Deploy Docker Compose (v3) to Swarm (mode) Cluster

TL;DR

Docker 1.13 simplifies deployment of composed applications to a swarm (mode) cluster. And you can do it without creating a new dab (Distribution Application Bundle) file, but just using familiar and well-known docker-compose.yml syntax (with some additions) and the --compose-file option. Read about this exciting feature, create a free Codefresh account, and try building, testing and deploying  images instantly.

Swarm cluster

Docker Engine 1.12 introduced a new swarm mode for natively managing a cluster of Docker Engines called a swarm. Docker swarm mode implements Raft Consensus Algorithm and does not require using external key value store anymore, such as Consul or etcd.
If you want to run a swarm cluster on a developer’s machine, there are several options.
The first option and most widely known is to use a docker-machine tool with some virtual driver (Virtualbox, Parallels or other).
But, in this post, I will use another approach: using docker-in-docker Docker image with Docker for Mac, see more details in my Docker Swarm cluster with docker-in-docker on MacOS post.

Docker Registry mirror

When you deploy a new service on a local swarm cluster, I recommend setting up a local Docker registry mirror so you can run all swarm nodes with the --registry-mirror option, pointing to your local Docker registry. By running a local Docker registry mirror, you can keep most of the redundant image fetch traffic on your local network and speedup service deployment.

Docker Swarm cluster bootstrap script

I’ve prepared a shell script to bootstrap a 4 node swarm cluster with Docker registry mirror and the very nice swarm visualizer application.
The script initializes docker engine as a swarm master, then starts 3 new docker-in-docker containers and joins them to the swarm cluster as worker nodes. All worker nodes run with the --registry-mirror option.

#!/bin/bash

# vars
[ -z "$NUM_WORKERS" ] && NUM_WORKERS=3

# init swarm (need for service command); if not created
docker node ls 2> /dev/null | grep "Leader"
if [ $? -ne 0 ]; then
  docker swarm init > /dev/null 2>&1
fi

# get join token
SWARM_TOKEN=$(docker swarm join-token -q worker)

# get Swarm master IP (Docker for Mac xhyve VM IP)
SWARM_MASTER=$(docker info --format "{{.Swarm.NodeAddr}}")
echo "Swarm master IP: ${SWARM_MASTER}"
sleep 10

# start Docker registry mirror
docker run -d --restart=always -p 4000:5000 --name v2_mirror \
  -v $PWD/rdata:/var/lib/registry \
  -e REGISTRY_PROXY_REMOTEURL=https://registry-1.docker.io \
  registry:2.5

# run NUM_WORKERS workers with SWARM_TOKEN
for i in $(seq "${NUM_WORKERS}"); do
  # remove node from cluster if exists
  docker node rm --force $(docker node ls --filter "name=worker-${i}" -q) > /dev/null 2>&1
  # remove worker contianer with same name if exists
  docker rm --force $(docker ps -q --filter "name=worker-${i}") > /dev/null 2>&1
  # run new worker container
  docker run -d --privileged --name worker-${i} --hostname=worker-${i} \
    -p ${i}2375:2375 \
    -p ${i}5000:5000 \
    -p ${i}5001:5001 \
    -p ${i}5601:5601 \
    docker:1.13-rc-dind --registry-mirror http://${SWARM_MASTER}:4000
  # add worker container to the cluster
  docker --host=localhost:${i}2375 swarm join --token ${SWARM_TOKEN} ${SWARM_MASTER}:2377
done

# show swarm cluster
printf "\nLocal Swarm Cluster\n===================\n"

docker node ls

# echo swarm visualizer
printf "\nLocal Swarm Visualizer\n===================\n"
docker run -it -d --name swarm_visualizer \
  -p 8000:8080 -e HOST=localhost \
  -v /var/run/docker.sock:/var/run/docker.sock \
  manomarks/visualizer:beta

Deploying multi-container application – the “old” way

The Docker compose is a tool (and deployment specification format) for defining and running composed multi-container Docker applications. Before Docker 1.12, you could use docker-compose to deploy such applications to a swarm cluster. With 1.12 release, that is no longer possible: docker-compose can deploy your application on single Docker host only.
In order to deploy it to a swarm cluster, you need to create a special deployment specification file (also knows as Distribution Application Bundle) in dab format (see more here).
To create this file, run docker-compose bundle. This will create a JSON file that describes a multi-container composed application with Docker images referenced by @sha256 instead of tags. Currently the dab file format does not support multiple settings from docker-compose.yml and does not support options from the docker service create command.
It’s really too bad, the dab bundle format looks promising, but is useless in Docker 1.12.

Deploying multi-container application – the “new” way

With Docker 1.13, the “new” way to deploy a multi-container composed application is to use docker-compose.yml again (hurrah!). Kudos to the Docker team!
*Note: You do not need docker-compose. You only need a yaml file in docker-compose format (version: "3")

$ docker deploy --compose-file docker-compose.yml

Docker compose v3 (version: "3")

So, what’s new in docker compose version 3?
First, I suggest you take a deeper look at the docker-compose schema. It is an extension of the well-known docker-compose format.
Note:docker-compose tool (ver. 1.9.0) does not support docker-compose.yaml version: "3" yet.
The most visible change is around swarm service deployment.
Now you can specify all options supported by docker service create/update commands, this includes:

• number of service replicas (or global service)
• service labels
• hard and soft limits for service (container) CPU and memory
• service restart policy
• service rolling update policy
• deployment placement constraints link
  

  Docker compose v3 example

  I’ve created a “new” compose file (v3) for the classic Cats vs. Dogs voting app. This example application contains 5 services with the following deployment configurations:

1. voting-app – a Python webapp which lets you vote between two options; requires redis
2. redis – Redis queue which collects new votes; deployed on swarm manager node
3. db – Postgres database backed by a Docker volume; deployed on swarm manager node
4. result-app  Node.js webapp which shows the results of the voting in real time; 2 replicas, deployed on swarm worker nodes
5. worker .NET worker which consumes votes and stores them in db;

• # of replicas: 2 replicas
• hard limit: max 25% CPU and 512MB memory
• soft limit: max 25% CPU and 256MB memory
• placement: on swarm worker nodes only
• restart policy: restart on-failure, with 5 seconds delay, up to 3 attempts
• update policy: one by one, with 10 seconds delay and 0.3 failure rate to tolerate during the update

version: "3"

services:

  redis:
    image: redis:3.2-alpine
    ports:
      - "6379"
    networks:
      - voteapp
    deploy:
      placement:
        constraints: [node.role == manager]

  db:
    image: postgres:9.4
    volumes:
      - db-data:/var/lib/postgresql/data
    networks:
      - voteapp
    deploy:
      placement:
        constraints: [node.role == manager]

  voting-app:
    image: gaiadocker/example-voting-app-vote:good
    ports:
      - 5000:80
    networks:
      - voteapp
    depends_on:
      - redis
    deploy:
      mode: replicated
      replicas: 2
      labels: [APP=VOTING]
      placement:
        constraints: [node.role == worker]

  result-app:
    image: gaiadocker/example-voting-app-result:latest
    ports:
      - 5001:80
    networks:
      - voteapp
    depends_on:
      - db

  worker:
    image: gaiadocker/example-voting-app-worker:latest
    networks:
      voteapp:
        aliases:
          - workers
    depends_on:
      - db
      - redis
    # service deployment
    deploy:
      mode: replicated
      replicas: 2
      labels: [APP=VOTING]
      # service resource management
      resources:
        # Hard limit - Docker does not allow to allocate more
        limits:
          cpus: '0.25'
          memory: 512M
        # Soft limit - Docker makes best effort to return to it
        reservations:
          cpus: '0.25'
          memory: 256M
      # service restart policy
      restart_policy:
        condition: on-failure
        delay: 5s
        max_attempts: 3
        window: 120s
      # service update configuration
      update_config:
        parallelism: 1
        delay: 10s
        failure_action: continue
        monitor: 60s
        max_failure_ratio: 0.3
      # placement constraint - in this case on 'worker' nodes only
      placement:
        constraints: [node.role == worker]

networks:
    voteapp:

volumes:
  db-data:

Run the docker deploy –compose-file docker-compose.yml VOTE command to deploy my version of “Cats vs. Dogs” application on a swarm cluster.

Hope you find this post useful. I look forward to your comments and any questions you have.

Hope you find this post useful. I look forward to your comments and any questions you have. Now, it’s time to get you onboarded.  Go on and create a free Codefresh account to start building, testing and deploying Docker images faster than ever.