docker started 3 - Service [translation]

Getting started, Part 3: Service

prerequisites

• Docker install version 1.13 or later.

• Get Docker Compose. On Docker for Mac desktops and Windows, it has been pre-installed, so you can be good-to-go. On Linux systems, you need to install it directly. In the previous Windows 10 system, there is no Hyper-V, please use the Docker Toolbox.

• Reading direction Part 1.

• Learn how to create a container in Part 2.

• By ensure friendlyhelloto publish your image to create a mirror image pushed to the registry. Here we use a shared image.

• Ensure that the container has been deployed as a mirror. Run this command, type in the information username, repoand tag: docker run -p 4000:80 username/repo:tagthen accesshttp://localhost:4000/

Introduction

In Part 3, we extend the application and load balancing. To this end, we must elevate one level in the hierarchy of distributed application: service.

• Stack

• Services (you are here)

• Container (Part 2 covers)

About Service

In distributed applications, different parts of an application called "service." For example, if you imagine a video sharing site, it probably includes a service in the database to store application data, user content after uploading video transcoding service, front-end services in the background.

Service is really just "a production environment of the container." Services run only a mirror, but it mirrored the way of coding the run - it should use what port, container how many copies should be running in order to service with the required capacity, and so on. Zoom will change the service to run container number of instances of the software, which will allocate more resources to the process of computing services.

Fortunately, the use of Docker platform definition, operation and extended service is very simple - just write a  docker-compose.yml file.

Your first  docker-compose.yml file

docker-compose.yml YAML file is a file that defines how to operate Docker containers in production.

docker-compose.yml

Save this file as  docker-compose.yml, whether you need. Make sure that the mirror portion is created in the second push registry, and by username/repo:tag updating a mirror image of this alternative details  .yml.

 

version: "3"
services:
  web:
    # replace username/repo:tag with your name and image details
    image: username/repo:tag
    deploy:
      replicas: 5
      resources:
        limits:
          cpus: "0.1"
          memory: 50M
      restart_policy:
        condition: on-failure
    ports:
      - "4000:80"
    networks:
      - webnet
networks:
  webnet:

 

This  docker-compose.yml file tells Docker do the following:

• We extract images uploaded in step 2 from the registry.

• The five instances referred to as mirroring  web service running limit each time instance up to 10% of a single CPU (which may be, for example, "1.5" indicates that each of the memory core 1 and a half), and 50MB of RAM limit .

• If the container fails, immediately restart the container.

• The port on the host 4000 is mapped to the Web port 80.

• Indicated  web vessel referred to by  webnet load balancing network shared port 80. (Internally, the container itself is posted to the Web port 80 in a temporary port.

• Using the default settings (overlay network load balancing) defined  webnet network.

The new load-balancing applications running

In use  docker stack deploy before the command, we first run:

 

docker swarm init

 

Note: We enter the meaning of section 4 of the command. If you do not run  docker swarm init, you will receive an error that "this node is not a swarm manager .".

Now let's run it. You need to specify a name for the application. Here, it is called getstartedlab:

 

docker stack deploy -c docker-compose.yml getstartedlab

 

Our services stack run single to deploy five container instance mirrors on a single host. Let's look into it.

Get our application service ID of a service:

 

docker service ls

 

Find  web output services, and pre-application name. If you will be named the same as shown in this example, the name  getinitlab_web. Service ID and the number of copies, image name, and open ports are also listed.

Alternatively, you can run  docker stack services, then the name of the stack. The following example command allows you to view and  getstartedlab all associated services stack:

 

docker stack services getstartedlab
ID                  NAME                MODE                REPLICAS            IMAGE               PORTS
bqpve1djnk0x        getstartedlab_web   replicated          5/5                 username/repo:tag   *:4000->80/tcp

 

Running in a single container service called 任务. The task is given a unique identification number can add up to way to get up to you  docker-compose.yml to copy defined replicasnumber. Lists the tasks and services:

 

docker service ps getstartedlab_web

 

If you just list all the container on the system, the task is also displayed, although screening service fails:

 

docker container ls -q

 

You can continuously run curl -4 http://localhost:4000a few times, or go to the URL in your browser and click refresh a few times.

Either way, the container ID are changed, the load balancing presentation; each request, in a cyclic manner to select one of five tasks in response. Container ID are the above command ( docker container ls -qoutput match).

To see all the task stack, you can run  docker stack ps followed by application name, as the following example:

 

docker stack ps getstartedlab
ID                  NAME                  IMAGE               NODE                DESIRED STATE       CURRENT STATE           ERROR               PORTS
uwiaw67sc0eh        getstartedlab_web.1   username/repo:tag   docker-desktop      Running             Running 9 minutes ago                       
sk50xbhmcae7        getstartedlab_web.2   username/repo:tag   docker-desktop      Running             Running 9 minutes ago                       
c4uuw5i6h02j        getstartedlab_web.3   username/repo:tag   docker-desktop      Running             Running 9 minutes ago                       
0dyb70ixu25s        getstartedlab_web.4   username/repo:tag   docker-desktop      Running             Running 9 minutes ago                       
aocrb88ap8b0        getstartedlab_web.5   username/repo:tag   docker-desktop      Running             Running 9 minutes ago

 

Running Windows 10?

Windows 10 PowerShell should already have curly available, but if not, you can grab a Linux terminal emulator, such as Git BASH, or download wget for Windows that is very similar.

Slow response times?

The network configuration environment, the container may take up to 30 seconds to respond to HTTP requests. It is not indicative of the performance Docker or group, but discussed later in this tutorial unmet Redis dependency. Currently, visitors counter do not work for the same reason; we have not been added to retain data services.

Scaling Application

You can change  docker-compose.yml the replicasvalues, save the changes and re-run the  docker stack deploycommand to scale the application:

 

docker stack deploy -c docker-compose.yml getstartedlab

 

Docker-place update, without first stack torn or terminate any container.

Now, re-run  docker container ls -q to see the deployed instance reconfiguration. If the enlarged replicas, will start more tasks to start more container.

Under the application and swarm out

Use  docker stack rm the application under out:

 

docker stack rm getstartedlab

 

Next fall swarm:

 

docker swarm leave --force

 

Docker establish and expand the use of the application is very simple. You learn how to run container in a production environment a big step. Next, you will learn how to run this application to form a true group on Docker computer cluster.

Note: Compose file like this using Docker custom applications, and can be used Docker Cloud uploaded to the cloud provider, you can also be uploaded to the cloud provider use any hardware or Enterprise Edition Docker selected.

Review and Cheat sheets (optional)

In a nutshell, although the type  docker runis very simple, but truly the production of container is running as a service it. Service behavior codified in the Compose container file and the file can be used to extend, limit and re-deploy our application.

At this stage some of the commands to be explored:

 

docker stack ls                                            # List stacks or apps
docker stack deploy -c <composefile> <appname>  # Run the specified Compose file
docker service ls                 # List running services associated with an app
docker service ps <service>                  # List tasks associated with an app
docker inspect <task or container>                   # Inspect task or container
docker container ls -q                                      # List container IDs
docker stack rm <appname>                             # Tear down an application
docker swarm leave --force      # Take down a single node swarm from the manager