Today for large-scale application deployments, all architectural components should be planned and tuned with current and future plans in mind. Container orchestration tools help achieve this by automating the management of application micro services across multiple clusters. Two of the most popular container compose tools are Kubernetes and Docker Swarm. In this article, we’ll explore the main differences between Kubernetes and Docker Swarm so you can choose the one that’s right for your tech stack.
It is an open source cloud infrastructure tool that automates the scaling, deployment, and management of containerised applications (apps that reside within the container).
Google initially developed Kubernetes and handed it over to the Cloud Native Computing Foundation (CNCF) for improvement and maintenance. One of the top options for developers, Kubernetes is a feature-rich container orchestration platform with the following points:
- Regular updates from CNCF
- Daily posts from the global community
Docker Swarm Overview
It is similar to the Docker platform. Docker is designed to maintain application efficient and available in multiple run-time environments by delivering containerised application micro services to multiple clusters.
Docker Swarm is a Docker’s unique container orchestration tool that allows us to run the application across multiple nodes that share the same container. Basically, it uses the Docker Swarm model to efficiently manage, deploy, and scale a cluster of nodes on Docker.
Difference & Features between Kubernetes and Docker Swarm
Kubernetes and Docker Swarm are both effective solutions, including:
- Large-scale application delivery
Both models divide the application into containers, enabling efficient automation of application management and scaling. An overview of the difference between them is: With a focus on open source and modular orchestration,
Kubernetes provides an efficient container orchestration solution for demanding applications with complex configurations. Docker Swarm focuses on ease of use , making it ideal for simple applications that are quick to deploy and easy to manage.
Let’s take a look at the fundamental difference between them. Each section describes K8s first, then Docker Swarm.
With multiple installation options, Kubernetes can be easily deployed on any platform, but it’s a good idea to understand the basics of platforms and cloud computing before installing.
To install Kubernetes, we need to download and install kubectl, the kubernetes command line interface (CLI).
- On Linux, you can install kubectl as a snap application using curl, native, or other package management techniques.
- MacOS, kubectl can be installed with curl, homebrew, or MacPorts.
- On Windows, you can install kubectl using several options such as curl, Powershell Gallery Package Manager, Chocolatey Package Manager, and Scoop command line installer.
Detailed instructions for installing kubectl can be found here.
Docker Swarm is relatively easy to install compared to Kubernetes. Once the Docker Engine is installed on your computer, deploying Docker Swarm is easy:
- Assigning IP Addresses to Hosts
- Opening Protocols and Ports Between Hosts
Before initialising Swarm, first assign a manager node and one or more worker nodes. Between the hosts.
GRAPHICAL USER INTERFACE (GUI)
Kubernetes provides a simple web user interface (dashboard) to help you:
- Deploy container applications to a cluster
- Manage cluster resources
- Error logs and information about the status of cluster resources (including deployments, jobs, daemon sets) for efficient troubleshooting
Unlike Kubernetes, Docker Swarm does not come standard with a Web UI for deploying applications and orchestrating containers. However, as it grows in popularity, there are some third-party tools that provide a simple and feature-rich GUI for Docker Swarm.
The popular Docker Swarm UI tools are:
APPLICATION DEFINITION & DEPLOYMENT
Deploying Kubernetes includes a declarative update of the application state when the Kubernetes pod and Replica Sets are updated,by describing the desired state of the pod, the controller changes the current state to the desired state at a controlled rate. Kubernetes deployments allow us to define all aspects of your application’s life cycle.
These aspects are:
- Number of Pods
- Images to Use
- How to Update Pods
Docker Swarm uses predefined Swarm files to define the application and declare the desired state of application. To deploy your app, just copy the YAML file at the root level. This file, also known as the Docker Compose File, enables you to use the multi-node computer features.
This allows organizations to run containers and services in the following locations:
- Multiple computers
- Any number of networks
Kubernetes allows two topologies by default. They ensure high availability by creating a cluster to eliminate a single point of failure:
- Stack control plane nodes are available. It ensures availability by merging etcd objects with all available nodes in the cluster during fail over.
- Alternatively, you can use an external etcd object for load balancing while controlling the
or the control plane node individually.
In particular, both of these methods utilise the use of kubeadm and maintain high availability by using the Multi Master approach to manage etcd cluster nodes outside or inside the control plane.
To maintain high availability, Docker uses service replication at the swarm node level. In this way, Swarm Manager provides multiple instances of the same container, each with a replica of the service. Default internal distributed state store:
- Control Swarm Manager nodes to manage the entire cluster
- Manage worker node resources to create highly available and load balanced container instances
Kubernetes supports automatic scaling in both:
- From cluster level to cluster auto scaling
- With pod level and horizontal pod autoscaler
At its core, Kubernetes acts as a comprehensive network of distributed nodes, providing a strong guarantee of a uniform API set and cluster state. Scaling in Kubernetes basically involves creating new pods and planning nodes with available resources.
Docker Swarm allows you to use your containers faster. This reduces the response time of the orchestration tool and allows it to be scaled as needed. To scale your Docker application to handle heavy traffic loads, you need to replicate the number of connections to your application. Therefore, you can easily scale up and down your application for even higher availability.
Kubernetes creates flat peer-to-peer connections between pods and node agents for efficient inter cluster networking. This link contains a network policy that regulates communication between pods while assigning different IP addresses to each pod. To define a subnet, the Kubernetes network model requires two Classless Inter-Domain Routers (CIDRs).
- One for node IP addressing
- Another for services
Docker Swarm creates two types of networks for each node that participates in the swarm.
- A superposition of all services in the network.
- The other creates a host-only bridge for all containers.
The Multi layer Overlay Network enables peer-to-peer delivery to all hosts, enabling secure and encrypted communication.
Kubernetes provides several native logging and monitoring solutions for services deployed in a cluster. These solutions monitor application performance in the following ways:
- Service, Pod, and Container Inspection
- Monitoring Cluster-Wide Behaviour
In addition, Kubernetes also supports third-party integration to support event-based monitoring, such as:
- ElasticSearch / Kibana
Unlike Kubernetes, Docker Swarm does not provide a ready to use monitoring solution. Therefore, you need to plan on a third-party application to help monitor Docker Swarm. It’s monitoring is typically considered more complex than K8s clusters due to the sheer volume of cross-node objects and services.These are several open source monitoring tools that work together to enable Docker Swarm’s scalable monitoring solution.
In conclusion, the overall purpose of Kubernetes and Docker Swarm overlaps. However, as mentioned earlier,
there is a fundamental difference between these two behaviours. After all, both options solve advanced challenges and make digital transformation realistic and efficient.