Containerization has existed for decades but has seen increasing adoption in recent years for application development and modernization. This article covers two container solutions and their uses:
Containerization is a form of virtualization at the application level. It aims to package an application with all its dependencies, runtimes, libraries and configuration files in one isolated executable package, which is called a container. The operating system (OS) is not included in the container which makes it different from virtual machines (VMs), which are virtualized at the hardware level and include the OS.
While the concept behind virtualization is the sharing of physical resources between several virtual machines, containers share the kernel of one OS between several containers. Unlike virtual machines, containers are lightweight precisely because they don’t contain the OS. This is why containers take seconds to boot. In addition, containers can easily be deployed on different operating systems (Windows, Linux, macOS) and in different environments (cloud, VM, physical server) without requiring any changes.
In 2013, Docker Inc. introduced Docker in an attempt to standardize containers to be used widely and on different platforms. A year later, Google introduced Kubernetes as a solution to manage a cluster of container hosts. The definitions of the two solutions will show the difference between Kubernetes and Docker.
Docker is an open-source platform to package and run applications in standard containers that can run across different platforms in the same behavior. With Docker, containerized applications are isolated from the host, which offers the flexibility of delivering applications to any platform running any OS. Furthermore, the Docker engine manages containers and allows them to run simultaneously on the same host.
Due to the client-server architecture, Docker consists of client- and server-side components (Docker client and Docker daemon). The client and the daemon (Dockerd) can run on the same system or you can connect the client to a remote daemon. The daemon processes the API requests sent by the client in addition to managing the other Docker objects (containers, networks, volumes, images, etc.).
Docker Desktop is the installer of Docker client and daemon and includes other components like Docker Compose, Docker CLI (Command Line Interface), and more. It can be installed on different platforms: Windows, Linux, and macOS.
Developers can design an application to run on multiple containers on the same host, which creates the need to manage multiple containers at the same time. For this reason, Docker Inc. introduced Docker Compose. Docker vs Docker Compose can be summarized as follows: Docker can manage a container, while Compose can manage multiple containers on one host.
Managing multi-containerized applications on the same host is a complicated and time-consuming task. Docker Compose, the orchestration tool for a single host, manages multi-containerized applications defined on one host using the Compose file format.
Docker Compose allows running multiple containers at the same time by creating one YAML configuration file where you define all the containers. Compose allows you to split the application into several containers instead of building it in one container. You can split your application into sub-services called microservices and run each microservice in a container. Then you can start all the containers by running a single command through Compose.
Developers can design an application to run on multiple containers on different hosts, which creates the need for an orchestration solution for a cluster of containers across different hosts. For this reason, Docker Inc. introduced Docker Swarm.
Docker Swarm or Docker in Swarm mode is a cluster of Docker engines that can be enabled after installing Docker. Swarm allows managing multiple containers on different hosts, unlike Compose which allows managing multiple containers on the same host only.
Kubernetes (K8s) is an orchestration tool that manages containers on one or more hosts. K8s clusters the hosts whether they are on-premises, in the cloud or in hybrid environments, and can integrate with Docker and other container platforms. Google initially developed and introduced Kubernetes to automate the deployment and management of containers. K8s provides several features to support resiliency, like container fault tolerance, load balancing across hosts, and automatic creation and removal of containers.
Kubernetes manages a cluster of one or more hosts, which are either master nodes or worker nodes. The master nodes contain the control panel components of Kubernetes, while the worker nodes contain non-control panel components (Kubelet and Kube-proxy). The recommendation is to have at least a cluster of four hosts: at least one master node and three worker nodes to run your tests.
The master node can span across multiple nodes but can run only on one computer. It is recommended that you avoid creating application containers on the master node. The master is responsible for managing the cluster. It responds to cluster events, makes cluster decisions, schedules operations with containers, starts up a new Pod (a group of containers on the same host and the smallest unit in Kubernetes), runs control loops, etc.
The working nodes are the non-master nodes. There are two node components: kubelet and kube-proxy. They should run on each working node in addition to a container runtime software like Docker.
Kubernetes and Docker are different scope solutions that can complete each other to make a powerful combination. Thus, Docker vs Kubernetes is not a correct comparison. Docker allows developers to package applications in isolated containers. Developers can deploy those containers to other machines without worrying about compatibility with operating systems.
Developers can use Docker Compose to manage containers on one host. But Docker Compose vs Kubernetes is not an accurate comparison either, since the solutions are for different scopes. The scope of Compose is limited to one host while that of Kubernetes is for a cluster of hosts.
When the number of containers and hosts becomes high, developers can use Docker Swarm or Kubernetes to orchestrate Docker containers and manage them in a cluster. Both Kubernetes and Docker Swarm are container orchestration solutions in a cluster setup.
Kubernetes is more widely used than Swarm in large environments because it provides high availability, load balancing, scheduling, and monitoring to provide an always-on, reliable, and robust solution.
The following points will highlight the differences that make K8s a more robust solution to consider.
Note: The complexity of Kubernetes installation can be overcome by using Kubernetes as a service (KaaS). Major cloud platforms offer Kaas, those include Google Kubernetes Engine (GKE), which is part of Google Cloud Platform (GCP), and Amazon Elastic Kubernetes Service (EKS).
Both solutions support scalability. However, it is easier to achieve scalability with Swarm while with Kubernetes it is more flexible to do so.
Both solutions natively support high-availability features.
Docker is a containerization platform for building and deploying applications in containers independently from the operating system. It can be installed using Docker Desktop on Windows, Linux, or macOS, and includes other solutions like Compose and Swarm. When multiple containers are created on the same host, managing them becomes more complicated. Docker Compose can be used in this case to easily manage multiple containers of one application on the same host.
In large environments, a cluster of multiple nodes becomes a need to ensure high availability and other advanced features. Here comes the need for a container orchestration solution like Docker Swarm and alternatively Kubernetes. The comparison between the features of these two platforms shows that both support scalability, high availability, and load balancing. However, Swarm is easier to install and use, while Kubernetes supports auto-scaling and built-in monitoring tools. This explains why most large organizations use Kubernetes with Docker for applications that are largely distributed across hundreds of containers.
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