Kubernetes Explained | SevenMentor

The Ultimate Guide to Kubernetes Explained: Container Orchestration for Beginners and Enterprise Scale

If you are working in software development or IT operations, you probably have already encountered the term “Kubernetes” within the last couple of years. Often enough Kubernetes is presented as the backbone of cloud computing or even the state-of-the-art infrastructure. Colloquially even just K8s is being used. However, we will try to explain in detail what Kubernetes actually is.

Modern software can no longer be deployed by copying a single file onto a web server. Many modern applications are comprised of hundreds of individual services and applications, which are individually packaged and run as containers. And then there’s the issue of where to run them all—it's common for companies to spread their applications across a multitude of cloud providers, which in turn can make tracking and maintaining individual applications very difficult to manage manually, akin to attempting to balance spinning chainsaws on top of unicycles.

That is where Kubernetes comes into play.

This in-depth Kubernetes tutorial – Kubernetes Explained – teaches container orchestration and explains Kubernetes in-depth. It describes the architecture of Kubernetes, and the step-by-step tutorial on Kubernetes is especially for Kubernetes beginners.

What is Kubernetes? Demystifying Modern Container Orchestration

To understand what Kubernetes is, first we need to understand the problem it was created to solve.

The way web applications were deployed in the early days of the web was to host them directly on physical servers. However, very quickly it became apparent that there were going to be many different versions of many libraries, and it was not going to be practical to have different versions of different libraries installed on each server to support each application. This led to the use of virtual machines (VMs). Each virtual machine would run its own copy of an operating system, and so multiple different versions of different applications could be run on a single physical server, each in its own virtual machine. Virtual machines provided the necessary isolation between different applications, but they were very resource-intensive and also very slow to start up a new virtual machine.

Containers have revolutionized the way applications are developed and run. The containers developed using Docker for example, allow an application and all of its dependencies to be packaged up into a lightweight, lightweight, isolated unit that can run on any server in any data center around the world. This makes for a very consistent and development-friendly environment.

With the easy way of using Docker on your local development machine for one application consisting of one container, it is totally different when you run 500 containers on 50 servers in production. Then it becomes a real challenge to operate your applications. You want to automate as much as possible in order to avoid mistakes. There are several challenges that need to be solved when running containerized applications in production. What to do when one of your containers crashes in the middle of the night? How to scale up your instances during peak traffic? How to distribute incoming traffic to your instances? How to ensure that traffic to different services in your application is distributed evenly?

Enter Kubernetes

Kubernetes (often abbreviated as K8s, counting the 8 letters between K and s) is an open-source container orchestration platform for automated management of containerized applications. Originally created by Google for their internal use, it was donated to the Cloud Native Computing Foundation (CNCF) in 2015. Kubernetes serves as the underlying engine for many modern cloud systems.

It was originally created by Google as part of their Borg internal cluster management system. Once Google open-sourced part of the system, it was donated to the Cloud Native Computing Foundation (CNCF) in 2015. Today it is the core underlying technology for many cloud providers.

Kubernetes can be likened to the auto-magic conductor of an orchestra made up of containers. The conductor (Kubernetes) ensures that all the violinists (your front-end services), the cellists (your back-end APIs), and the drummers (your databases) all play well together in perfect harmony. The auto-magic conductor is able to speed up or slow down an orchestra as necessary and can even immediately replace a musician who has dropped his or her instrument.

Why Do Businesses and Developers Need Kubernetes?

So why is Kubernetes the new industry standard for cloud technologies? Here are four operational advantages for you to consider.

1. Automated Self-Healing

Kubernetes is able to detect and kill a failing container instantly and start new instances of the failed container as needed. It can even detect failure of an entire host, and automatically reschedule containers that were running on that host on other hosts in the cluster without any downtime for end users.

2. Auto-Scaling on Demand

As traffic increases such as on Black Friday, it is common for organizations to scale their applications to handle the increase in demand. Kubernetes automatically scales the application up as traffic increases and then scales it back down once traffic decreases to cut costs.

3. Seamless Zero-Downtime Deployments

No longer will you have to schedule late night maintenance windows for the deployment of updates to your application. Simply release a new version of your application as a new container version and Kubernetes will then perform a rolling update replacing old containers with new ones one at a time. Should any issues occur during the deployment of the new container version Kubernetes will automatically roll back to the previous version ensuring that your application remains always up and running.

4. Vendor Neutrality and Portability

Kubernetes runs on top of Amazon Web Services (EKS), Google Cloud (GKE), and Microsoft Azure (AKS); on bare metal for private cloud / data center deployments; as well as on edge devices (e.g., Raspberry Pi). Thus, there is no lock-in, and corporations can run their cloud as they see fit.

Understanding Kubernetes Architecture: Control Plane vs. Worker Nodes

In order to fully understand how K8s works, one must understand the architecture behind Kubernetes. Here we will briefly describe the architecture of a normal Kubernetes setup (a cluster), which contains 2 key components that function to allow the cluster to be managed in order to achieve the goals for which the system was created: the control plane and the worker nodes.

The Control Plane (The Brain)
Worker Nodes (The Muscle)

+-------------------------------------------------------------------+

| KUBERNETES CLUSTER |

| |

| +-----------------------------------------------------------+ |

| | CONTROL PLANE | |

| | +--------------------+ +----------------------------+ | |

| | +--------------------+ +----------------------------+ | |

| | +--------------------+ +----------------------------+ | |

| +-----------------------------------------------------------+ |

| | |

| +-----------------------+-----------------------+ |

| | | |

| +-----+---------------------+ +-------------+-----+ |

| | +---------------------+ | | +---------------+ | |

| | +---------------------+ | | +---------------+ | |

| | +---------------------+ | | +---------------+ | |

| | +---------------------+ | | +---------------+ | |

| | | [Pod] [Pod] | | | | [Pod] | | |

| | +---------------------+ | | +---------------+ | |

| +---------------------------+ +-------------------+ |

+-------------------------------------------------------------------+

The Control Plane: The Cluster's Command Center

The Control Plane consists of four components that together make up the cluster’s “brain” and function to manage the cluster as a whole. The Control Plane makes global decisions for the cluster, detects failures and enforces the desired state of the cluster.

The main components of the Control Plane are the following: The API Server

(kube-apiserver): The front door to the cluster. When you run commands in the cluster with kubectl or cloud management dashboards, they all go through the API Server.
etcd: A highly available, secure, distributed database for critical cluster data and configuration, such as cluster state. If this database loses data for any reason, the cluster will lose memory.
The “traffic cop” for the Cluster – kube-scheduler. This component evaluates newly created containers and decides which Node (or Nodes) within a Cluster has the required resources to run them. The scheduler can make decisions based on a variety of data including available resources on each Node, the hardware that each Node has, as well as a plethora of other policy based criteria.
kube-controller-manager: This is the active manager for the cluster. It is running continuous loops of processing trying to make sure the current state of the cluster is equal to the desired state. Therefore, in the case of the four replicas of the web server mentioned earlier, if one of the web servers crashed, the controller manager for the replication controller would detect this shortage and start a new web server.
Worker Nodes: Where the Heavy Lifting Happens
Worker Nodes, on the other hand, are the physical or virtual servers in your data center where your workloads actually run. Each worker node runs three fundamental components:
Kubelet: The agent on every node (worker node) that talks to the API server of the control plane (cluster). It makes sure the containers that have been scheduled on that host are running and healthy.
kube-proxy: The network communication rules agent that routes incoming traffic from outside the cluster to running containers.
Container Runtime: The runtime (e.g., containerd, CRI-O, rkt) in which the actual software that runs your containers on your system.

Core Kubernetes Concepts Every Developer Must Know

Kubernetes for Beginners: Core Objects You’ll cover core objects you’ll interact with on a daily basis. But for a beginner, the terms can be even more confusing than regular Docker stuff.

+----------------------------------------------------------------------+

| KUBERNETES NAMESPACE |

| |

| +----------------------------------------------------------------+ |

| | SERVICE (Stable IP / DNS Load Balancer) | |

| +----------------------------------------------------------------+ |

| | |

| v |

| +----------------------------------------------------------------+ |

| | DEPLOYMENT (Manages lifecycle & scaling) | |

| | | |

| | +------------------------+ +------------------------+ | |

| | | POD 1 | | POD 2 | | |

| | | +------------------+ | | +------------------+ | | |

| | | +------------------+ | | +------------------+ | | |

| | | +------------------+ | | +------------------+ | | |

| | +------------------------+ +------------------------+ | |

| +----------------------------------------------------------------+ |

+----------------------------------------------------------------------+

1. Pods: The Smallest Unit in K8s

In Kubernetes you don’t deploy containers directly. Instead you deploy Pods. Pods are the smallest unit in K8s. A Pod is a wrapper for one or more containers. The containers in a Pod are tightly coupled. This means that they share a network IP, storage volumes and runtime environment. Normally a Pod would contain only one container.

2. Deployments: Declarative App Management

The Pods that you create on their own are “transient” or “short-lived”. In other words, once isolated Pods die (and they usually die for reasons outside of your control) they are GONE. However, with the creation of the Deployment object, you can declare how many identical Pods you wish to create and have the system manage to create those replicas for you. You can then also have the Deployment roll out an application update to those replicas, scale the number of replicas up or down, and even automatically have the Deployment recreate any of the Pods that die for reasons unknown.

3. Services: Reliable Network Endpoints

Pods are highly dynamic, therefore their IP addresses often change. Since Services are typically used for applications, which are never static, their use is especially helpful in this scenario. A Service provides a single static IP address and a DNS name to access a set of Pods. It can then distribute incoming traffic to the Pods, that are capable of processing the request.

4. ConfigMaps and Secrets: Environment Isolation

To maintain a good level of security it is very important to avoid hard coding password or using environment variables in your application containers images, especially passwords.

ConfigMaps: Store non-sensitive configuration parameters (like API endpoints or database hostnames).

Secrets: Store sensitive encrypted data such as passwords, SSH keys or OAuth tokens.

5. Persistent Volumes (PV): Long-Term Storage

Containers are by default meant to be short lived, and the data in them is meant to be thrown away when the container is removed. If you’re running a database, like PostgreSQL, inside of a K8s cluster then you’re going to need some persistent storage that survives the container’s demise. This is where Persistent Volumes (PV) come in to play. They are long-lived storage provided to your cluster that can be attached to containers on an as needed basis.

Hands-On Kubernetes Tutorial: Deploying Your First Web Application

While reading theory about Kubernetes for Beginners is very important, the best way to learn about it is by building something yourself. Therefore in this mini Kubernetes Tutorial we will create an NGINX web application by using declarative YAML files.

Prerequisites

Step 1: Install Docker Desktop or Minikube.

Download and install kubectl, the command line tool for running and managing Kubernetes.

Step 1: Create a Deployment Manifest

In Kubernetes declarative syntax means that you describe the application you want to run instead of telling Kubernetes how to run it. This usually means writing files in YAML or JSON that get applied to your cluster.

Create a file named nginx-deployment.yaml:

YAML

apiVersion: apps/v1

kind: Deployment

metadata:

name: nginx-web-app

labels:

app: web

spec:

replicas: 3

selector:

matchLabels:

app: web

template:

metadata:

labels:

app: web

spec:

containers:

- name: nginx

image: nginx:latest

ports:

- containerPort: 80

What is happening here?

kind: Deployment: Tells Kubernetes to construct a Deployment controller.
replicas: 3: Requests 3 identical copies of this web server running simultaneously.
image: nginx:latest: Pulls the public NGINX image from Docker Hub.

Step 2: Apply the Deployment

kubectl apply -f nginx-deployment. yaml

Bash

kubectl apply -f nginx-deployment. yaml

Verify your Pods are running.

Bash

kubectl get pods

Output:

NAME READY STATUS RESTARTS AGE

nginx-web-app-769649c595-2xk8l 1/1 Running 0 12s

nginx-web-app-769649c595-8vjlp 1/1 Running 0 12s

nginx-web-app-769649c595-s92m4 1/1 Running 0 12s

You now have three active instances running on your cluster!

Step 3: Expose the App via a Service

Your Pods are currently only accessible within the internal cluster network. To make your web server accessible externally, create a file named nginx-service.yaml:

YAML

apiVersion: v1

kind: Service

metadata:

name: nginx-service

spec:

type: LoadBalancer

selector:

app: web

ports:

- protocol: TCP

port: 80

targetPort: 80

Apply the service configuration:

Bash

kubectl apply -f nginx-service. yaml

Check your exposed service IP:

Bash

kubectl get service nginx-service

Navigating to your allocated IP address in your browser will display the official NGINX welcome page!

Step 4: Test Kubernetes Self-Healing in Action

Want to see the power of self-healing in action? For demonstration purposes, delete one of the running Pods. Note that this will cause one of the replicas to fail, but the deployment will re-create it automatically as described in the spec. Here’s how to delete a Pod:

Bash

kubectl delete pod nginx-web-app-769649c595-2xk8l

Immediately after running the above command, let’s run the kubectl get pods command again to see how Kubernetes self-heals the pods. This time, we will see how the Kubernetes cluster automatically creates a new Pod for us to reach the same number of Pods that we originally specified in our deployment’s YAML file (3 Pods in this case):

Managed Kubernetes: EKS, GKE, and AKS

Setting up and managing a control plane from scratch (using tools like kubeadm) requires deep infrastructure expertise and significant maintenance overhead. For most production workloads, organizations prefer managed Kubernetes services.

+------------------------------------------------------------------------+

| CLOUD MANAGED KUBERNETES |

| |

| +------------------------------------------------------------------+ |

| | CONTROL PLANE (Managed & Monitored automatically by Cloud Provider) | |

| | [ API Server ] [ etcd Storage ] [ Scheduler ] [ Controllers]| |

| +------------------------------------------------------------------+ |

| | |

| +----------------------------+----------------------------+ |

| | | | |

| v v v |

| +---------------+ +---------------+ +---------------+ |

| +---------------+ +---------------+ +---------------+ |

| | | | |

| +------------------------------------------------------------------+ |

| | WORKER NODES (Customer Compute: EC2, Compute Engine, Azure VMs) | |

| +------------------------------------------------------------------+ |

+------------------------------------------------------------------------+

A managed provider will manage the high-availability control plane for you and keep it up-to-date and perform etcd backups for you. You can then just focus on adding worker nodes in order to add more application workloads.

Amazon EKS is integrated with Amazon networking, IAM security and Amazon storage.

Google GKE (Google Kubernetes Engine): The most advanced managed Kubernetes service on the market. Auto-scaling for the control plane, and turnkey operational management of the cluster (operational automation) for the worker nodes. You only pay for the worker nodes that are running your applications.
Microsoft Azure AKS (Azure Kubernetes Service): AKS allows for the integration of identity with Azure Active Directory / Entra ID for the enterprise IT user.

Key Takeaways: Why You Should Learn Kubernetes Today

Industry Standard: 80%+ of enterprises running containerized workloads in production on Kubernetes.

High-Demand Career Path: DevOps engineers, cloud architects, and site reliability engineers (SREs) fluent in Kubernetes command premium positions across the tech industry.
Developer Productivity for Developers: Simplify the way you develop, by deploying your applications on a standard way of doing things, and focusing on writing code instead of setting up and maintaining the infrastructure that your application runs on.

Got Questions? Here Are Some FAQs

1. What is the difference between Docker and Kubernetes?

Docker is a containerization platform for developing, shipping and running single applications as isolated and portable containerized software packages (containers). Kubernetes is a container orchestration platform for managing hundreds of containers distributed across multiple hosts as a unified whole (cluster). In practice, Docker and Kubernetes are different software systems and are used in tandem.

2. Is Kubernetes difficult for beginners to learn?

Don’t let the terminology and complexity of the whole system keep you from learning the basics of the system. And there are plenty of resources out there for people to learn to manage their own applications as a developer, including local examples and scenarios with tools like Minikube to allow developers with basic knowledge of Linux and how to use Docker to learn the basics of Pods, Deployments and Services and how to use them for their applications.

3. Can I run stateful applications like databases on Kubernetes?

Yes. While Kubernetes was designed for stateless web applications first (e.g. HTTP servers like nginx), there are features like StatefulSets, Persistent Volumes as well as Operators that make it possible to run stateful applications like databases (e.g. PostgreSQL, MySQL, MongoDB) with persistence and automated failover.

4. What is kubectl and why do I need it?

Kubectl, which is the official command line interface client for the Kubernetes system, is used by the system administrators as well as the application developers in order to connect directly to the API Server of the cluster of the system and issue commands in order to check the available resources of the system, to deploy applications, check system logs and also to debug running containers in order to solve any problem that might occur in the running of the containers.

5. Should I manage my own cluster or use a cloud service?

For development / testing on your local machine you might want to consider using Minikube or Kind. For production however it is recommended to use a managed service like AWS EKS, Google GKE or Azure AKS to not get stuck in maintaining the high-availability Control Plane.

blog Links:

Anthropic AI Tool

What is Writesonic

What is Claude AI

AI Engineer Roadmap

What is JasperAI

What is Copy AI

Do visit our channel to know more: SevenMentor

SevenMentor

Expert trainer and consultant at SevenMentor with years of industry experience. Passionate about sharing knowledge and empowering the next generation of tech leaders.

#Technology#Education#Career Guidance