A Kubernetes (K8) cluster is a systematic arrangement of nodes that automates the operation of containerized apps in a highly organized manner. The purpose of containerizing applications is to equip them with their dependences and other necessary features. The efficiency of K8 clusters also allows engineers to analyze and transport containers across different servers.
Kubernetes clusters are unique tools because they are not dependent on a specific operating system. Instead, these groupings can adapt to different operating systems and carry out their functions anywhere.
Despite its unprecedented growth in the past few years, the popularity of K8 clusters as a cloud-native application solution continues to reach new heights.
How additional tools unify K8 clusters
In today’s age of rapid technological advancements, most companies are trying to digitize their operations. SUSE Rancher is just one example of an open-source container management platform that assists companies in accelerating their digital transformation by deploying Kubernetes clusters.
If Kubernetes puts your IT system into boxes, a container management system is like a manifest controlling your inventory. Using a management tool, administrators can control, customize, and monitor any cluster in any location.
Digital transformation companies also provide complete lifecycle management for hosted Kubernetes clusters. This service enables subscribers to run applications and distribute workloads on servers like AWS EKS, Microsoft AKS, and Google GKE. In addition, the right platform allows CIS templating and scanning to minimize drift between clusters.
The critical components of a Kubernetes cluster
A Kubernetes cluster consists of two primary components: a control plane and nodes.
The control plane in itself contains an API server and a scheduler.
The control plane is responsible for the maintenance of the Kubernetes cluster. The control plane is essentially accountable for the upkeep of the Kubernetes cluster. Essential information like configuration and storage data allows the control plane to ensure the smooth operation of the K8 cluster. It also remains in close communication with the nodes to ensure that all programs run without interruptions.
The major components of the control plane are as follows:
The API server is the receiving end of the control plane. It is responsible for receiving and processing requests from internal and external servers in the system.
The API server accepts requests, determines their validity, and executes them accordingly. External components utilize REST calls to access the API, whereas internal cluster components use command-line tools such as kubectl or kubeadm.
The Kubernetes scheduler is responsible for arranging containers according to resource requirements and metrics. It identifies and analyzes pods without assigned nodes and includes them in the system.
Similarly, the nodes are responsible for running pods.
A Kubernetes node is a physical or virtual machine situated within the cloud server or on-premises. Nodes are primarily responsible for running applications.
To better explain how nodes run different applications, here’s a little analogy:
Imagine four boxes of ascending sizes, from smallest to largest. The largest box in this scenario is synonymous with the nodes. The pods operate inside the nodes while the containers are inside pods. Finally, the application denoted by the smallest box deploys inside containers.
Nodes are the building blocks of the Kubernetes cluster. Therefore, the cluster’s capacity can be enhanced by allocating more nodes.
A container runtime is a software designed to run containers. To allow the pods to run inside nodes, installing container runtime software is necessary.
The Kubernetes cluster supports various container runtime software, including Open Container Initiative-compliant runtimes like CRI-O, containerd, Docker, etc.
Pods are the basic processing units that function as a single instance of an application. Pods run on nodes, and a single pod has limited capacity and can only accommodate one container of a set of tightly coupled containers.
How to work with a Kubernetes cluster in practice
The practical functioning of a K8 cluster depends on an operator and how they define the desired end state. When determining the end state, several elements must be factored in, including apps, resources, images, and replica quantity. JSON is usually used as a manifest file to specify the application type and determine the number of replicas required to operate the system.
Developers can choose between the kubectl command-line interface or the Kubernetes API to define parameters and get the desired outcomes at the master node. Once the desired state is achieved, the Kubernetes automates the management of different clusters via the control plane. The control plane acts as a mediator by running continuous loops to ensure that the actual state matches the desired state.
In case of any anomalies in the system, the control plane is responsible for taking effective and immediate corrective measures.
Before you go
The K8 cluster is ideal for companies looking to accelerate their digital transformation. With so many ways to utilize the Kubernetes, organizations can rest assured regarding their digital operations and security.