Kubernetes is an open source container orchestration platform created by Google. Discover its usefulness, how it works, and its differences with Docker.
Containers are an operating system virtualization method that allows an application and its dependencies to be run through a set of processes isolated from the rest of the system. This method allows for the rapid and stable deployment of applications in any IT environment.
It has been booming for several years, the containers have changed the way we’ve been developingdeploy and maintain software. Because of their lightness and flexibility, they have enabled the emergence of new forms of application architectures, consisting of building applications within separate containers and then deploying these containers on a cluster of virtual or physical machines. However, this new approach has created the need for new “container orchestration” tools. to automate the deployment, management, networking, scaling and availability of container-based applications. This is the role of Kubernetes.
Kubernetes: what is it?
Kubernetes is an Open Source project created by Google in 2015. It allows Automate the deployment and management of multi-container applications on a global scale.. It is a system for running and coordinating containerized applications on a cluster of machines. It is a platform designed to fully manage the lifecycle of containerized applications and services using predictability, scalability and high availability methods.
Mainly compatible with Docker, Kubernetes can work with any container system complies with the Open Container Initiative standard in terms of image formats and runtime environments. Due to its open source nature, Kubernetes can also be used freely by anyone, anywhere.
Kubernetes: how does it work?
Architectures Kubernetes are based on several concepts and abstractions Some already existed before, others are specific to him. The main abstraction on which Kubernetes is based is the cluster, i.e. the group of machines running Kubernetes and the containers it manages.
A Kubernetes cluster must have a master the system that commands and controls all the other machines in the cluster. A highly available Kubernetes cluster replicates the functions of the master on the different machines, but only one master at a time runs the controller-manager and the scheduler.
Each cluster contains nodes Kubernetes. They can be physical or virtual machines. Nodes run pods: the most basic Kubernetes objects that can be created or managed. Each pod represents a single instance of an application or a process running on Kubernetes, and consists of one or more containers. All containers are launched and replicated as a group in the pod. This way, the user can focus on the application rather than on the containers.
The controller is another abstraction to manage how pods are deployed, created or destroyed. Depending on the different applications to be managed, there are different pods. One another abstraction is the servicewhich ensures application persistence even if the pods are destroyed. The service describes how a group of pods can be accessed via the network.
There are other key components of Kubernetes. The scheduler distributes workloads between nodes to balance resources and ensure that deployments match application needs. The controller manager as for him ensures that the state of the system (applications, workloads…) corresponds to the desired state defined in the configuration parameters Etcd.
Kubernetes: What’s the point?
The main interest of Kubernetes is to allow companies to focus on how they want the applications to work, rather than on specific implementation details. Using abstractions to manage groups of containers, the behaviors they need are separated from the components that provide them.
Kubernetes thus makes it possible to automate and simplify several tasks. First of all, we can mention the deployment of multi-container applications. Many applications reside in several containers (database, web front end, cache server…), and microservices are also developed on this model. Generally, the different services are linked by API and web protocols.
This approach has long term benefits, but requires a lot of work in the short term. Kubernetes reduces the effort required. The user tells Kubernetes how to compose an application from a set of containers, and the platform supports the deployment and ensures the synchronization of the components between them.
This tool also simplifies the scaling of containerized applications. Indeed, applications need to be scaled to keep pace with demand and optimize the use of resources. Kubernetes allows to automate this scaling. The platform also allows the continuous deployment of new versions of applications, eliminating maintenance time. Its mechanisms allow to update container images and even to go back in case of problem.
Kubernetes and its APIs also allow to networking of containersservice discovery and storage. Finally, not tied to a specific cloud environment or technology, Kubernetes can be launched in any environment : public cloud, private stacks, physical or virtual hardware… it is even possible to mix environments.
Kubernetes vs. Docker Swarm: what’s the difference?
Kubernetes is very often compared with the Docker container storage platform, and more precisely with Docker Swarm the native clustering solution for the Docker contacts. These two tools offer functionalities for creating and managing virtual containers. However, there are many differences between the two systems.
First of all, Docker proves to be easier to use than Kubernetes. One of the flaws often reproached to Kubernetes is indeed its complexity. For example, Kubernetes is very long to install and configure, and requires some planning because the nodes must be defined before starting. The procedure also differs for each operating system.
For its part, Docker Swarm uses Docker’s CLI to run all portions of its program. It just learn to master this set of tools… to be able to create environments and configurations. There is also no need to map clusters before you start.
In addition, Kubernetes can be run over Docker but needs to know the characteristics of their respective CLI’s to be able to access the data via the API. You need to know the Docker CLI to navigate within the structure, and the Kubernetes kubectl CLI to run the programs.
In comparison, the use of Docker Swarm is similar to that of other Docker tools such as Compose. The same Docker CLI is used, and it is even possible to launch new containers with a simple command. It is fast, versatile and easy to use, Docker therefore has a certain advantage over Kubernetes in terms of usability..
The two platforms also used to differ in terms of the number of containers that could be launched, as well as their size. In this area, Kubernetes had the advantage. However, theecent updates from Docker have narrowed the gap.
Both systems can now support a maximum of 1,000 clusters and 30,000 containers. However, a test conducted by Docker in March 2016 revealed that Docker can launch the same number of containers as Kubernetes five times faster. However, once the containers are launched, Kubernetes retains an advantage in terms of responsiveness and flexibility.
In any case, nothing prevents the use of both Kubernetes and Docker Swarm. It is for example possible to use Docker and Kubernetes together to coordinate the programming and execution of Docker containers on Kubelets. The Docker engine takes care of executing the container image, while service discovery, task balancing and networking are managed by Kubernetes. These two tools are therefore very suitable for the development of modern Cloud architecture despite their differences.