Docker Swarm 更新
文章目录
服务可以动态更新，以控制各种设置和选项。在内部，Docker管理如何应用更新。对于某些命令，Docker将停止、删除和重新创建容器。对于管理连接和正常运行时间来说，让所有容器一次性停止是一个重要的考虑因素。
有各种各样的设置你可以控制，通过查看帮助
$ docker service update --help
要启动，需要部署HTTP服务。我们将使用它来更新/修改容器设置。
$ docker swarm init && docker service create --name http --replicas 2 -p 80:80 katacoda/docker-http-server:v1 Swarm initialized: current node (vemt8upto85rpq2c0iv26hfjb) is now a manager. To add a worker to this swarm, run the following command: docker swarm join --token SWMTKN-1-3ql2gc1k1clslqhyce6ww09fshgvslde4fpkt5wabgc6gewkid-96vytrgsrua2qrgfujq8bdo08 172.17.0.40:2377 To add a manager to this swarm, run 'docker swarm join-token manager' and follow the instructions. 2838c9f2d95l8qxzdin1zn7pa overall progress: 2 out of 2 tasks 1/2: running [==================================================>] 2/2: running [==================================================>] verify: Service converged
1. Update Limits
一旦启动，就可以更新各种属性。例如，向容器添加一个新的环境变量
$ docker service update --env-add KEY=VALUE http http overall progress: 0 out of 2 tasks overall progress: 2 out of 2 tasks 1/2: running [==================================================>] 2/2: running [==================================================>] verify: Service converged
或者，更新CPU和内存限制。
$ docker service update --limit-cpu 2 --limit-memory 512mb http http overall progress: 2 out of 2 tasks 1/2: running [==================================================>] 2/2: running [==================================================>] verify: Service converged
一旦执行，当您检查服务时，结果将是可见的.
$ docker service inspect --pretty http ID: 2838c9f2d95l8qxzdin1zn7pa Name: http Service Mode: Replicated Replicas: 2 UpdateStatus: State: completed Started: 38 seconds ago Completed: 23 seconds ago Message: update completed Placement: UpdateConfig: Parallelism: 1 On failure: pause Monitoring Period: 5s Max failure ratio: 0 Update order: stop-first RollbackConfig: Parallelism: 1 On failure: pause Monitoring Period: 5s Max failure ratio: 0 Rollback order: stop-first ContainerSpec: Image: katacoda/docker-http-server:v1@sha256:4d7bfcb1e38912d286c5cda63aeddc850a4be16127094ffacbb7abfc6298c5fa Env: KEY=VALUE Resources: Limits: CPU: 2 Memory: 512MiB Endpoint Mode: vip Ports: PublishedPort = 80 Protocol = tcp TargetPort = 80 PublishMode = ingress
但是，在列出所有容器时，您将看到它们在每次更新时都被重新创建.
$ docker ps -a CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 26e2064259ff katacoda/docker-http-server:v1 "/app" About a minute ago Up About a minute 80/tcp http.1.vsv080fuwlsgcqo16m0d3czz9 74c412f02426 katacoda/docker-http-server:v1 "/app" About a minute ago Up About a minute 80/tcp http.2.z6sp9scii6kj4ponoz0wrmv05 deda0102a7e2 katacoda/docker-http-server:v1 "/app" 2 minutes ago Exited (2) About a minute ago http.2.ugilx2q6zkkkw0pwo2f6ydrmi 9b9d3addcc2f katacoda/docker-http-server:v1 "/app" 2 minutes ago Exited (2) About a minute ago http.1.lvhnd9zywl7ioax9t5wi3y9c8 9806903d549f katacoda/docker-http-server:v1 "/app" 2 minutes ago Exited (2) 2 minutes ago http.1.9m8l4jz9cxicel0ff8w3sq8k7 cdcd87d9487d katacoda/docker-http-server:v1 "/app" 2 minutes ago Exited (2) 2 minutes ago http.2.ahrvwdkcd9kkkxp868ppx14v5
2. Update Replicas
并非所有更新都需要重新创建每个容器。例如，扩展副本的数量不会影响现有容器。docker service scale作为一种替代docker服务规模的方法，可以使用更新来定义应该运行多少个副本。下面将把副本从2更新为6。然后Docker将重新安排要部署的另外四个容器。
$ docker service update --replicas=6 http http 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
副本的数量在检查服务时是可见的
$ docker service inspect --pretty http ID: 2838c9f2d95l8qxzdin1zn7pa Name: http Service Mode: Replicated Replicas: 6
3. Update Image
使用更新的最常见场景是通过更新的Docker Image发布应用程序的新版本。由于Docker Image是容器的属性，所以可以像前面的步骤一样对其进行更新。
下面的命令将使用Docker镜像的v2标记重新创建HTTP服务的实例。
$ docker service update --image katacoda/docker-http-server:v2 http http 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
如果你打开一个新的终端窗口，你会注意到Swarm正在执行滚动更新。
$ docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 35d342b07967 katacoda/docker-http-server:v2 "/app" 49 seconds ago Up 44 seconds 80/tcp http.5.bjdoq1c85l2q2hdv1xkx0q8tb 18da1f1606ef katacoda/docker-http-server:v2 "/app" 54 seconds ago Up 49 seconds 80/tcp http.2.gx464snpuedj2dm0iq1rzgad6 725fdaafe45b katacoda/docker-http-server:v2 "/app" About a minute ago Up 54 seconds 80/tcp http.1.4n0ub4wo24zi8v7ptigbahtsz 5987cf3c84e8 katacoda/docker-http-server:v2 "/app" About a minute ago Up About a minute 80/tcp http.3.rm9ehbhf8gaay83dkb44frd3o 7c68ffd7eb76 katacoda/docker-http-server:v2 "/app" About a minute ago Up About a minute 80/tcp http.6.u9yzhw2reneuipj5na0vkwp8r 2c1b365d7601 katacoda/docker-http-server:v2 "/app" About a minute ago Up About a minute 80/tcp http.4.i8r9ulpxfcldjorqucfryjtgl
通过使用多个副本进行滚动更新，应用程序永远不会宕机，并且可以执行零停机部署。
$ curl http://docker <h1>New Release! Now v2! This request was processed by host: 35d342b07967</h1> $ curl http://docker <h1>New Release! Now v2! This request was processed by host: 18da1f1606ef</h1> $ curl http://docker <h1>New Release! Now v2! This request was processed by host: 725fdaafe45b</h1> $ curl http://docker <h1>New Release! Now v2! This request was processed by host: 5987cf3c84e8</h1> $ curl http://docker <h1>New Release! Now v2! This request was processed by host: 7c68ffd7eb76</h1> $ curl http://docker <h1>New Release! Now v2! This request was processed by host: 2c1b365d7601</h1> $ curl http://docker <h1>New Release! Now v2! This request was processed by host: 35d342b07967</h1> $
下一步将讨论如何控制推出和零停机部署。
4. 滚动更新
其目的是部署一个新的Docker镜像而不引起任何停机时间。通过设置并行性和延迟，可以实现零停机时间。Docker可以批处理更新，并将其作为跨集群的rollout执行。
update-parallelism：定义了Docker一次应该更新多少个容器。副本的数量取决于您将对请求进行批量处理的大小。
update-delay：定义在每个更新批之间等待多长时间。如果应用程序有预热时间(例如启动JVM或CLR)，那么延迟是有用的。通过指定延迟，可以确保在流程启动时仍然可以处理请求。
这两个参数在运行docker服务更新时应用。在这个例子中，它一次更新一个容器，在每次更新之间等待10秒。该更新将影响所使用的Docker映像，但参数可以应用于任何可能的更新值
$ docker service update --update-delay=10s --update-parallelism=1 --image katacoda/docker-http-server:v3 http
启动之后，您会慢慢地看到容器的新v3版本启动并替换现有的v2版本。
$ docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES bf72245972b2 katacoda/docker-http-server:v3 "/app" 8 seconds ago Up 2 seconds 80/tcp http.5.nk6451tjyjof7bmhrbz8mwa8t db63c2989df4 katacoda/docker-http-server:v3 "/app" 24 seconds ago Up 18 seconds 80/tcp http.2.ymml1p2qcyndx7wdpzt4fgnmd b5e45490f79b katacoda/docker-http-server:v3 "/app" 39 seconds ago Up 34 seconds 80/tcp http.1.l6la8w8cqu87ndenxico2fx4q 5987cf3c84e8 katacoda/docker-http-server:v2 "/app" 7 minutes ago Up 6 minutes 80/tcp http.3.rm9ehbhf8gaay83dkb44frd3o 7c68ffd7eb76 katacoda/docker-http-server:v2 "/app" 7 minutes ago Up 7 minutes 80/tcp http.6.u9yzhw2reneuipj5na0vkwp8r 2c1b365d7601 katacoda/docker-http-server:v2 "/app" 7 minutes ago Up 7 minutes 80/tcp http.4.i8r9ulpxfcldjorqucfryjtgl
向负载均衡器发出HTTP请求将请求v2和v3容器处理它们，从而产生不同的输出。
$ curl http://docker <h1>New Release! Now v2! This request was processed by host: 5987cf3c84e8</h1> $ curl http://docker <h1>New Another Release! Now v3! This request was processed by host: 8349dd465a7e</h1> $ curl http://docker <h1>New Another Release! Now v3! This request was processed by host: 09860150d9b1</h1> $ curl http://docker <h1>New Another Release! Now v3! This request was processed by host: bf72245972b2</h1> $ curl http://docker <h1>New Another Release! Now v3! This request was processed by host: db63c2989df4</h1> $ curl http://docker <h1>New Another Release! Now v3! This request was processed by host: b5e45490f79b</h1>
应用程序必须考虑到这一点，并同时处理两个不同的版本。
参考：
docker swarm update
Updating Services in a Docker Swarm Mode Cluster
Rolling updates with Docker Swarm
Updating Docker Swarm Configs and Secrets Without Downtime
