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HA Docker Swarm With Docker Machine

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HA Docker Swarm With Docker Machine

Make sure your Docker Swarm setups remain highly available to overcome software ruptures, service order overloads, and infrastructure or hardware problems.

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Docker Swarm allows us to provide High Availability services for our clients. This article will show some recommendations and examples to achieve services with this feature.


Have Docker and Docker Machine installed.

Have a cluster configured using Docker Swarm with Docker Machine with a total of 6 nodes (3 managers and 3 workers). This requirement can be achieved using the scripts published in the article Docker Swarm with Docker Machine, Scripts.

Environment Settings

$ docker version
 Version:      17.11.0-ce
 API version:  1.34
 Go version:   go1.8.3
 Git commit:   1caf76c
 Built:        Mon Nov 20 18:37:39 2017
 OS/Arch:      linux/amd64

 Version:      17.11.0-ce
 API version:  1.34 (minimum version 1.12)
 Go version:   go1.8.3
 Git commit:   1caf76c
 Built:        Mon Nov 20 18:36:09 2017
 OS/Arch:      linux/amd64
 Experimental: false

Source Code

The source code used in this article is published on GitHub.

High Availability Services

When you have services published in production environments, your priority should be to provide these services continuously and without interruptions. In order to achieve this objective, the infrastructure of its systems must be prepared to recover from both physical failures and software components without the user being affected.

High Availability (HA) is the quality of a system or component that ensures a high level of operational performance for a certain period of time.

Preparing Our Machine

Commands From Docker Client to Local Swarm

For the next steps, we need our Docker Client to make requests to the cluster created with Docker Machine. To achieve this, we must establish that the requests are always made from our Docker Client to the Docker Server that is running on node1 of the cluster. Let’s use the following command:

$ eval $(docker-machine env node1)

Check that the change has been made correctly by listing the nodes created with Docker Machinenode1 should be active.

$ docker-machine ls NAME    ACTIVE   DRIVER       STATE     URL                         SWARM   DOCKER        ERRORS
node1   *        virtualbox   Running   tcp://           v17.11.0-ce   
node2   -        virtualbox   Running   tcp://           v17.11.0-ce   
node3   -        virtualbox   Running   tcp://           v17.11.0-ce   
node4   -        virtualbox   Running   tcp://           v17.11.0-ce   
node5   -        virtualbox   Running   tcp://           v17.11.0-ce   
node6   -        virtualbox   Running   tcp://           v17.11.0-ce 

If you want to learn more about Docker architecture, you can consult this link.

Docker Swarm From the Browser

We will use the Docker Swarm Visualizer project to see our Swarm from the browser. To achieve this, we will use the file visualizer.yml located in the stacks folder of the repository. The command to publish this service would be as follows:

$ docker stack deploy --compose-file=stacks/visualizer.yml visualizer

Let’s check if the service was deployed correctly:

$ docker stack services visualizer
ID                  NAME                MODE                REPLICAS            IMAGE                             PORTS
qxm4w28xr4la        visualizer_web      replicated          2/2                 dockersamples/visualizer:latest   *:8080->8080/tcp

Then we access our browser using the IP of node1 ( and the port 8080.

Docker Swarm Visualizer

Setting Local DNS

Let’s group the different IP addresses of our nodes under a single web address. The web address to be used will be swarm.local and we must add it together with the IPs of the Docker Machines in the /etc/hosts file.

To edit the file, you can use the command:

$ sudo vim /etc/hosts

Add the following data to the file:

Setting hosts file

Once the file is saved, we can access the systems displayed in the Swarm through the link http://swarm.local/, such as Visualizar Swarm.

Our App or Service

We will use DockerCloud’s Hello-World as an application, which will be deployed through port 80.

We will use this application to identify some problems that could lead to service interruptions for our clients. We will also see the suggested solution that we can implement using the benefits of Docker Swarm.

The possible disaster situations to be resolved will be:

  • Software rupture.
  • Overload of orders to a service.
  • Infrastructure or hardware problems.

Software Rupture

The published product is not perfect and, therefore, unexpected interruptions could occur due to situations such as: overload of users accessing the site at the same time, the identification of a bug or critical case, the demand for higher values of RAM or CPU, among others.

The solution before these possible problems is to create multiple instances of our application to continue providing the services even if one or several of them are not available.

Docker Swarm will allow us to create multiple instances of the same service easily. The following configuration will allow us to deploy our system and will be able to easily identify how the two replicas of the service are specified.

The file with the configuration can be found in the stacks folder with the name dockercloud-hello-world.yml.

version: '3.4'
    image: dockercloud/hello-world
      - target: 80
        published: 80
        protocol: tcp
        mode: ingress
      mode: replicated
      replicas: 2

Let’s start the service with the following command:

$ docker stack deploy --compose-file=stacks/dockercloud-hello-world.yml dc-helloworld

Let’s update our Visualizer application, and we’ll see something similar to the following image:

Docker Swarm Visualizer

If we access this link we can see the Hello World application. If you update the browser a couple of times, you will see how the name of the container changes, indicating that both instances are available.

DockerCloud Hello World

Overload of Orders to a Service

When we have multiple instances of the same service, we need to balance the load that arrives at them so that none is saturated in requests. Luckily for us, Docker Swarm solves this problem for us because it has a system to balance the load within its own core.

As this load balancer is in the core of Docker, we have the guarantee that each node has one of these systems. Therefore, if any of the nodes stops working, the Swarm will be able to continue distributing the requests to the instances with less demand.

For more information about it, you can consult this link.

Docker Swarm - Load Balance

Infrastructure or Hardware Problems

The virtual machines of our infrastructure are physically located in an availability zone. If all our nodes are in the same zone and a network or hardware problem occurs, all Swarm services will be interrupted. For this reason, this is another element to be taken into account.

So far, we are clear that our nodes should be created in different areas of availability, but the next question would be:

How do we configure our Swarm so that it publishes the services establishing a balance between the different physical zones?

The answer is adding Tags to the nodes and Restrictions in the deployment of the services. Let’s see an example in the following steps.

Add Tags to Nodes

In the example, just the 3 Worker nodes will be used, and they will be distributed in 2 physical zones: us-east-1 and us-west-1. The commands to add the tags to the nodes are:

$ docker node update --label-add zone=us-east-1 node4
$ docker node update --label-add zone=us-east-1 node5
$ docker node update --label-add zone=us-west-1 node6

Docker Swarm - Node Labels

Add Constraints to the Service

Let’s configure the file dockercloud-hello-world.yml where the following elements will be added:

  • Use only the worker nodes.
  • Propagation strategy using the tags node.labels.zone.
  • Create 6 replicas of the service.
version: '3.4'
    image: dockercloud/hello-world
      - target: 80
        published: 80
        protocol: tcp
        mode: ingress
      mode: replicated
      replicas: 6
          - spread: node.labels.zone
          - node.role == worker

Update the Service Deployed

Let’s move on to update our service with the new configurations. To achieve this we must use the same command used during the creation of it.

$ docker stack deploy --compose-file=stacks/dockercloud-hello-world.yml dc-helloworld

Docker Swarm - Spread Strategy


Providing services with High Availability is not an easy task, but neither is it impossible. With this article, you have some suggestions and advice to establish High Availability services using Docker Swarm.

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