Deploy the application

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Estimated reading time: 10 minutes

You’ve deployed the load balancer, the discovery backend, and a Swarm cluster so now you can build and deploy the voting application itself. You do this by starting a number of “Dockerized applications” running in containers.

The diagram below shows the final application configuration including the overlay container network, voteapp.

In this procedure you will connect containers to this network. The voteapp network is available to all Docker hosts using the Consul discovery backend. Notice that the interlock, nginx, consul, and swarm manager containers on are not part of the voteapp overlay container network.

Task 1. Set up volume and network

This application relies on both an overlay container network and a container volume. The Docker Engine provides these two features. You’ll create them both on the Swarm manager instance.

  1. Direct your local environment to the Swarm manager host.

    $ eval $(docker-machine env manager)

    You can create the network on a cluster node at the network is visible on them all.

  2. Create the voteapp container network.

    $ docker network create -d overlay voteapp
  3. Switch to the db store.

    $ eval $(docker-machine env dbstore)
  4. Verify you can see the new network from the dbstore node.

    $ docker network ls
    NETWORK ID          NAME                DRIVER
    e952814f610a        voteapp             overlay
    1f12c5e7bcc4        bridge              bridge
    3ca38e887cd8        none                null
    3da57c44586b        host                host
  5. Create a container volume called db-data.

    $ docker volume create --name db-data

Task 2. Start the containerized microservices

At this point, you are ready to start the component microservices that make up the application. Some of the application’s containers are launched from existing images pulled directly from Docker Hub. Other containers are launched from custom images you must build. The list below shows which containers use custom images and which do not:

  • Load balancer container: stock image (ehazlett/interlock)
  • Redis containers: stock image (official redis image)
  • Postgres (PostgreSQL) containers: stock image (official postgres image)
  • Web containers: custom built image
  • Worker containers: custom built image
  • Results containers: custom built image

You can launch these containers from any host in the cluster using the commands in this section. Each command includes a -H flag so that they execute against the Swarm manager.

The commands also all use the -e flag which is a Swarm constraint. The constraint tells the manager to look for a node with a matching function label. You set established the labels when you created the nodes. As you run each command below, look for the value constraint.

  1. Start a Postgres database container.

    $ docker -H $(docker-machine ip manager):3376 run -t -d \
    -v db-data:/var/lib/postgresql/data \
    -e constraint:com.function==dbstore \
    --net="voteapp" \
    --name db postgres:9.4
  2. Start the Redis container.

    $ docker -H $(docker-machine ip manager):3376 run -t -d \
    -p 6379:6379 \
    -e constraint:com.function==dbstore \
    --net="voteapp" \
    --name redis redis

    The redis name is important so don’t change it.

  3. Start the worker application

    $ docker -H $(docker-machine ip manager):3376 run -t -d \
    -e constraint:com.function==worker01 \
    --net="voteapp" \
    --net-alias=workers \
    --name worker01 docker/example-voting-app-worker
  4. Start the results application.

    $ docker -H $(docker-machine ip manager):3376 run -t -d \
    -p 80:80 \
    --label=interlock.hostname=results \ \
    -e constraint:com.function==dbstore \
    --net="voteapp" \
    --name results-app docker/example-voting-app-result-app
  5. Start the voting application twice; once on each frontend node.

    $ docker -H $(docker-machine ip manager):3376 run -t -d \
    -p 80:80 \
    --label=interlock.hostname=vote \ \
    -e constraint:com.function==frontend01 \
    --net="voteapp" \
    --name voting-app01 docker/example-voting-app-voting-app

    And again on the other frontend node.

    $ docker -H $(docker-machine ip manager):3376 run -t -d \
    -p 80:80 \
    --label=interlock.hostname=vote \ \
    -e constraint:com.function==frontend02 \
    --net="voteapp" \
    --name voting-app02 docker/example-voting-app-voting-app

Task 3. Check your work and update /etc/hosts

In this step, you check your work to make sure the Nginx configuration recorded the containers correctly. You’ll update your local systems /etc/hosts file to allow you to take advantage of the loadbalancer.

  1. Change to the loadbalancer node.

    $ eval $(docker-machine env loadbalancer)
  2. Check your work by reviewing the configuration of nginx.

    $ docker exec interlock cat /etc/conf/nginx.conf
    ... output snipped ...
    upstream {
        zone results.myenterprise.example.com_backend 64k;
    server {
        listen 80;
        location / {
    upstream {
        zone vote.myenterprise.example.com_backend 64k;
    server {
        listen 80;
        location / {
    include /etc/conf/conf.d/*.conf;

    The site configuration should point to either frontend node. Requests to go just to the single dbstore node where the example-voting-app-result-app is running.

  3. On your local host, edit /etc/hosts file add the resolution for both these sites.

  4. Save and close the /etc/hosts file.

  5. Restart the nginx container.

    Manual restart is required because the current Interlock server is not forcing an Nginx configuration reload.

    $ docker restart nginx

Task 4. Test the application

Now, you can test your application.

  1. Open a browser and navigate to the site.

    You should see something similar to the following:

  2. Click on one of the two voting options.
  3. Navigate to the site to see the results.
  4. Try changing your vote.

    You’ll see both sides change as you switch your vote.

Extra Credit: Deployment with Docker Compose

Up to this point, you’ve deployed each application container individually. This can be cumbersome especially because their are several different containers and starting them is order dependent. For example, that database should be running before the worker.

Docker Compose let’s you define your microservice containers and their dependencies in a Compose file. Then, you can use the Compose file to start all the containers at once. This extra credit

  1. Before you begin, stop all the containers you started.

    a. Set the host to the manager.

     $ DOCKER_HOST=$(docker-machine ip manager):3376

    b. List all the application containers on the Swarm.

    c. Stop and remove each container.

  2. Try to create Compose file on your own by reviewing the tasks in this tutorial.

    The version 2 Compose file format is the best to use. Translate each docker run command into a service in the docker-compose.yml file. For example, this command:

    $ docker -H $(docker-machine ip manager):3376 run -t -d \
    -e constraint:com.function==worker01 \
    --net="voteapp" \
    --net-alias=workers \
    --name worker01 docker/example-voting-app-worker

    Becomes this in a Compose file.

      image: docker/example-voting-app-worker
          - workers

    In general, Compose starts services in reverse order they appear in the file. So, if you want a service to start before all the others, make it the last service in the file. This application relies on a volume and a network, declare those at the bottom of the file.

  3. Check your work against this file.

  4. When you are satisfied, save the docker-compose.yml file to your system.

  5. Set DOCKER_HOST to the Swarm manager.

    $ DOCKER_HOST=$(docker-machine ip manager):3376
  6. In the same directory as your docker-compose.yml file, start the services.

    $ docker-compose up -d
    Creating network "scale_voteapp" with the default driver
    Creating volume "scale_db-data" with default driver
    Pulling db (postgres:9.4)...
    worker01: Pulling postgres:9.4... : downloaded
    dbstore: Pulling postgres:9.4... : downloaded
    frontend01: Pulling postgres:9.4... : downloaded
    frontend02: Pulling postgres:9.4... : downloaded
    Creating db
    Pulling redis (redis:latest)...
    dbstore: Pulling redis:latest... : downloaded
    frontend01: Pulling redis:latest... : downloaded
    frontend02: Pulling redis:latest... : downloaded
    worker01: Pulling redis:latest... : downloaded
    Creating redis
    Pulling worker (docker/example-voting-app-worker:latest)...
    dbstore: Pulling docker/example-voting-app-worker:latest... : downloaded
    frontend01: Pulling docker/example-voting-app-worker:latest... : downloaded
    frontend02: Pulling docker/example-voting-app-worker:latest... : downloaded
    worker01: Pulling docker/example-voting-app-worker:latest... : downloaded
    Creating scale_worker_1
    Pulling voting-app (docker/example-voting-app-voting-app:latest)...
    dbstore: Pulling docker/example-voting-app-voting-app:latest... : downloaded
    frontend01: Pulling docker/example-voting-app-voting-app:latest... : downloaded
    frontend02: Pulling docker/example-voting-app-voting-app:latest... : downloaded
    worker01: Pulling docker/example-voting-app-voting-app:latest... : downloaded
    Creating scale_voting-app_1
    Pulling result-app (docker/example-voting-app-result-app:latest)...
    dbstore: Pulling docker/example-voting-app-result-app:latest... : downloaded
    frontend01: Pulling docker/example-voting-app-result-app:latest... : downloaded
    frontend02: Pulling docker/example-voting-app-result-app:latest... : downloaded
    worker01: Pulling docker/example-voting-app-result-app:latest... : downloaded
    Creating scale_result-app_1
  7. Use the docker ps command to see the containers on the Swarm cluster.

    $ docker -H $(docker-machine ip manager):3376 ps
    CONTAINER ID        IMAGE                                  COMMAND                  CREATED             STATUS              PORTS                            NAMES
    b71555033caa        docker/example-voting-app-result-app   "node server.js"         6 seconds ago       Up 4 seconds>80/tcp     frontend01/scale_result-app_1
    cf29ea21475d        docker/example-voting-app-worker       "/usr/lib/jvm/java-7-"   6 seconds ago       Up 4 seconds                                         worker01/scale_worker_1
    98414cd40ab9        redis                                  "/ redis"   7 seconds ago       Up 5 seconds>6379/tcp   frontend02/redis
    1f214acb77ae        postgres:9.4                           "/docker-entrypoint.s"   7 seconds ago       Up 5 seconds        5432/tcp                         frontend01/db
    1a4b8f7ce4a9        docker/example-voting-app-voting-app   "python"          7 seconds ago       Up 5 seconds>80/tcp     dbstore/scale_voting-app_1

    When you started the services manually, you had a voting-app instances running on two frontend servers. How many do you have now?

  8. Scale your application up by adding some voting-app instances.

    $ docker-compose scale voting-app=3
    Creating and starting 2 ... done
    Creating and starting 3 ... done

    After you scale up, list the containers on the cluster again.

  9. Change to the loadbalancer node.

    $ eval $(docker-machine env loadbalancer)
  10. Restart the Nginx server.

    $ docker restart nginx
  11. Check your work again by visiting the and again.

  12. You can view the logs on an individual container.

    $ docker logs scale_voting-app_1
     * Running on (Press CTRL+C to quit)
     * Restarting with stat
     * Debugger is active!
     * Debugger pin code: 285-809-660 - - [11/Apr/2016 17:15:44] "GET / HTTP/1.0" 200 - - - [11/Apr/2016 17:15:44] "GET /static/stylesheets/style.css HTTP/1.0" 304 - - - [11/Apr/2016 17:15:45] "GET /favicon.ico HTTP/1.0" 404 - - - [11/Apr/2016 17:22:24] "POST / HTTP/1.0" 200 - - - [11/Apr/2016 17:23:37] "POST / HTTP/1.0" 200 - - - [11/Apr/2016 17:23:39] "POST / HTTP/1.0" 200 - - - [11/Apr/2016 17:23:40] "POST / HTTP/1.0" 200 - - - [11/Apr/2016 17:23:41] "POST / HTTP/1.0" 200 - - - [11/Apr/2016 17:23:43] "POST / HTTP/1.0" 200 - - - [11/Apr/2016 17:23:44] "POST / HTTP/1.0" 200 - - - [11/Apr/2016 17:23:46] "POST / HTTP/1.0" 200 -

This log shows the activity on one of the active voting application containers.

Next steps

Congratulations. You have successfully walked through manually deploying a microservice-based application to a Swarm cluster. Of course, not every deployment goes smoothly. Now that you’ve learned how to successfully deploy an application at scale, you should learn what to consider when troubleshooting large applications running on a Swarm cluster.

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