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Java EE Application on Docker Swarm Cluster

Docker Swarm is native clustering for Docker. It allows you create and access to a pool of Docker hosts using the full suite of Docker tools. Because Docker Swarm serves the standard Docker API, any tool that already communicates with a Docker daemon can use Swarm to transparently scale to multiple hosts

Key Components of Docker Swarm

docker swarm components
Figure 1. Key Components of Docker Swarm

Swarm Manager: Docker Swarm has a Manager, that is a pre-defined Docker Host, and is a single point for all administration. The swarm manager orchestrates and schedules containers on the entire cluster. Currently only a single instance of manager is allowed in the cluster. This is a SPOF for high availability architectures and additional managers will be allowed in a future version of Swarm with #598.

Swarm Nodes: The containers are deployed on Nodes that are additional Docker Hosts. Each Swarm Node must be accessible by the manager, each node must listen to the same network interface (TCP port). Each node runs a Docker Swarm agent that registers the referenced Docker daemon, monitors it, and updates the discovery backend with the node’s status. The containers run on a node.

Scheduler Strategy: Different scheduler strategies (“binpack”, “spread” (default), and “random”) can be applied to pick the best node to run your container. The default strategy optimizes the node for least number of running containers. There are multiple kinds of filters, such as constraints and affinity. This should allow for a decent scheduling algorithm.

Node Discovery Service: By default, Swarm uses hosted discovery service, based on Docker Hub, using tokens to discover nodes that are part of a cluster. However etcd, consul, and ZooKeeper can be also be used for service discovery as well. This is particularly useful if there is no access to Internet, or you are running the setup in a closed network. A new discovery backend can be created as explained here. It would be useful to have the hosted Discovery Service inside the firewall and #660 will discuss this.

Standard Docker API: Docker Swarm serves the standard Docker API and thus any tool that talks to a single Docker host will seamlessly scale to multiple hosts now. That means that if you were using shell scripts using Docker CLI to configure multiple Docker hosts, the same CLI would can now talk to Swarm cluster and Docker Swarm will then act as proxy and run it on the cluster.

There are lots of other concepts but these are the main ones.

Create a Docker Swarm Cluster

  1. The easiest way of using 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>.

    Note
    		 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://<TOKEN> 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
    Note
    		 If you’re on Windows, use the docker-machine env swarm-master command only and copy the output into an editor to replace all appearances of EXPORT with SET and issue the three commands at your command prompt, remove the quotes and all duplicate appearences of "/".

    This will show the output as:

    > 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://<TOKEN> 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://<TOKEN> 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
default         -        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, “default” is 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:

    > 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. This can be verified by connecting to the master and listing all the containers.

  8. List nodes in the cluster with the following command:

    docker run swarm list token://<TOKEN>

    This shows the output as:

    > 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

The complete cluster is in place now, and we need to deploy the Java EE application to it.

Swarm takes care for the distribution of deployments across the nodes. The only thing, we need to do is to deploy the application as already explained in [JavaEE7_Container_Linking].

  1. Start MySQL server as:

    docker run --name mysqldb -e MYSQL_USER=mysql -e MYSQL_PASSWORD=mysql -e MYSQL_DATABASE=sample -e MYSQL_ROOT_PASSWORD=supersecret -p 3306:3306 -d mysql

    -e define environment variables that are read by the database at startup and allow us to access the database with this user and password.

  2. Start WildFly and deploy Java EE 7 application as:

    docker run -d --name mywildfly --link mysqldb:db -p 8080:8080 arungupta/wildfly-mysql-javaee7

    This is using the Docker Container Linking explained earlier.

  3. Check state of the cluster 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

    “swarm-node-02” is running three containers and so lets look at the list of running containers:

    > eval "$(docker-machine env swarm-node-02)"
> docker ps -a
CONTAINER ID        IMAGE                             COMMAND                CREATED              STATUS              PORTS                    NAMES
805f3587f5df        arungupta/wildfly-mysql-javaee7   "/opt/jboss/wildfly/   About a minute ago   Up About a minute   0.0.0.0:8080->8080/tcp   mywildfly
ababc544df97        mysql                             "/entrypoint.sh mysq   5 minutes ago        Up 5 minutes        0.0.0.0:3306->3306/tcp   mysqldb
45b015bc79f4        swarm:latest                      "/swarm join --addr    17 minutes ago       Up 17 minutes       2375/tcp                 swarm-agent

  4. Access the application as:

    curl http://$(docker-machine ip swarm-node-02):8080/employees/resources/employees

    to see the output as:

    <?xml version="1.0" encoding="UTF-8" standalone="yes"?><collection><employee><id>1</id><name>Penny</name></employee><employee><id>2</id><name>Sheldon</name></employee><employee><id>3</id><name>Amy</name></employee><employee><id>4</id><name>Leonard</name></employee><employee><id>5</id><name>Bernadette</name></employee><employee><id>6</id><name>Raj</name></employee><employee><id>7</id><name>Howard</name></employee><employee><id>8</id><name>Priya</name></employee></collection>

Deploy Java EE Application to Docker Swarm Cluster using Docker Compose

[Docker_Compose] explains how multi container applications can be easily started using Docker Compose.

  1. Connect to ‘swarm-node-02’:

    eval "$(docker-machine env swarm-node-02)"

  2. Stop the MySQL and WildFly containers:

    docker ps -a | grep wildfly | awk '{print $1}' | xargs docker rm -f
docker ps -a | grep mysql | awk '{print $1}' | xargs docker rm -f

  3. Use the docker-compose.yml file explained in [Docker_Compose] to start the containers as:

    docker-compose up -d
Creating wildflymysqljavaee7_mysqldb_1...
Creating wildflymysqljavaee7_mywildfly_1...

  4. 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

  5. Connect to ‘swarm-node-02’ again:

    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->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

  6. Application can then be accessed again using:

    curl http://$(docker-machine ip swarm-node-02):8080/employees/resources/employees

    and shows the output as:

    <?xml version="1.0" encoding="UTF-8" standalone="yes"?><collection><employee><id>1</id><name>Penny</name></employee><employee><id>2</id><name>Sheldon</name></employee><employee><id>3</id><name>Amy</name></employee><employee><id>4</id><name>Leonard</name></employee><employee><id>5</id><name>Bernadette</name></employee><employee><id>6</id><name>Raj</name></employee><employee><id>7</id><name>Howard</name></employee><employee><id>8</id><name>Priya</name></employee></collection>

Add container visualiation using arun-gupta#55.