2:v2 --update-delay 5s --update-parallelism 2 web
image nginx2:v2 could not be accessed on a registry to record
its digest. Each node will access nginx2:v2 independently,
possibly leading to different nodes running different
versions of the image.web
overall progress: 6 out of 6 tasks
1/6: running
2/6: running
3/6: running
4/6: running
5/6: running
6/6: running
verify: Service converged在服务中查看监控：
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六、k8s
kubernetes，简称K8s，是用8代替8个字符 “ubernete”而成的缩写。是一个开源的，用于管理云平台中多个主机上的容器化的应用，Kubernetes的目标是让部署容器化的应用简单并且高 效（powerful）,Kubernetes提供了应用部署，规划，更新，维护的一种机制。 [1]
传统的应用部署方式是通过插件或脚本来安装应用。这样做的缺点是应用的运行、配置、管理、所有生存周期将与当前操作系统绑定，这样做并不利于应用的升级更新/回滚等操作，当然也可以通过创建虚拟机的方式来实现某些功能，但是虚拟机非常重，并不利于可移植性。
新的方式是通过部署容器方式实现，每个容器之间互相隔离，每个容器有自己的文件系统 ，容器之间进程不会相互影响，能区分计算资源。相对于虚拟机，容器能快速部署，由于容器与底层设施、机器文件系统解耦的，所以它能在不同云、不同版本操作系统间进行迁移。
容 器占用资源少、部署快，每个应用可以被打包成一个容器镜像，每个应用与容器间成一对一关系也使容器有更大优势，使用容器可以在build或release 的阶段，为应用创建容器镜像，因为每个应用不需要与其余的应用堆栈组合，也不依赖于生产环境基础结构，这使得从研发到测试、生产能提供一致环境。类似地， 容器比虚拟机轻量、更“透明”，这更便于监控和管理。
实验环境：删除源先的docker swarm
[root@server2 anzhuangbao]# docker swarm leave
Node left the swarm.[root@server3 anzhuangbao]# docker swarm leave
Node left the swarm.[root@server1 ~]# docker swarm leave --force
Node left the swarm.[root@server3 tar]# docker container prune1、server1，2，3.安装 kubeadm
[root@server1 ~]# yum install -y kubeadm-1.12.2-0.x86_64.rpm kubelet-1.12.2-0.x86_64.rpm kubectl-1.12.2-0.x86_64.rpm kubernetes-cni-0.6.0-0.x86_64.rpm cri-tools-1.12.0-0.x86_64.rpm2、server1，2，3.关闭swapoff,开机启动，载入镜像
[root@server1 ~]# swapoff -a
[root@server1 ~]# vim /etc/fstab ##
#/dev/mapper/rhel-swap swap swap defaults 0 0
[root@server1 ~]# df -h[root@server1 ~]# systemctl enable kubelet.service
Created symlink from /etc/systemd/system/multi-user.target.wants/kubelet.service to /etc/systemd/system/kubelet.service.
[root@server1 ~]# systemctl start kubelet.service[root@server1 ~]# kubeadm config images list
I0323 16:50:43.447921 16529 version.go:93] could not fetch a Kubernetes version from the internet: unable to get URL "https://dl.k8s.io/release/stable-1.txt": Get https://dl.k8s.io/release/stable-1.txt: net/http: request canceled while waiting for connection (Client.Timeout exceeded while awaiting headers)
I0323 16:50:43.448006 16529 version.go:94] falling back to the local client version: v1.12.2
k8s.gcr.io/kube-apiserver:v1.12.2
k8s.gcr.io/kube-controller-manager:v1.12.2
k8s.gcr.io/kube-scheduler:v1.12.2
k8s.gcr.io/kube-proxy:v1.12.2
k8s.gcr.io/pause:3.1
k8s.gcr.io/etcd:3.2.24
k8s.gcr.io/coredns:1.2.2加载镜像
11 docker load -i coredns.tar
12 docker load -i kube-apiserver.tar
13 docker load -i kube-scheduler.tar
14 docker load -i etcd.tar
15 docker load -i kube-controller-manager.tar
16 docker load -i pause.tar
17 docker load -i kube-proxy.tar
18 docker load -i flannel.tar
3、初始化
[root@server1 ~]# kubeadm init --pod-network-cidr=10.244.0.0/16 --apiserver-advertise-address=172.25.38.1
Your Kubernetes master has initialized successfully!
To start using your cluster, you need to run the following as a regular user:
mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/configYou should now deploy a pod network to the cluster.
Run "kubectl apply -f [podnetwork].yaml" with one of the options listed at:
https://kubernetes.io/docs/concepts/cluster-administration/addons/You can now join any number of machines by running the following on each node
as root: kubeadm join 172.25.85.1:6443 --token fkpqn8.1ws2abhq7qrakw59 --discovery-token-ca-cert-hash sha256:aa71b8de1a85d55f884b29544e2cf7f76387e0b25b4dc8a3eca22d1988d482694、创建用户，添加用户
[root@server1 k8s]# useradd k8s
[root@server1 k8s]# vim /etc/sudoers 91 root ALL=(ALL) ALL
92 k8s ALL=(ALL) NOPASSWD: ALL5、按照kubeadm初始化后的指令来做
[root@server1 k8s]# su k8s
[k8s@server1 k8s]$ cd
[k8s@server1 ~]$ mkdir -p $HOME/.kube
[k8s@server1 ~]$ sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
[k8s@server1 ~]$ sudo chown $(id -u):$(id -g) $HOME/.kube/config
[k8s@server1 ~]$ echo " source < (kubectl completion bash)" >> ./.bashrc
[k8s@server1 ~]$ vim .bashrc
source <(kubectl completion bash)6、复制并运行.yml文件
[root@server1 k8s]# cp *.yml /home/k8s/
[k8s@server1 ~]$ kubectl apply -f kube-flannel.yml
clusterrole.rbac.authorization.k8s.io/flannel created
clusterrolebinding.rbac.authorization.k8s.io/flannel created
serviceaccount/flannel created
configmap/kube-flannel-cfg created
daemonset.extensions/kube-flannel-ds-amd64 created
daemonset.extensions/kube-flannel-ds-arm64 created
daemonset.extensions/kube-flannel-ds-arm created
daemonset.extensions/kube-flannel-ds-ppc64le created
daemonset.extensions/kube-flannel-ds-s390x created发现多了几个容器
[k8s@server1 ~]$ sudo docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
d53a57cf8108 k8s.gcr.io/pause:3.1 "/pause" 7 seconds ago Up 2 seconds k8s_POD_coredns-576cbf47c7-f8lqt_kube-system_7aa9ab95-4d69-11e9-86e8-5254007c8875_0
133a87918ec7 k8s.gcr.io/pause:3.1 "/pause" 7 seconds ago Up 2 seconds k8s_POD_coredns-576cbf47c7-b7lp7_kube-system_7a794351-4d69-11e9-86e8-5254007c8875_07、server2和3添加节点
server2
[root@server2 tar]# kubeadm join 172.25.85.1:6443 --token fkpqn8.1ws2abhq7qrakw59 --discovery-token-ca-cert-hash sha256:aa71b8de1a85d55f884b29544e2cf7f76387e0b25b4dc8a3eca22d1988d48269
[root@server2 tar]# modprobe ip_vs_wrr ip_vs_sh
server3
[root@server3 tar]# modprobe ip_vs_wrr
[root@server3 tar]# modprobe ip_vs_sh
[root@server3 tar]# kubeadm join 172.25.85.1:6443 --token fkpqn8.1ws2abhq7qrakw59 --discovery-token-ca-cert-hash sha256:aa71b8de1a85d55f884b29544e2cf7f76387e0b25b4dc8a3eca22d1988d48269测试
1、查看节点
[k8s@server1 ~]$ kubectl get nodes
NAME STATUS ROLES AGE VERSION
server1 Ready master 26m v1.12.2
server2 Ready <none> 3m37s v1.12.2
server3 Ready <none> 34s v1.12.22、查看命名空间
[k8s@server1 ~]$ kubectl get pod --all-namespaces
NAMESPACE NAME READY STATUS RESTARTS AGE
kube-system etcd-server1 1/1 Running 0 34m
kube-system kube-apiserver-server1 1/1 Running 0 35m
kube-system kube-controller-manager-server1 1/1 Running 3 35m
kube-system kube-flannel-ds-amd64-5hx9c 1/1 Running 1 10m
kube-system kube-flannel-ds-amd64-m74vx 1/1 Running 0 15m
kube-system kube-flannel-ds-amd64-nvdtx 1/1 Running 0 13m
kube-system kube-proxy-2cv2c 1/1 Running 0 35m
kube-system kube-proxy-6q7cn 1/1 Running 0 10m
kube-system kube-proxy-mklts 1/1 Running 0 13m
kube-system kube-scheduler-server1 1/1 Running 4 34m注意
这里要保证有网络，如果出现如下，可以删除节点，自动添加查看
[k8s@server1 ~]$ kubectl get pod --all-namespaces
NAMESPACE NAME READY STATUS RESTARTS AGE
kube-system coredns-576cbf47c7-b7lp7 0/1 CrashLoopBackOff 5 26m
kube-system coredns-576cbf47c7-f8lqt 0/1 CrashLoopBackOff 5 26m
kube-system etcd-server1 1/1 Running 0 25m
kube-system kube-apiserver-server1 1/1 Running 0 26m
kube-system kube-controller-manager-server1 1/1 Running 1 26m
kube-system kube-flannel-ds-amd64-5hx9c 1/1 Running 1 95s
kube-system kube-flannel-ds-amd64-m74vx 1/1 Running 0 7m
kube-system kube-flannel-ds-amd64-nvdtx 1/1 Running 0 4m36s
kube-system kube-proxy-2cv2c 1/1 Running 0 26m
kube-system kube-proxy-6q7cn 1/1 Running 0 95s
kube-system kube-proxy-mklts 1/1 Running 0 4m36s
kube-system kube-scheduler-server1 1/1 Running 1 25m[k8s@server1 ~]$ kubectl describe pod coredns-576cbf47c7-b7lp7 -n kube-system ##查看信息
[k8s@server1 ~]$ kubectl logs coredns-576cbf47c7-b7lp7 -n kube-system ##查看日志
[k8s@server1 ~]$ kubectl delete pod coredns-576cbf47c7-b7lp7 -n kube-system ##删除节点
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