5. Stacks

Stacks

Group of interrelated services that share dependencies, and can be orchestrated and scaled together.

Inter-related services all running in concert.

A single stack is capable of defining and coordinating the functionality of an entire application (though very complex applications may want to use multiple stacks).

Add a new service and redeploy

It’s easy to add services to our docker-compose.yml file. First, let’s add a free visualizer service that lets us look at how our swarm is scheduling containers.

1. Open up docker-compose.yml in an editor and replace its contents with the following:

   docker-compose.yml

   version: "3"
   services:
   
     web:
       # replace username/repo:tag with your name and image details
       image: username/repo:tag
       deploy:
         replicas: 5
         restart_policy:
           condition: on-failure
         resources:
           limits:
             cpus: "0.1"
             memory: 50M
       ports:
         - "80:80"
       networks:
         - webnet
     visualizer:
       image: dockersamples/visualizer:stable
       ports:
         - "8080:8080"
       volumes:
         - "/var/run/docker.sock:/var/run/docker.sock"
       deploy:
         placement:
           constraints: [node.role == manager]
       networks:
         - webnet
   networks:
     webnet:

   The only thing new here is the peer service to web, named visualizer. Notice two new things here: a volumes key, giving the visualizer access to the host’s socket file for Docker, and a placement key, ensuring that this service only ever runs on a swarm manager -- never a worker. That’s because this container, built from an open source project created by Docker, displays Docker services running on a swarm in a diagram.

   We talk more about placement constraints and volumes in a moment.

2. Make sure your shell is configured to talk to myvm1 (full examples are here).

   • Run docker-machine ls to list machines and make sure you are connected to myvm1, as indicated by an asterisk next to it.

   • If needed, re-run docker-machine env myvm1, then run the given command to configure the shell.

     On Mac or Linux the command is:

     eval $(docker-machine env myvm1)

     On Windows the command is:

     & "C:\Program Files\Docker\Docker\Resources\bin\docker-machine.exe" env myvm1 | Invoke-Expression

3. Re-run the docker stack deploy command on the manager, and whatever services need updating are updated:

   $ docker stack deploy -c docker-compose.yml getstartedlab
   Updating service getstartedlab_web (id: angi1bf5e4to03qu9f93trnxm)
   Creating service getstartedlab_visualizer (id: l9mnwkeq2jiononb5ihz9u7a4)

4. Take a look at the visualizer.

   You saw in the Compose file that visualizer runs on port 8080. Get the IP address of one of your nodes by running docker-machine ls. Go to either IP address at port 8080 and you can see the visualizer running:

   

   The single copy of visualizer is running on the manager as you expect, and the 5 instances of web are spread out across the swarm. You can corroborate this visualization by running docker stack ps <stack>:

   docker stack ps getstartedlab

   The visualizer is a standalone service that can run in any app that includes it in the stack. It doesn’t depend on anything else. Now let’s create a service that does have a dependency: the Redis service that provides a visitor counter.