Introduction to Kubernetes (K8S)

Before Kubernetes, developers used Docker to package and run their applications inside containers. Docker made creating and running a single container easy, but it became hard to manage many containers running across different machines. For example, what if one container crashes? How do you restart it automatically? Or how do you handle hundreds of containers that need to work together?

That’s why Kubernetes was created. It helps manage and organize containers automatically. Kubernetes makes sure your containers keep running, can scale up when there’s more traffic, and can move to healthy machines if something goes wrong.

What is Kubernetes?

Kubernetes (also called K8s) is an open-source platform that helps you automates the deployment, scaling, and management of containerized applications. In simple words, if you're running a lot of apps using containers (like with Docker), Kubernetes helps you organize and control them efficiently just like a traffic controller for your apps.

You tell Kubernetes what your app should look like (how many copies to run, what to do if something fails, etc.), and Kubernetes takes care of the rest making sure everything is up and running properly.

Example

Now after discussing about the Kubernetes let's take an example to understand how Kubernetes help us in real-world:

Let’s say you created a food delivery app and it runs in a container using Docker. When your app becomes popular and thousands of users start placing orders, you need to run more copies of it to handle the load.

Instead of doing this manually, you use Kubernetes to say:

"Hey Kubernetes, always keep 5 copies of my app running. If one stops, replace it. And if more users come, increase the number of copies automatically."

Kubernetes listens to this instruction and makes it happen automatically.

Key Terminologies

Think of Kubernetes as a well-organized company where different teams and systems work together to run applications efficiently. Here’s how the key terms fit into this system:

1. Pod

A Pod is the smallest unit you can deploy in Kubernetes. It wraps one or more containers that need to run together, sharing the same network and storage. Containers inside a Pod can easily communicate and work as a single unit.

2. Node

A Node is a machine (physical or virtual) in a Kubernetes cluster that runs your applications. Each Node contains the tools needed to run Pods, including the container runtime (like Docker), the Kubelet (agent), and the Kube proxy (networking).

3. Cluster

A Kubernetes cluster is a group of computers (called nodes) that work together to run your containerized applications. These nodes can be real machines or virtual ones.

There are two types of nodes in a Kubernetes cluster:

1. Master node (Control Plane):
   • Think of it as the brain of the cluster.
   • It makes decisions, like where to run applications, handles scheduling, and keeps track of everything.
2. Worker nodes:
   • These are the machines that actually run your apps inside containers.
   • Each worker node has a Kubelet (agent), a container runtime (like Docker or containerd), and tools for networking and monitoring.

4. Deployment

A Deployment is a Kubernetes object used to manage a set of Pods running your containerized applications. It provides declarative updates, meaning you tell Kubernetes what you want, and it figures out how to get there.

5. ReplicaSet

A ReplicaSet ensures that the right number of identical Pods are running.

6. Service

A Service in Kubernetes is a way to connect applications running inside your cluster. It gives your Pods a stable way to communicate, even if the Pods themselves keep changing.

7. Ingress

Ingress is a way to manage external access to your services in a Kubernetes cluster. It provides HTTP and HTTPS routing to your services, acting as a reverse proxy.

8. ConfigMap

A ConfigMap stores configuration settings separately from the application, so changes can be made without modifying the actual code.

Imagine you have an application that needs some settings, like a database password or an API key. Instead of hardcoding these settings into your app, you store them in a ConfigMap. Your application can then read these settings from the ConfigMap at runtime, which makes it easy to update the settings without changing the app code.

9. Secret

A Secret is a way to store sensitive information (like passwords, API keys, or tokens) securely in a Kubernetes cluster.

10. Persistent Volume (PV)

A Persistent Volume (PV) in Kubernetes is a piece of storage in the cluster that you can use to store data — and it doesn’t get deleted when a Pod is removed or restarted.

11. Namespace

A Namespace is like a separate environment within your Kubernetes cluster. It helps you organize and isolate your resources like Pods, Services, and Deployments.

12. Kubelet

A Kubelet runs on each Worker Node and ensures Pods are running as expected.

13. Kube-proxy

Kube-proxy manages networking inside the cluster, ensuring different Pods can communicate.

Benefits of using Kubernetes

1. Automated Deployment and Management

• If you are using Kubernetes for deploying the application then no need for manual intervention kubernetes will take care of everything like automating the deployment, scaling, and containerizing the application.
• Kubernetes will reduce the errors that can be made by humans which makes the deployment more effective.

2. Scalability

• You can scale the application containers depending on the incoming traffic Kubernetes offers Horizontal pod scaling the pods will be scaled automatically depending on the load.

3. High Availability

• You can achieve high availability for your application with the help of Kubernetes and also it will reduce the latency issues for the end users.

4. Cost-Effectiveness

• If there is unnecessary use of infrastructure the cost will also increase kubernetes will help you to reduce resource utilization and control the overprovisioning of infrastructure.

5. Improved Developer Productivity

• Developers can focus on writing code rather than managing deployments, as Kubernetes automates much of the deployment and scaling process

Deploying and Managing Containerized Applications with Kubernetes

Follow the steps mentioned below to deploy the application in the form of containers.

Step 1: Install Kubernetes and setup Kubernetes cluster there should be minimum at least one master node and two worker nodes you can set up the Kubernetes cluster in any of the cloud which are providing the Kubernetes as an service.

Step 2: Now, create a deployment manifest file. In this file, you specify the desired number of Pods, the container image, and the resources required. After creating the manifest, apply it using the kubectl command.

Step 3: After creating the pods know you need to expose the service to the outside for that you need to write one more manifest file which contains service type (e.g., Load Balancer or Cluster IP), ports, and selectors.

Use Cases of Kubernetes in Real-World Scenarios

Following are the some of the use cases of kuberneets in real-world scenarios

1. E-commerce

You deploy and manage the e-commerce websites by autoscaling and load balancing you can manage the millions of users and transactions.

2. Media and Entertainment

You can store the static and dynamic data can deliver it to the across the world with out any latency to the end users.

3. Financial Services

Kubernetes is well suited for the critical application because of the level of security it is offering.

4. Healthcare

You can store the data of patient and take care the outcomes of the health of patient.

Kubernetes v/s Other Container Orchestration Platforms

Features of Kubernetes

The following are some important features of Kubernetes:

1. Automated Scheduling

Kubernetes provides an advanced scheduler to launch containers on cluster nodes. It performs resource optimization.

2. Self-Healing Capabilities

It provides rescheduling, replacing, and restarting the containers that are dead.

3. Automated Rollouts and Rollbacks

It supports rollouts and rollbacks for the desired state of the containerized application.

4. Horizontal Scaling and Load Balancing

Kubernetes can scale up and scale down the application as per the requirements.

5. Resource Utilization

Kubernetes provides resource utilization monitoring and optimization, ensuring containers are using their resources efficiently.

6. Support for multiple clouds and hybrid clouds

Kubernetes can be deployed on different cloud platforms and run containerized applications across multiple clouds.

7. Extensibility

Kubernetes is very extensible and can be extended with custom plugins and controllers.

8. Community Support

Kubernetes has a large and active community with frequent updates, bug fixes, and new features being added.

Kubernetes v/s Docker

The following table shows the comparison between Kubernetes vs Docker

Architecture of Kubernetes

Kubernetes follows the client-server architecture where we have the master installed on one machine and the node on separate Linux machines. It follows the master-slave model, which uses a master to manage Docker containers across multiple Kubernetes nodes. A master and its controlled nodes(worker nodes) constitute a “Kubernetes cluster”. A developer can deploy an application in the docker containers with the assistance of the Kubernetes master. 

Key Components of Kubernetes

1. Kubernetes-Master Node Components

Kubernetes master is responsible for managing the entire cluster, coordinates all activities inside the cluster, and communicates with the worker nodes to keep the Kubernetes and your application running. This is the entry point of all administrative tasks. When we install Kubernetes on our system we have four primary components of Kubernetes Master that will get installed. The components of the Kubernetes Master node are: 

API Server

The API server is the entry point for all the REST commands used to control the cluster. All the administrative tasks are done by the API server within the master node. If we want to create, delete, update or display in Kubernetes object it has to go through this API server.API server validates and configures the API objects such as ports, services, replication, controllers, and deployments and it is responsible for exposing APIs for every operation. We can interact with these APIs using a tool called kubectl. 'kubectl' is a very tiny go language binary that basically talks to the API server to perform any operations that we issue from the command line. It is a command-line interface for running commands against Kubernetes clusters 

Scheduler

It is a service in the master responsible for distributing the workload. It is responsible for tracking the utilization of the working load of each worker node and then placing the workload on which resources are available and can accept the workload. The scheduler is responsible for scheduling pods across available nodes depending on the constraints you mention in the configuration file it schedules these pods accordingly. The scheduler is responsible for workload utilization and allocating the pod to the new node. 

Controller Manager

Also known as controllers. It is a daemon that runs in a non terminating loop and is responsible for collecting and sending information to the API server. It regulates the Kubernetes cluster by performing lifestyle functions such as namespace creation and lifecycle event garbage collections, terminated pod garbage collection, cascading deleted garbage collection, node garbage collection, and many more. Basically, the controller watches the desired state of the cluster if the current state of the cluster does not meet the desired state then the control loop takes the corrective steps to make sure that the current state is the same as that of the desired state. The key controllers are the replication controller, endpoint controller, namespace controller, and service account, controller. So in this way controllers are responsible for the overall health of the entire cluster by ensuring that nodes are up and running all the time and correct pods are running as mentioned in the specs file. 

etcd

It is a distributed key-value lightweight database. In Kubernetes, it is a central database for storing the current cluster state at any point in time and is also used to store the configuration details such as subnets, config maps, etc. It is written in the Go programming language.

2. Kubernetes-Worker Node Components

Kubernetes Worker node contains all the necessary services to manage the networking between the containers, communicate with the master node, and assign resources to the containers scheduled. The components of the Kubernetes Worker node are: 

Kubelet

It is a primary node agent which communicates with the master node and executes on each worker node inside the cluster. It gets the pod specifications through the API server and executes the container associated with the pods and ensures that the containers described in the pods are running and healthy. If kubelet notices any issues with the pods running on the worker nodes then it tries to restart the pod on the same node. If the issue is with the worker node itself then the Kubernetes master node detects the node failure and decides to recreate the pods on the other healthy node.

Kube-Proxy

It is the core networking component inside the Kubernetes cluster. It is responsible for maintaining the entire network configuration. Kube-Proxy maintains the distributed network across all the nodes, pods, and containers and exposes the services across the outside world. It acts as a network proxy and load balancer for a service on a single worker node and manages the network routing for TCP and UDP packets. It listens to the API server for each service endpoint creation and deletion so for each service endpoint it sets up the route so that you can reach it. 

Pods

A pod is a group of containers that are deployed together on the same host. With the help of pods, we can deploy multiple dependent containers together so it acts as a wrapper around these containers so we can interact and manage these containers primarily through pods. 

Docker

Docker is the containerization platform that is used to package your application and all its dependencies together in the form of containers to make sure that your application works seamlessly in any environment which can be development or test or production. Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. Docker is the world's leading software container platform. It was launched in 2013 by a company called Dot cloud. It is written in the Go language. It has been just six years since Docker was launched yet communities have already shifted to it from VMs. Docker is designed to benefit both developers and system administrators making it a part of many DevOps toolchains. Developers can write code without worrying about the testing and production environment. Sysadmins need not worry about infrastructure as Docker can easily scale up and scale down the number of systems. Docker comes into play at the deployment stage of the software development cycle.

Application of Kubernetes

The following are some application of Kubernetes:

1. Microservices Architecture

Kubernetes is well-suited for managing microservices architectures, which involve breaking down complex applications into smaller, modular components that can be independently deployed and managed.

2. Cloud-native Development

Kubernetes is a key component of cloud-native development, which involves building applications that are designed to run on cloud infrastructure and take advantage of the scalability, flexibility, and resilience of the cloud.

3. Continuous Integration and Delivery

Kubernetes integrates well with CI/CD pipelines, making it easier to automate the deployment process and roll out new versions of your application with minimal downtime.

4. Hybrid and Multi-Cloud Deployments

Kubernetes provides a consistent deployment and management experience across different cloud providers, on-premise data centers, and even developer laptops, making it easier to build and manage hybrid and multi-cloud deployments.

5. High-Performance Computing

Kubernetes can be used to manage high-performance computing workloads, such as scientific simulations, machine learning, and big data processing.

6. Edge Computing

Kubernetes is also being used in edge computing applications, where it can be used to manage containerized applications running on edge devices such as IoT devices or network appliances.

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Article Tags :

• GBlog
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• DevOps