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Multi-Container Applications Using Docker Compose and Swarm

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Multi-Container Applications Using Docker Compose and Swarm

Learn how to run a multi-container applications using Docker Compose in a Docker Swarm cluster.

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Docker Compose to Orchestrate Containers shows how to run two linked Docker containers using Docker Compose. Clustering Using Docker Swarm shows how to configure a Docker Swarm cluster.

This blog will show how to run a multi-container application created using Docker Compose in a Docker Swarm cluster.

Updated version of Docker Compose and Docker Swarm are released with Docker 1.7.0.

Docker 1.7.0 CLI

Get the latest Docker CLI:

curl https://get.docker.com/builds/Darwin/x86_64/docker-latest > /usr/local/bin/docker

and check the version as:

docker -v
Docker version 1.7.0, build 0baf609

Docker Machine 0.3.0

Get the latest Docker Machine as:

curl -L https://github.com/docker/machine/releases/download/v0.3.0/docker-machine_darwin-amd64 > /usr/local/bin/docker-machine

and check the version as:

docker-machine -v
docker-machine version 0.3.0 (0a251fe)

Docker Compose 1.3.0

Get the latest Docker Compose as:

curl -L https://github.com/docker/compose/releases/download/1.3.0/docker-compose-`uname -s`-`uname -m` > /usr/local/bin/docker-compose
chmod +x /usr/local/bin/docker-compose

and verify the version as:

docker-compose -v
docker-compose version: 1.3.0
CPython version: 2.7.9
OpenSSL version: OpenSSL 1.0.1j 15 Oct 2014

Docker Swarm 0.3.0

Swarm is run as a Docker container and can be downloaded as:

docker pull swarm

You can learn about Docker Swarm at docs.docker.com/swarm or Clustering using Docker Swarm.

Create Docker Swarm Cluster

The key components of Docker Swarm are shown below:

and explained in Clustering Using Docker Swarm.

  1. The easiest way of getting started with Swarm is by using the official Docker image:
    docker run swarm create

    This command returns a discovery token, referred as <TOKEN> in this document, and is the unique cluster id. It will be used when creating master and nodes later. This cluster id is returned by the hosted discovery service on Docker Hub. It shows the output as:
    docker run swarm create
    Unable to find image 'swarm:latest' locally
    latest: Pulling from swarm
    55b38848634f: Pull complete
    fd7bc7d11a30: Pull complete
    db039e91413f: Pull complete
    1e5a49ab6458: Pull complete
    5d9ce3cdadc7: Pull complete
    1f26e949f933: Pull complete
    e08948058bed: Already exists
    swarm:latest: The image you are pulling has been verified. Important: image verification is a tech preview feature and should not be relied on to provide security.
    Digest: sha256:0e417fe3f7f2c7683599b94852e4308d1f426c82917223fccf4c1c4a4eddb8ef
    Status: Downloaded newer image for swarm:latest
    1d528bf0568099a452fef5c029f39b85
    The last line is the <TOKEN>.Make sure to note this cluster id now as there is no means to list it later. This should be fixed with#661.
  2. Swarm is fully integrated with Docker Machine, and so is the easiest way to get started. Let’s create a Swarm Master next:
    docker-machine create -d virtualbox --swarm --swarm-master --swarm-discovery token://&lt;TOKEN&gt; swarm-master
    Replace <TOKEN> with the cluster id obtained in the previous step.--swarm configures the machine with Swarm, --swarm-master configures the created machine to be Swarm master. Swarm master creation talks to the hosted service on Docker Hub and informs that a master is created in the cluster.
  3. Connect to this newly created master and find some more information about it:
    eval "$(docker-machine env swarm-master)"
    docker info
    This will show the output as:
    &gt; docker info
    Containers: 2
    Images: 7
    Storage Driver: aufs
     Root Dir: /mnt/sda1/var/lib/docker/aufs
     Backing Filesystem: extfs
     Dirs: 11
     Dirperm1 Supported: true
    Execution Driver: native-0.2
    Logging Driver: json-file
    Kernel Version: 4.0.5-boot2docker
    Operating System: Boot2Docker 1.7.0 (TCL 6.3); master : 7960f90 - Thu Jun 18 18:31:45 UTC 2015
    CPUs: 1
    Total Memory: 996.2 MiB
    Name: swarm-master
    ID: DLFR:OQ3E:B5P6:HFFD:VKLI:IOLU:URNG:HML5:UHJF:6JCL:ITFH:DS6J
    Debug mode (server): true
    File Descriptors: 22
    Goroutines: 36
    System Time: 2015-07-11T00:16:34.29965306Z
    EventsListeners: 1
    Init SHA1:
    Init Path: /usr/local/bin/docker
    Docker Root Dir: /mnt/sda1/var/lib/docker
    Username: arungupta
    Registry: https://index.docker.io/v1/
    Labels:
     provider=virtualbox
  4. Create a Swarm node
    docker-machine create -d virtualbox --swarm --swarm-discovery token://&lt;TOKEN&gt; swarm-node-01
    Replace <TOKEN> with the cluster id obtained in an earlier step.Node creation talks to the hosted service at Docker Hub and joins the previously created cluster. This is specified by --swarm-discovery token://... and specifying the cluster id obtained earlier.
  5. To make it a real cluster, let’s create a second node:
    docker-machine create -d virtualbox --swarm --swarm-discovery token://&lt;TOKEN&gt; swarm-node-02
    Replace <TOKEN> with the cluster id obtained in the previous step.
  6. List all the nodes created so far:
    docker-machine ls
    This shows the output similar to the one below:
    docker-machine ls
    NAME            ACTIVE   DRIVER       STATE     URL                         SWARM
    lab                      virtualbox   Running   tcp://192.168.99.101:2376
    summit2015               virtualbox   Running   tcp://192.168.99.100:2376
    swarm-master    *        virtualbox   Running   tcp://192.168.99.102:2376   swarm-master (master)
    swarm-node-01            virtualbox   Running   tcp://192.168.99.103:2376   swarm-master
    swarm-node-02            virtualbox   Running   tcp://192.168.99.104:2376   swarm-master
    The machines that are part of the cluster have the cluster’s name in the SWARM column, blank otherwise. For example, “lab” and “summit2015” are standalone machines where as all other machines are part of the “swarm-master” cluster. The Swarm master is also identified by (master) in the SWARM column.
  7. Connect to the Swarm cluster and find some information about it:
    eval "$(docker-machine env --swarm swarm-master)"
    docker info
    This shows the output as:
    &gt; docker info
    Containers: 4
    Images: 3
    Role: primary
    Strategy: spread
    Filters: affinity, health, constraint, port, dependency
    Nodes: 3
     swarm-master: 192.168.99.102:2376
      └ Containers: 2
      └ Reserved CPUs: 0 / 1
      └ Reserved Memory: 0 B / 1.022 GiB
      └ Labels: executiondriver=native-0.2, kernelversion=4.0.5-boot2docker, operatingsystem=Boot2Docker 1.7.0 (TCL 6.3); master : 7960f90 - Thu Jun 18 18:31:45 UTC 2015, provider=virtualbox, storagedriver=aufs
     swarm-node-01: 192.168.99.103:2376
      └ Containers: 1
      └ Reserved CPUs: 0 / 1
      └ Reserved Memory: 0 B / 1.022 GiB
      └ Labels: executiondriver=native-0.2, kernelversion=4.0.5-boot2docker, operatingsystem=Boot2Docker 1.7.0 (TCL 6.3); master : 7960f90 - Thu Jun 18 18:31:45 UTC 2015, provider=virtualbox, storagedriver=aufs
     swarm-node-02: 192.168.99.104:2376
      └ Containers: 1
      └ Reserved CPUs: 0 / 1
      └ Reserved Memory: 0 B / 1.022 GiB
      └ Labels: executiondriver=native-0.2, kernelversion=4.0.5-boot2docker, operatingsystem=Boot2Docker 1.7.0 (TCL 6.3); master : 7960f90 - Thu Jun 18 18:31:45 UTC 2015, provider=virtualbox, storagedriver=aufs
    CPUs: 3
    Total Memory: 3.065 GiB
    There are 3 nodes – one Swarm master and 2 Swarm nodes. There is a total of 4 containers running in this cluster – one Swarm agent on master and each node, and there is an additional swarm-agent-master running on the master.
  8. List nodes in the cluster with the following command:
    docker run swarm list token://&lt;TOKEN&gt;
    This shows the output as:
    &gt; docker run swarm list token://1d528bf0568099a452fef5c029f39b85
    192.168.99.103:2376
    192.168.99.104:2376
    192.168.99.102:2376

Deploy Java EE Application to Docker Swarm Cluster using Docker Compose

Docker Compose to Orchestrate Containers explains how multi container applications can be easily started using Docker Compose.

  1. Use the docker-compose.yml file explained in that blog to start the containers as:
    docker-compose up -d
    Creating wildflymysqljavaee7_mysqldb_1...
    Creating wildflymysqljavaee7_mywildfly_1...

    The docker-compose.yml file looks like:
    mysqldb:
      image: mysql:latest
      environment:
        MYSQL_DATABASE: sample
        MYSQL_USER: mysql
        MYSQL_PASSWORD: mysql
        MYSQL_ROOT_PASSWORD: supersecret
    mywildfly:
      image: arungupta/wildfly-mysql-javaee7
      links:
        - mysqldb:db
      ports:
        - 8080:8080
  2. Check the containers running in the cluster as:
    eval "$(docker-machine env --swarm swarm-master)"
    docker info

    to see the output as:
    docker info
    Containers: 7
    Images: 5
    Role: primary
    Strategy: spread
    Filters: affinity, health, constraint, port, dependency
    Nodes: 3
     swarm-master: 192.168.99.102:2376
      └ Containers: 2
      └ Reserved CPUs: 0 / 1
      └ Reserved Memory: 0 B / 1.022 GiB
      └ Labels: executiondriver=native-0.2, kernelversion=4.0.5-boot2docker, operatingsystem=Boot2Docker 1.7.0 (TCL 6.3); master : 7960f90 - Thu Jun 18 18:31:45 UTC 2015, provider=virtualbox, storagedriver=aufs
     swarm-node-01: 192.168.99.103:2376
      └ Containers: 2
      └ Reserved CPUs: 0 / 1
      └ Reserved Memory: 0 B / 1.022 GiB
      └ Labels: executiondriver=native-0.2, kernelversion=4.0.5-boot2docker, operatingsystem=Boot2Docker 1.7.0 (TCL 6.3); master : 7960f90 - Thu Jun 18 18:31:45 UTC 2015, provider=virtualbox, storagedriver=aufs
     swarm-node-02: 192.168.99.104:2376
      └ Containers: 3
      └ Reserved CPUs: 0 / 1
      └ Reserved Memory: 0 B / 1.022 GiB
      └ Labels: executiondriver=native-0.2, kernelversion=4.0.5-boot2docker, operatingsystem=Boot2Docker 1.7.0 (TCL 6.3); master : 7960f90 - Thu Jun 18 18:31:45 UTC 2015, provider=virtualbox, storagedriver=aufs
    CPUs: 3
    Total Memory: 3.065 GiB
  3. “swarm-node-02” is running three containers and so lets look at the list of containers running there:
    eval "$(docker-machine env swarm-node-02)"

    and see the list of running containers as:
    docker ps -a
    CONTAINER ID        IMAGE                             COMMAND                CREATED             STATUS              PORTS                    NAMES
    b1e7d9bd2c09        arungupta/wildfly-mysql-javaee7   "/opt/jboss/wildfly/   38 seconds ago      Up 37 seconds       0.0.0.0:8080-&gt;8080/tcp   wildflymysqljavaee7_mywildfly_1
    ac9c967e4b1d        mysql:latest                      "/entrypoint.sh mysq   38 seconds ago      Up 38 seconds       3306/tcp                 wildflymysqljavaee7_mysqldb_1
    45b015bc79f4        swarm:latest                      "/swarm join --addr    20 minutes ago      Up 20 minutes       2375/tcp                 swarm-agent
  4. Application can then be accessed again using:
    curl http://$(docker-machine ip swarm-node-02):8080/employees/resources/employees

    and shows the output as:
    &lt;?<span class="pl-ent">xml</span><span class="pl-e"> version</span>=<span class="pl-s"><span class="pl-pds">"</span>1.0<span class="pl-pds">"</span></span><span class="pl-e"> encoding</span>=<span class="pl-s"><span class="pl-pds">"</span>UTF-8<span class="pl-pds">"</span></span><span class="pl-e"> standalone</span>=<span class="pl-s"><span class="pl-pds">"</span>yes<span class="pl-pds">"</span></span>?&gt;&lt;<span class="pl-ent">collection</span>&gt;&lt;<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">id</span>&gt;1&lt;/<span class="pl-ent">id</span>&gt;&lt;<span class="pl-ent">name</span>&gt;Penny&lt;/<span class="pl-ent">name</span>&gt;&lt;/<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">id</span>&gt;2&lt;/<span class="pl-ent">id</span>&gt;&lt;<span class="pl-ent">name</span>&gt;Sheldon&lt;/<span class="pl-ent">name</span>&gt;&lt;/<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">id</span>&gt;3&lt;/<span class="pl-ent">id</span>&gt;&lt;<span class="pl-ent">name</span>&gt;Amy&lt;/<span class="pl-ent">name</span>&gt;&lt;/<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">id</span>&gt;4&lt;/<span class="pl-ent">id</span>&gt;&lt;<span class="pl-ent">name</span>&gt;Leonard&lt;/<span class="pl-ent">name</span>&gt;&lt;/<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">id</span>&gt;5&lt;/<span class="pl-ent">id</span>&gt;&lt;<span class="pl-ent">name</span>&gt;Bernadette&lt;/<span class="pl-ent">name</span>&gt;&lt;/<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">id</span>&gt;6&lt;/<span class="pl-ent">id</span>&gt;&lt;<span class="pl-ent">name</span>&gt;Raj&lt;/<span class="pl-ent">name</span>&gt;&lt;/<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">id</span>&gt;7&lt;/<span class="pl-ent">id</span>&gt;&lt;<span class="pl-ent">name</span>&gt;Howard&lt;/<span class="pl-ent">name</span>&gt;&lt;/<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">employee</span>&gt;&lt;<span class="pl-ent">id</span>&gt;8&lt;/<span class="pl-ent">id</span>&gt;&lt;<span class="pl-ent">name</span>&gt;Priya&lt;/<span class="pl-ent">name</span>&gt;&lt;/<span class="pl-ent">employee</span>&gt;&lt;/<span class="pl-ent">collection</span>&gt;

Latest instructions for this setup are always available at: github.com/javaee-samples/docker-java/blob/master/chapters/docker-swarm.adoc.

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Topics:
docker ,containers ,docker swarm ,docker compose ,clustering ,orchestration ,cloud

Published at DZone with permission of Arun Gupta, DZone MVB. See the original article here.

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