Kubernetes is a popular open-source platform for managing containerized applications across multiple hosts. It provides a consistent and reliable way to deploy, scale, and update applications in different environments. In this blog post, we will cover some of the basic concepts and features of Kubernetes that you need to know before getting started.

Kubernetes (also known as k8s) is a system that automates the deployment, scaling, and management of containerized applications. It was originally developed by Google based on their experience of running production workloads at scale with containers. It is now maintained by the Cloud Native Computing Foundation (CNCF) and has a large and active community of contributors and users.

Containers are a way of packaging an application and its dependencies into a single unit that can run anywhere. Containers provide isolation, portability, and efficiency for applications. However, containers alone are not enough to handle complex scenarios such as:

• How to run multiple containers across different machines?

• How to ensure high availability and fault tolerance for applications?

• How to balance the load among containers?

• How to update or roll back applications without downtime?

• How to monitor and troubleshoot applications?

This is where Kubernetes comes in. Kubernetes gives you the platform to schedule and run containers on clusters of physical or virtual machines. Kubernetes also provides various features and tools to help you manage your containerized applications throughout their lifecycle.

Kubernetes architecture divides a cluster into components that work together to maintain the cluster's defined state. A Kubernetes cluster is a set of node machines for running containerized applications. A node can be either a physical machine or a virtual machine. A cluster can have one or more nodes.

The main components of a Kubernetes cluster are:

1. The master node(s): runs the control plane components that are responsible for managing the cluster state and coordinating all activities in the cluster. The control plane components include:

• The API server: the entry point for all REST commands used to control the cluster. It processes and validates requests from users, clients, and other components.

• The etcd: a distributed key-value store that stores the configuration data of the cluster. It acts as the source of truth for the cluster state.

• The scheduler: decides which nodes should run which pods based on resource availability and scheduling policies.

• The controller manager: runs various controllers that regulate the behavior of different objects in the cluster such as nodes, pods, services, etc.

2. The worker nodes: run the workload containers that make up your application. Each worker node runs two essential components:

• The kubelet: an agent that communicates with the API server and manages pods on its node. It ensures that pods are running according to their specifications.

• The kube-proxy: a network proxy that maintains network rules on its node. It enables network communication between pods across nodes.

A pod is the smallest unit of deployment in Kubernetes. A pod consists of one or more containers that share resources such as storage volumes, network interfaces, etc. Pods are ephemeral; they can be created, deleted, moved, or replicated as needed by controllers.

A service is an abstraction that defines a logical set of pods and provides access to them via a stable name or IP address. Services allow clients to discover and communicate with pods without knowing their exact locations.

There are many other concepts and features in Kubernetes such as deployments, replica sets, stateful sets, daemon sets, jobs, cron jobs, config maps, secrets, ingresses, network policies, storage classes, persistent volumes, persistent volume claims, horizontal pod autoscalers, vertical pod autoscalers, operators etc., but we will not go into details here.

Kubernetes offers many benefits for developers and operators who want to run containerized applications at scale,

such as:

You can run your applications on any platform that supports Kubernetes such as public clouds (e.g., AWS, GCP, Azure), private clouds, hybrid clouds, or bare metal servers.

You can easily scale your (stateless) applications up or down by adding or removing nodes or pods without affecting the availability or performance of your application. For more complex and stateful workloads we can use community built operators or can build our own operators with CRDs if required.

You can ensure high availability and fault tolerance for your applications by using features such as replication controllers along with pod topology spread constraints (e.g. spread pods in all availability zones in AWS etc.)