Introduction

Kubernetes is an open source system for automating deployment, scaling and management of containerized applications. It was originally built by Google and runs in production inside Google Cloud Platform. Kubernetes started as a small project but has grown into one of the most popular tools to manage containerized environments across multiple platforms including AWS, Azure and GCP. This article provides a basic introduction to Kubernetes architecture, components and installation steps with some real use cases using kubectl commands in order to get you familiar with Kubernetes features

What is Kubernetes?

Kubernetes is a collection of tools that help you manage your containerized applications. Kubernetes is an open-source, container management system. It consists of several components, some of which are:

• API Server - The API server provides the API for interacting with Kubernetes and accessing its features.
• Controller Manager - The controller manager runs controllers that monitor your cluster's state and make changes based on those observations. One example of this would be a replication controller, which ensures that pods exist according to the desired count in your configuration file.
• Scheduler - The scheduler decides where to run each pod based on resource requirements (memory/CPU/disk space), labels applied to containers within a pod as well as other factors such as node health or available resources on nodes in the cluster.

Kubernetes Components

Kubernetes is a system for managing containerized applications in cloud native environments, such as on any of the major public clouds or on-premises. It's made up of several components that provide functionality around orchestration, service discovery, networking and more. Here's an overview of those components:

• Kubernetes Master - This runs on a single server (or several replicas) in your cluster. It manages all the other components and provides APIs for them to communicate with each other.
• Kubernetes Node - These are nodes that run pods and other containers to do work on behalf of end users or applications running inside pods (like Docker). In general there will be more than one node in your cluster because it needs at least three nodes with sufficient CPU memory disk space etc..  A node can be any machine with enough resources to run containers -- this could include virtual machines instances like AWS EC2 or GCE instances or bare metal servers/physical machines like AWS EC2 instances or OpenStack bare metal compute nodes -- but typically we'd recommend using at least two or three VMs if possible because then you can add multiple cores per machine which makes scaling easier down the road when traffic increases .  You'll also want enough RAM memory so that if one VM crashes then another can take over without causing problems .
• Kubernetes Pod - A pod defines how many containers should run together as well as their environment settings like container ports maps volumes etc.. Pods typically contain one container per process although some processes may use shared volumes instead."

Kubernetes Architecture

Kubernetes architecture is a collection of components that work together to provide a highly available, scalable, and self-healing environment for your applications.

The components of the Kubernetes architecture are:

• Controller manager
• API server
• Scheduler

Kubernetes Installation and Basic Concepts

• Installation
• Basic Concepts
• kubectl
• Kubernetes clusters
• Kubernetes nodes
• Kubernetes pods
• Kubernetes services
• Replication controllers and deployments: what are they?

How to Use Kubernetes?

The first step to using Kubernetes is to install it. You can do this on a laptop or desktop computer with the latest version of Ubuntu or Red Hat Enterprise Linux, CentOS, or Fedora. You'll also need 2GB of RAM and 20GB of disk space for the minimum install.

Once installed, run kubectl --kubeconfig="$HOME/.kube/config" get nodes to see if your cluster is running properly by listing all available nodes. If there are no errors—and you see output similar to 11:58:34 I0517 12:00:50.897480 1 controller-manager-master Ready ActiveLeaderMasterControllerAddress=10.32.0.26:6443 LeaderElect=true

Scaling and self-healing with Kubernetes

Kubernetes provides you with the ability to scale your application based on demand. For example, if there is a surge in traffic during the day, you can increase the number of instances of your service and then decrease them again when traffic drops off at night. Or if you have an event that causes people to visit your website in droves (maybe because it's featured on Product Hunt), you can add more resources so that performance does not suffer.

Another way Kubernetes helps with scaling applications is by providing self-healing capabilities for services running on top of it. Your application will automatically restart any pods whose containers have crashed or become unhealthy, ensuring that they are always available even if something goes wrong within them. This means that if one instance crashes due to an unexpected error or other problem—such as human error—it will be replaced by another one automatically without any intervention needed on your part!

It's all about the API

Kubernetes is a complex system, but it's all about the API. The API is the interface that you use to interact with Kubernetes. It has many benefits:

• The API is RESTful and versioned, which means it's easy to use and stable.
• The documentation for the API is thorough and well-written, making it easy to understand how everything works together.
• You can find examples of how to use the API in many programming languages on GitHub or by searching online (for example, here).

Clusters, nodes, pods and containers

Kubernetes is a system for automating the deployment, scaling, and management of containerized applications. Kubernetes clusters consist of one or more nodes that run containers to host your application’s components. Each node runs one or more containers and provides them with resources such as CPU, memory and networking.

Clusters have two distinct types of nodes: master nodes and worker nodes. Master nodes provide API services to the cluster’s users; worker nodes handle the work of running pods (the basic unit for scheduling workloads on Kubernetes). Pods are groups of closely related containers; each pod is scheduled onto one or more workers according to resource constraints defined by its configuration file. Containers within a pod share an IP address space, volumes, some network namespaces and other resources provided by their host machine (i.e., they are “containerized”).

The lifecycle management of all pods within a cluster is managed by kubelet daemons on each machine in the cluster; these daemons respond to requests from clients such as KUBERNETES_TASK_ID=$(date +%Y%m%d) . Pods can be thought of as ephemeral entities - they exist only within their hosts until they are deleted or moved elsewhere through replication controllers - whereas containers persist even after being stopped because they use bind mounts instead (i.e., referencing files outside themselves).

Benefits of using clusters

The benefits of using clusters include:

• Scalability. A Kubernetes cluster can be scaled easily to handle more workloads and users. The cluster is self-healing, which means that if a pod goes down, it will automatically restart (called auto-restarting). This eliminates the need for human intervention when something goes wrong with a pod. It also means that you don't have to worry about monitoring your pods 24/7 as they'll be automatically restarted if they crash or otherwise fail.
• Automation. Setting up a Kubernetes cluster is easy and automated, so there are no lengthy manual steps required when adding new applications onto it or updating existing ones—you just tell the system what needs changing, and the rest takes care of itself! Once everything's in place, scaling up your application becomes simple; add more instances whenever necessary by telling Kubernetes what services need to be scaled up or down (called autoscalability).
• Centralization/multi-tenancy . Because all containers run on one shared host operating system image instead of having separate OS instances running on each machine within an application stack like traditional VMs do (which can lead towards increased overhead), containerized deployments are much lighter overall than traditional VMs

If you need to run containerized applications in a production environment, you should consider using Kubernetes.

Since Kubernetes is an open source platform for automating deployment, scaling, and management of containerized applications, it's a great tool for managing containerized applications.

Kubernetes is a platform that allows you to deploy and manage containerized applications. It was originally created by Google in 2014 as an internal project to automate their own infrastructure. The project was made public in 2015 under the Apache 2 license, and it has rapidly gained popularity since then because of its simplicity and ease of use.

Takeaway:

Kubernetes is a powerful tool for managing containerized applications. It's the best choice for running containerized applications in production, and it’s the most popular container orchestration system in the world.

Kubernetes is built on Google’s internal experience running containers at scale. It was open-sourced by Google in 2014 and has been growing rapidly ever since. Kubernetes has become an important part of Cloud Native Computing Foundation (CNCF), which aims to drive cloud native technologies into production at scale.

Conclusion

Kubernetes is an open source container orchestration tool that runs on top of the same technology used by Google. It can be used to deploy, manage and scale applications in a production environment.

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