Linux下 Docker容器引擎基础（2）

目录

创建私有仓库

将修改过的nginx镜像做标记封装，准备上传到私有仓库

将镜像上传到私有仓库

从私有仓库中下载镜像到本地

CPU使用率

CPU共享比例

CPU周期限制

CPU 配额控制参数的混合案例

内存限制

Block IO 的限制

限制bps 和iops

---

创建私有仓库

仓库（Repository）是集中存放镜像的地方。

仓库注册服务器才是存放仓库具体的服务器（Registry），每个服务器上都可以放置多个仓库，而每个仓库下可以放置多个镜像，每个镜像上可以运行多个容器，每个容器上可以跑一个应用或应用组。

安装docker后，可以通过官方提供的registry镜像部署一套本地的私有仓库环境

[root@localhost ~]# mkdir -p /opt/data/registry

[root@localhost ~]# docker run -d --restart=always -p 5000:5000 -v /opt/data/registry:/tmp/registry registry

Unable to find image 'registry:latest' locally

Trying to pull repository docker.io/library/registry ...

latest: Pulling from docker.io/library/registry

79e9f2f55bf5: Pull complete

0d96da54f60b: Pull complete

5b27040df4a2: Pull complete

e2ead8259a04: Pull complete

3790aef225b9: Pull complete

Digest: sha256:169211e20e2f2d5d115674681eb79d21a217b296b43374b8e39f97fcf866b375

Status: Downloaded newer image for docker.io/registry:latest

a0edf5ac6cdda7464855c98db855c60f32f54bf8f078647dc2b8357aa8581151

[root@localhost ~]# docker ps -l

CONTAINER ID        IMAGE               COMMAND                  CREATED             STATUS              PORTS                    NAMES

a0edf5ac6cdd        registry            "/entrypoint.sh /e..."   31 seconds ago      Up 29 seconds       0.0.0.0:5000->5000/tcp   thirsty_ptolemy

准备测试镜像

[root@localhost ~]# docker run -d -p 8000:80 nginx     //将宿主机8000端口映射给容器的业务端口

ea26add1a77cd25a90041acfd3b0994630cecc098de2ed15f088be9b4fa8335a

[root@localhost ~]# docker ps -l

CONTAINER ID        IMAGE               COMMAND                  CREATED             STATUS              PORTS                  NAMES

ea26add1a77c        nginx               "/docker-entrypoin..."   9 seconds ago       Up 8 seconds        0.0.0.0:8000->80/tcp   nifty_knuth

宿主机访问8000端口测试：

[root@localhost ~]# docker logs  ea26add1a77c

[root@localhost ~]# docker tag nginx 192.168.50.59:5000/nginx-awd

将修改过的nginx镜像做标记封装，准备上传到私有仓库

[root@localhost ~]# cat /etc/docker/daemon.json

{

        "registry-mirrors":[ "https://nyakyfun.mirror.aliyuncs.com" ]

}

[root@localhost ~]# vim /etc/docker/daemon.json

{

        "registry-mirrors":[ "https://nyakyfun.mirror.aliyuncs.com" ],"insecure-registries":["192.168.50.59:5000"]

}

[root@localhost ~]# systemctl daemon-reload

[root@localhost ~]# systemctl restart docker

将镜像上传到私有仓库

[root@localhost ~]# docker push 192.168.50.59:5000/nginx-awd

The push refers to a repository [192.168.50.59:5000/nginx-awd]

d874fd2bc83b: Pushed

32ce5f6a5106: Pushed

f1db227348d0: Pushed

b8d6e692a25e: Pushed

e379e8aedd4d: Pushed

2edcec3590a4: Pushed

latest: digest: sha256:ee89b00528ff4f02f2405e4ee221743ebc3f8e8dd0bfd5c4c20a2fa2aaa7ede3 size: 1570

查看

[root@localhost ~]# docker images

REPOSITORY                     TAG                 IMAGE ID            CREATED             SIZE

centos                         exp                 c85e59d0ca2f        23 hours ago        231 MB

192.168.50.59:5000/nginx-awd   latest              605c77e624dd        19 months ago       141 MB

删除掉测试

[root@localhost ~]# docker rmi 192.168.50.59:5000/nginx-awd

Untagged: 192.168.50.59:5000/nginx-awd:latest

Untagged: 192.168.50.59:5000/nginx-awd@sha256:ee89b00528ff4f02f2405e4ee221743ebc3f8e8dd0bfd5c4c20a2fa2aaa7ede3

[root@localhost ~]# docker images

REPOSITORY           TAG                 IMAGE ID            CREATED             SIZE

centos               exp                 c85e59d0ca2f        23 hours ago        231 MB

docker.io/nginx      latest              605c77e624dd        19 months ago       141 MB

docker.io/registry   latest              b8604a3fe854        20 months ago       26.2 MB

docker.io/centos     latest              5d0da3dc9764        22 months ago       231 MB

从私有仓库中下载镜像到本地

[root@localhost ~]# docker pull 192.168.50.59:5000/nginx-awd

Using default tag: latest

Trying to pull repository 192.168.50.59:5000/nginx-awd ...

latest: Pulling from 192.168.50.59:5000/nginx-awd

Digest: sha256:ee89b00528ff4f02f2405e4ee221743ebc3f8e8dd0bfd5c4c20a2fa2aaa7ede3

Status: Downloaded newer image for 192.168.50.59:5000/nginx-awd:latest

[root@localhost ~]# docker images

REPOSITORY                     TAG                 IMAGE ID            CREATED             SIZE

centos                         exp                 c85e59d0ca2f        23 hours ago        231 MB

192.168.50.59:5000/nginx-awd   latest              605c77e624dd        19 months ago       141 MB

Docker资源限制

Docker容器技术底层是通过Cgroup（Control Group 控制组）实现容器对物理资源使用的限制，限制的资源包括CPU、内存、磁盘三个方面。基本覆盖了常见的资源配额和使用量控制。

Cgroup 是Linux 内核提供的一种可以限制、记录、隔离进程组所使用的物理资源的机制，被LXC及Docker等很多项目用于实现进程的资源控制。

Cgroup 是提供将进程进行分组化管理的功能和接口的基础结构，Docker中I/O 或内存的分配控制等具体的资源管理功能都是通过Cgroup功能来实现的。这些具体的资源管理功能称为Cgroup子系统

使用下面的Dockerfile 来创建一个基于CentOS的stress工具镜像。

[root@localhost ~]# cat centos-7-x86_64.tar.gz | docker import - centos:7

sha256:6e593ec2c4f80e5d44cd15d978c59c701f02b72b1c7458778854a6dc24d492b8

[root@localhost ~]# mkdir stress

[root@localhost ~]# vim stress/Dockerfile

FROM centos:7

MAINTAINER crushlinux "[email protected]"

RUN yum -y install wget

RUN wget -O /etc/yum.repos.d/epel.repo http://mirrors.aliyun.com/repo/epel-7.repo

RUN yum -y install stress

~         

[root@localhost ~]# cd stress/

[root@localhost stress]# docker build -t centos:stress .

CPU使用率

[root@localhost stress]#  docker run -itd centos:stress /bin/bash

9d9428089027bf70bf2b4e6a441cab0d465c2f5dd3988420b05c7149d4a9ff3d

                

utes ago                              suspicious_franklin

[root@localhost stress]# docker ps -a

CONTAINER ID        IMAGE               COMMAND                  CREATED             STATUS                        PORTS                    NAMES

9d9428089027        centos:stress       "/bin/bash"              39 seconds ago      Up 38 seconds                                          silly_mestorf

[root@localhost stress]# vim /sys/fs/cgroup/cpu,cpuacct/cpu.cfs_quota_us

-1

CPU共享比例

当多个容器任务运行时，很难计算CPU的使用率，为了使容器合理使用CPU资源，可以通过--cpu-shares选项设置容器按比例共享CPU资源，这种方式还可以实现CPU使用率的动态调整。

命令中的--cpu-shares 选项值不能保证可以获得1 个vcpu 或者多少GHz 的CPU 资源，仅仅只是一个弹性的加权值。

[root@localhost ~]# docker run --name aa -itd --cpu-shares 1024 centos:stress /bin/bash

1c9d6552e940da713e8ce89c9b10f045aff0b1fcbfdef45f2f9bf1d2189c4604

[root@localhost ~]# docker run --name bb -itd --cpu-shares 1024 centos:stress /bin/bash

4a7ea87192d16d4b8b086c125a467357f28aed00157726367cefea7fada12a21

[root@localhost ~]# docker run --name cc -itd --cpu-shares 2048 centos:stress /bin/bash

7b52275fa1b3c00b1bcbbb5ef6ef165f4b33bc5ccab51908b66e19b7f50fe772

[root@localhost ~]# docker run --name dd -itd --cpu-shares 4096 centos:stress /bin/bash

b56f55536170be6ac5bf25b6e1350e126c05fc44cf54d954a7c9d679ef73c110

默认情况下，每个docker容器的cpu份额都是1024。单独一个容器的份额是没有意义的。只有在同时运行多个容器时，容器的CPU加权的效果才能体现出来。例如，两个容器A、B的CPU份额分别为1000和500，在CPU进行时间片分配的时候，容器A比容器B多一倍的机会获得CPU的时间片。但分配的结果取决于当时主机和其他容器的运行状态，实际上也无法保证容器A一定能获得CPU时间片。比如容器A的进程一直是空闲的，那么容器B 是可以获取比容器A更多的CPU时间片的。极端情况下，比如说主机上只运行了一个容器，即使它的CPU份额只有50，它也可以独占整个主机的CPU资源。

换句话说,可以通过cpu shares可以设置容器使用CPU的优先级，比如启动了两个容器及运行查看CPU使用百分比。

[root@localhost ~]# docker run -tid --name cpu1024 --cpu-shares 1024 centos:stress stress -c 10

3aa4978e3257d760b66b8d85a9c78257e982fcff593f4211880a914a59978603

[root@localhost ~]# docker run -tid --name cpu512 --cpu-shares 512 centos:stress stress -c 10

[root@localhost ~]# docker ps -a

CONTAINER ID        IMAGE               COMMAND             CREATED              STATUS              PORTS               NAMES

3aa4978e3257        centos:stress       "stress -c 10"      About a minute ago   Up About a minute                       cpu1024

8a0048522072        centos:stress       "stress -c 10"      2 minutes ago        Up 2 minutes                            cpu512

[root@localhost ~]# docker exec -it 3a /bin/bash

[root@3aa4978e3257 /]# top

top - 02:46:44 up  5:45,  0 users,  load average: 19.34, 10.07, 4.21

Tasks:  13 total,  11 running,   2 sleeping,   0 stopped,   0 zombie

%Cpu(s): 98.6 us,  1.4 sy,  0.0 ni,  0.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st

KiB Mem :  3861056 total,   846756 free,   292556 used,  2721744 buff/cache

KiB Swap:  2097148 total,  2097148 free,        0 used.  2961824 avail Mem

   PID USER      PR  NI    VIRT    RES    SHR S %CPU %MEM     TIME+ COMMAND                           

    11 root      20   0    7260     92      0 R  7.0  0.0   0:11.83 stress                            

    14 root      20   0    7260     92      0 R  7.0  0.0   0:11.84 stress                            

     6 root      20   0    7260     92      0 R  6.7  0.0   0:11.83 stress                            

     7 root      20   0    7260     92      0 R  6.7  0.0   0:11.83 stress                            

     8 root      20   0    7260     92      0 R  6.7  0.0   0:11.84 stress                            

     9 root      20   0    7260     92      0 R  6.7  0.0   0:11.84 stress                            

    10 root      20   0    7260     92      0 R  6.3  0.0   0:11.83 stress                            

    12 root      20   0    7260     92      0 R  6.3  0.0   0:11.82 stress                            

    13 root      20   0    7260     92      0 R  6.3  0.0   0:11.83 stress                            

    15 root      20   0    7260     92      0 R  6.3  0.0   0:11.83 stress                            

     1 root      20   0    7260    640    548 S  0.0  0.0   0:00.01 stress                            

    16 root      20   0   11748   1796   1444 S  0.0  0.0   0:00.01 bash                              

    31 root      20   0   51872   1940   1408 R  0.0  0.1   0:00.00 top                               

 开启了10 个stress 进程，目的是充分让系统资源变得紧张。只有这样竞争资源，设定的资源比例才可以显现出来。如果只运行一个进行，会自动分配到空闲的CPU，这样比例就无法看出来。由于案例的环境不一样，可能导致上面两张图中占用CPU 百分比会不同，但是从cpu share 来看两个容器总比例一定会是1:2。

[root@localhost ~]# docker exec -it 8a /bin/bash

[root@8a0048522072 /]# top

top - 02:47:53 up  5:47,  0 users,  load average: 20.04, 12.21, 5.38

Tasks:  13 total,  11 running,   2 sleeping,   0 stopped,   0 zombie

%Cpu(s): 98.2 us,  1.8 sy,  0.0 ni,  0.0 id,  0.0 wa,  0.0 hi,  0.0 si,  0.0 st

KiB Mem :  3861056 total,   846756 free,   292548 used,  2721752 buff/cache

KiB Swap:  2097148 total,  2097148 free,        0 used.  2961828 avail Mem

   PID USER      PR  NI    VIRT    RES    SHR S %CPU %MEM     TIME+ COMMAND                           

     9 root      20   0    7260     92      0 R  3.7  0.0   0:15.21 stress                            

    12 root      20   0    7260     92      0 R  3.7  0.0   0:15.21 stress                            

    14 root      20   0    7260     92      0 R  3.7  0.0   0:15.20 stress                            

     6 root      20   0    7260     92      0 R  3.3  0.0   0:15.20 stress                            

     7 root      20   0    7260     92      0 R  3.3  0.0   0:15.19 stress                            

    10 root      20   0    7260     92      0 R  3.3  0.0   0:15.20 stress                            

    13 root      20   0    7260     92      0 R  3.3  0.0   0:15.19 stress                            

    15 root      20   0    7260     92      0 R  3.3  0.0   0:15.21 stress                            

     8 root      20   0    7260     92      0 R  3.0  0.0   0:15.19 stress                            

    11 root      20   0    7260     92      0 R  3.0  0.0   0:15.19 stress                            

     1 root      20   0    7260    640    548 S  0.0  0.0   0:00.01 stress                            

    16 root      20   0   11772   1896   1500 S  0.0  0.0   0:00.01 bash                              

31 root      20   0   51872   1944   1408 R  0.0  0.1   0:00.00 top   

CPU周期限制

cpu-period 和cpu-quota 的单位为微秒（μs）。cpu-period 的最小值为1000 微秒，

最大值为1 秒（10^6 μs），默认值为0.1 秒（100000 μs）。cpu-quota 的值默认为-1，

表示不做控制。cpu-period、cpu-quota 这两个参数一般联合使用。

[root@localhost ~]#  docker run -it --cpu-period 100000 --cpu-quota 200000 centos:stress /bin/bash

          [root@67f52c4e2d20 /]# cat /sys/fs/cgroup/cpu/cpu.cfs_period_us

100000

[root@67f52c4e2d20 /]# cat /sys/fs/cgroup/cpu/cpu.cfs_quota_us  

200000

CPU 配额控制参数的混合案例

通过--cpuset-cpus 指定容器A 使用CPU 内核0，容器B 只是用CPU 内核1。在主机上只有这两个容器使用对应CPU 内核的情况，它们各自占用全部的内核资源，--cpu-shares 没有明显效果。

--cpuset-cpus、--cpuset-mems 参数只在多核、多内存节点上的服务器上有效，并且必须与实际的物理配置匹配，否则也无法达到资源控制的目的。

在系统具有多个CPU 内核的情况下，需要通过cpuset-cpus 为容器CPU 内核才能比较方便地进行测试。

[root@localhost ~]# docker run -itd --name cpu0 --cpuset-cpus 0 --cpu-shares 512 centos:stress stress -c 1

d3734959ddb9a118d857a5d7d35b426b697b3d6a09670e6041096a74c17b6c4f

[root@localhost ~]# docker ps -a

CONTAINER ID        IMAGE               COMMAND             CREATED              STATUS              PORTS               NAMES

d3734959ddb9        centos:stress       "stress -c 1"       About a minute ago   Up 1 second                             cpu0

[root@localhost ~]# docker exec -it d37 /bin/bash

[root@d3734959ddb9 /]# top

top - 06:25:23 up  3:32,  0 users,  load average: 0.42, 0.20, 0.48

Tasks:   4 total,   2 running,   2 sleeping,   0 stopped,   0 zombie

%Cpu(s):  6.3 us, 14.6 sy,  0.0 ni, 79.1 id,  0.0 wa,  0.0 hi,  0.1 si,  0.0 st

KiB Mem :  3861048 total,   415924 free,   251640 used,  3193484 buff/cache

KiB Swap:  2097148 total,  2096884 free,      264 used.  2961148 avail Mem

   PID USER      PR  NI    VIRT    RES    SHR S  %CPU %MEM     TIME+ COMMAND                          

     6 root      20   0    7260     92      0 R 100.0  0.0   0:08.09 stress                           

     1 root      20   0    7260    432    352 S   0.0  0.0   0:00.00 stress                           

     7 root      20   0   11772   1804   1444 S   0.0  0.0   0:00.01 bash                             

    21 root      20   0   51868   1896   1388 R   0.0  0.0   0:00.00 top                              

内存限制

与操作系统类似，容器可使用的内存包括两部分：物理内存和swap。Docker 通过下面两组参数来控制容器内存的使用量。

1. -m 或--memory：设置内存的使用限额，例如100M, 1024M。
2. --memory-swap：设置内存swap 的使用限额。

3. 当执行如下命令：

   其含义是允许该容器最多使用200M 的内存和300M 的swap。

[root@localhost ~]#  docker run -it -m 200M --memory-swap=300M progrium/stress --vm 1 --vm-bytes 280M

Unable to find image 'progrium/stress:latest' locally

Trying to pull repository docker.io/progrium/stress ...

latest: Pulling from docker.io/progrium/stress

a3ed95caeb02: Pull complete

871c32dbbb53: Pull complete

dbe7819a64dd: Pull complete

d14088925c6e: Pull complete

58026d51efe4: Pull complete

7d04a4fe1405: Pull complete

1775fca35fb6: Pull complete

5c319e267908: Pull complete

Digest: sha256:e34d56d60f5caae79333cee395aae93b74791d50e3841986420d23c2ee4697bf

Status: Downloaded newer image for docker.io/progrium/stress:latest

stress: info: [1] dispatching hogs: 0 cpu, 0 io, 1 vm, 0 hdd

stress: dbug: [1] using backoff sleep of 3000us

stress: dbug: [1] --> hogvm worker 1 [6] forked

stress: dbug: [6] allocating 293601280 bytes ...

stress: dbug: [6] touching bytes in strides of 4096 bytes ...

stress: dbug: [6] freed 293601280 bytes

stress: dbug: [6] allocating 293601280 bytes ...

stress: dbug: [6] touching bytes in strides of 4096 bytes ...

stress: dbug: [6] freed 293601280 bytes

stress: dbug: [6] allocating 293601280 bytes ...

stress: dbug: [6] touching bytes in strides of 4096 bytes ...

stress: dbug: [6] freed 293601280 bytes

stress: dbug: [6] allocating 293601280 bytes ...

stress: dbug: [6] touching bytes in strides of 4096 bytes ...

stress: dbug: [6] freed 293601280 bytes

stress: dbug: [6] allocating 293601280 bytes ...

stress: dbug: [6] touching bytes in strides of 4096 bytes ...

stress: dbug: [6] freed 293601280 bytes

stress: dbug: [6] allocating 293601280 bytes ...

stress: dbug: [6] touching bytes in strides of 4096 bytes ...

1. --vm 1：启动1 个内存工作线程。
2. --vm-bytes 280M：每个线程分配280M 内存。

默认情况下，容器可以使用主机上的所有空闲内存。与CPU 的cgroups 配置类似，docker 会自动为容器在目录/sys/fs/cgroup/memory/docker/<容器的完整长ID>中创建相应cgroup 配置文件。

因为280M 在可分配的范围（300M）内，所以工作线程能够正常工作，其过程是：

1. 分配280M 内存。
2. 释放280M 内存。
3. 再分配280M 内存。
4. 再释放280M 内存。
5. 一直循环......

如果让工作线程分配的内存超过300M，分配的内存超过限额，stress 线程报错，容器退出。

[root@localhost ~]# docker run -it -m 200M --memory-swap=300M progrium/stress --vm 1 --vm-bytes 380M

stress: info: [1] dispatching hogs: 0 cpu, 0 io, 1 vm, 0 hdd

stress: dbug: [1] using backoff sleep of 3000us

stress: dbug: [1] --> hogvm worker 1 [6] forked

stress: dbug: [6] allocating 398458880 bytes ...

stress: dbug: [6] touching bytes in strides of 4096 bytes ...

stress: FAIL: [1] (416) <-- worker 6 got signal 9

stress: WARN: [1] (418) now reaping child worker processes

stress: FAIL: [1] (422) kill error: No such process

stress: FAIL: [1] (452) failed run completed in 1s

Block IO 的限制

默认情况下，所有容器能平等地读写磁盘，可以通过设置--blkio-weight 参数来改变容器block IO 的优先级。

--blkio-weight 与--cpu-shares 类似，设置的是相对权重值，默认为500。在下面的例子中，容器A 读写磁盘的带宽是容器B 的两倍。

[root@localhost ~]# docker run -it --name container_A --blkio-weight 600 centos:stress /bin/bash

[root@ee06408457d8 /]# cat /sys/fs/cgroup/blkio/blkio.weight

600

[root@localhost ~]# docker run -it --name container_B --blkio-weight 300 centos:stress /bin/bash

[root@0ad7376f831b /]# cat /sys/fs/cgroup/blkio/blkio.weight

300

限制bps 和iops

如果在一台服务器上进行容器的混合部署，那么会存在同时几个程序写磁盘数据的情况，这时可以通过--device-write-iops选项来限制每秒写io次数来限制制定设备的写速度。相应的还有--device-read-iops选项可以限制读取IO的速度，但是这种方法只能限制设备，而不能限制分区，相应的Cgroup写配置文件为/sys/fs/cgroup/blkio/容器ID/ blkio.throttle.write_iops_device。

1. bps 是byte per second，每秒读写的数据量。
2. iops 是io per second，每秒IO 的次数。

[root@localhost ~]# docker run -it --device-write-bps /dev/sda:5MB centos:stress /bin/bash

[root@bef94b99dc95 /]# dd if=/dev/zero of=test bs=1M count=100 oflag=direct

100+0 records in

100+0 records out

104857600 bytes (105 MB) copied, 20.0237 s, 5.2 MB/s