Kubernetes has emerged as a crucial component of contemporary software development, particularly for businesses that operate on a large scale. It is an open-source container orchestration technology that was initially created by Google and automates the deployment, scaling, and management of containerized applications. With Kubernetes, developers have the freedom to concentrate on creating code rather than worrying about the supporting infrastructure because of the framework it provides for managing distributed systems. For businesses that want to develop and deploy applications rapidly and effectively, with high availability, scalability, and resilience, Kubernetes is essential. This blog will explain what Kubernetes is, how it functions, its architecture and core components, and why modern software development needs it.
Kubernetes and How It Works
As technology is rapidly changing, the deployment, scaling, and maintenance of containerized applications are all automated via the open-source container orchestration technology known as Kubernetes.
Containerization is a process of packaging software in a way that it can run reliably across different computing environments. It has grown in popularity in recent years because it enables developers to build, package, and deploy applications more rapidly and consistently. Several applications can operate on a single host operating system using this containerization technique without interfering with one another. Each container has its own set of dependencies, libraries, and configuration files and is isolated from the others.
Let's understand more clearly with an example. Consider running a web application you have for development purposes on your local environment. To function, the application needs particular versions of Node.js, a database, and a few third-party libraries. As you are using your computer for other purposes as well, installing these dependencies globally and running the chance of conflicts with other programs is not something you want to do. Instead, you can package the application and its dependencies separately from the rest of the system by the container and run in any computer that supports containerization technologies, such as Docker. That container can also be deployed to a cloud platform like AWS or Google Cloud and based on demand, it can be quickly scaled up or down, making it simple to handle traffic peaks without over-provisioning resources.
A Container Orchestrator is a tool that simplifies the management of containerized applications and helps ensure that they are running properly across a distributed system which automates tasks such as network configuration, scaling, and load balancing. Kubernetes is created based on this principle that provides a powerful set of features for managing containerized applications such as:
Container orchestration: Kubernetes helps to automate the deployment, scaling, and management of containerized applications across a cluster of nodes.
Service discovery and load balancing: Kubernetes has an internal DNS system that helps to discover containers and communicate with each other. It also offers load balancing for distributing traffic between containers.
Self-healing: The health of containers is being monitored continuously and restarted or replaced automatically by Kubernetes if they fail or become unresponsive.
Auto-scaling: Kubernetes can automatically scale the number of containers based on resource utilization and spikes in traffic.
Rolling updates and rollbacks: Without downtime, Kubernetes offers a way to perform updates to containers and if there are any critical issues, It allows for easy rollbacks.
Config management: Kubernetes offers a way to manage configuration files and environment variables for containers.
Storage orchestration: Kubernetes can manage storage for containerized applications, including persistent storage volumes.
Security: Kubernetes offers a range of security features, including role-based access control (RBAC), network policies, and container image verification
Kubernetes Architecture and Components
As a distributed system for managing containerized applications, Kubernetes is composed of a cluster of nodes and those nodes in a Kubernetes cluster are divided into two types:
The Component of Kubernetes cluster (Source: Kubernetes)
1. Master Node: The master node runs the Kubernetes control plane components which is a collection of Kubernetes components that are responsible for managing the state of the cluster, scheduling applications, and maintaining communication between nodes. Control plane containers the following components:
Kubernetes API server: This is the central management point for the Kubernetes cluster. It provides an HTTP REST API that allows end users to interact with the Kubernetes cluster, including creating and managing pods, services, and other objects. The other cluster components also communicate with this API server. The API server is responsible for exposing the cluster API endpoints and processing all API requests as well as authentication and authorization. This API server is the only component that communicates with etcd and also coordinates all the processes between the control plane and worker node components.
etcd: This is a distributed key-value store used by Kubernetes to store cluster configuration and state information. We can call it the brain of the cluster. It provides a reliable and consistent way to store data across the cluster. etcd stores all configurations, states, and metadata of Kubernetes objects such as pods, secrets, deployment, daemonset, configmaps, etc. As it was mentioned earlier, It only communicates with the API server.
Kubernetes Scheduler: This component is responsible for scheduling pods onto worker nodes based on available resources and other constraints.
To deploy a pod, we specify the pod requirements that include CPU, memory, priority, persistent volumes (PV), etc and they deploy it in the cluster. Then Kubernetes scheduler identifies the pod creation request and chooses the best node for a pod that satisfies all the requirements.
Kube Controller Manager: In Kubernetes, controllers are programs that run endless control loops which continuously observe the state of objects in case there is any difference between the actual and desired state of those objects. The controller manager runs the core controllers that monitor and takes necessary action to maintain the desired state.
Cloud Controller Manager: The Cloud Controller Manager (CCM) is a component of the Kubernetes control plane that runs when Kubernetes is deployed in cloud environments. It provides an interface between the Kubernetes control plane and the cloud platform API and enables interaction between Kubernetes and the cloud provider's underlying infrastructure. Load balancers, block storage, network routes, etc are a few of the resources that CCM is responsible for managing.
2. Worker Node: The worker node(s) are responsible for running containers and serving application traffic. They contain the following core components:
Kubelet: This is an agent that runs as a daemon on each worker node and communicates with the Kubernetes API server to manage containers and pods from pod specification. It creates containers based on pod specifications. By starting, stopping, and restarting the containers as needed, the Kubelet makes sure they are running and in good condition. Moreover, it monitors how much CPU and memory are being used by the containers and provides this data to the Kubernetes API server.
Kube-proxy: The kube-proxy is a network proxy and load balancer for Kubernetes services. It executes on each worker node as a daemonset and routes traffic to the proper container or pod in accordance with the configuration of the service. Iptables rules, which is a default mode, are used by the kube-proxy to control network traffic and guarantee the service's scalability and high availability. With this mode, kube-proxy choose the backend pod randomly for load balancing. Once the connection is made, requests are sent to the same pod until the connection is broken.
Container runtime: Container runtime is a program that runs containers on worker nodes. It runs on all the nodes in the Kubernetes cluster. It is responsible for starting and stopping containers as well as pulling images from container registries, and allocating containers resources such as CPU and memory. Organizations can select the container runtime that best suits their needs thanks to Kubernetes' support for a variety of them.
In this article, we have discussed the fundamentals of Kubernetes, such as containerization, container orchestrators, and the main elements of the Kubernetes architecture. We've seen how Kubernetes offers attributes like fault tolerance, scalability, and high availability, all of which are essential for operating mission-critical applications.
The fundamental building blocks of Kubernetes, known as Kubernetes objects, will be covered in more detail in the forthcoming article. We will explore the different types of objects, their properties, and how a Kubernetes cluster can use them to manage its resources and applications.
Stay tuned for more information about the interesting Kubernetes world!
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