Docker Swarm Made Easy: A Step-by-Step Tutorial Series by Linuxlearning Hub

Docker Swarm runs on Docker applications and helps the developers/end-users create and deploy a cluster of Docker nodes. Additionally, a high-level availability for applications is one of the key benefits offered by Docker swarm. For example, we can schedule the application tasks so that each machine in the Swarm cluster has one task each. Moreover, it helps in the efficient distribution of tasks and reduces the turnaround time for the tasks, thus increasing the throughout.

Docker Swarm is one such management tool developed by Docker Inc. In this blog, I will not only explain what is Docker Swarm, but I will also walk you through the topics mentioned below. If we deploy the new version of the application and the end users find any bugs while using it you can roll back to the previous version of the application by using Docker Swarm. A restart of the daemon is required to take the new configuration into account.

Introduction to Docker Swarm Mode

These can be applied when creating a service or later with the docker service update command. Worker nodes are responsible for executing tasks that dispatch to them from manager nodes. An agent runs on each worker node and reports to the manager node on its assigned tasks. It helps the manager node to maintain the desired state of each worker node. At a high level, we can view the Docker Swarm as an orchestration management tool.

The latest format, defined by the
Compose specification
isn’t compatible with the docker stack deploy command. Here’s how you can use Swarm mode to set up simple distributed workloads across a fleet of machines. You should use Swarm if you want to host scalable applications with redundancy using a standard Docker installation, no other dependencies required.

Step 5: Verify Docker Version

But, for persistence, we use something called Raft implementation. The managers maintain a consistent internal state of services and the whole Swarm cluster itself. The best practice in production/non-testing purposes we should implement more than one manager node. Here a task is a running container that is part of a swarm service. Contrary to the standalone container, a swarm manager manages the task. Subsequently, the following diagram shows a typical docker swarm cluster.

Clusters benefit from integrated service discovery functions, support for rolling updates, and network traffic routing via external load balancers. The host has a changing IP address, or none if you have no network access. We recommend that you connect to the special DNS name host.docker.internal,
which resolves to the internal IP address used by the host. However if you are a Windows user, it works with Windows containers.

Automating Docker Setup with Ansible Playbook

We will have to create a manager to handle our worker nodes. And, you should also know that the manager is also a worker node with some special privileges. As of now, we have only the manager node, and hence the above command shows only the manager node details. Once we create a worker node, it will also show those details. A Docker Swarm is a group/ cluster of machines (either physical or virtual) that run the Docker application and configure it to join together in a cluster.

• The Worker nodes are nothing but the instances of Docker Engine which are created to run Docker Containers.
• Tasks are monitored for 20 seconds after rollback to be sure they do
  not exit, and a maximum failure ratio of 20% is tolerated.
• It’s an environment where you can have various Docker images running on the same host operating system.
• If at any time during an update a task returns FAILED, the scheduler pauses
  the update.
• Once you’ve added your nodes, run docker info on the manager to inspect the cluster’s status.
• You can update almost every configuration detail about an existing service,
  including the image name and tag it runs.

Make sure that the nodes to which you are deploying are correctly configured for the gMSA. For more details about image tag resolution, see
Specify the image version the service should use. Docker Swarm mode compares favorably to alternative orchestration platforms such as Kubernetes. It’s easier to get started with as it’s integrated with Docker and there are fewer concepts to learn.

Rolling Updates

To prevent this from
happening, ensure that your application runs on hosts with adequate memory and
see
Understand the risks of running out of memory. Service constraints let you set criteria for a node to meet before the scheduler
deploys a service to the node. You can apply constraints to the
service based upon node attributes and metadata or engine metadata. For more
information on constraints, refer to the docker service create
CLI reference. First, create overlay network on a manager node using the docker network create
command with the –driver overlay flag.

Every worker node has an agent that reports on the state of the node’s tasks to the manager. This way, the manager node can maintain the desired state of the cluster. You can change almost everything about an existing service using the
docker service update command. When you update a service, Docker stops its
containers and restarts them with the new configuration.

Monitoring Docker daemons

Once a group of machines that run the Docker application has been clustered together, we call it a “Swarm mode”. So in Swarm mode, we can still execute Docker commands with the only difference that now the machines in the cluster will execute them. Moreover, we have an entity called “Swarm Manager”, a machine that controls the activities of a cluster. Other machines that have joined the cluster are known as “Nodes”. The third one, services, will discover the services deployed in the
swarm.

However, using relabel_configs is recommended as it
enables Prometheus to reuse the same API calls across identical Docker Swarm
configurations. An individual task update is considered to have failed if the task doesn’t
start up, or if it stops running within the monitoring period specified with
the –update-monitor flag. You can pass the
–update-parallelism flag to configure the maximum number of service tasks
that the scheduler updates simultaneously. The –update-delay flag configures the time delay between updates to a service
task or sets of tasks. You can describe the time T as a combination of the
number of seconds Ts, minutes Tm, or hours Th.

Docker Commands

The dispatcher and scheduler are responsible for assigning and instructing worker nodes to run a task. The Worker node connects to the manager to check for new tasks. The last stage in this process is for the worker node to execute the tasks that have been assigned from the manager node. The API that we connect in our Swarm environment allows us to do orchestration by creating tasks for each service. The task allocation will enable us to allocate work to tasks via their IP address.