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Containers are a way to build, package, and deploy software. These are similar to virtual machines (VMs), but they are not the same. One of the main differences is that the container is separated or abstracted from the underlying operating system and the infrastructure on which the container runs. Simply put, a container contains both your application’s code and everything you need to run it correctly.


  • Portability: One of the biggest benefits of containers is that they can be run in any environment. This allows, for example, containerized workloads across different cloud platforms, regardless of the underlying operating system or other factors, without having to rewrite a large amount of code to properly run the containerized workload. Can be easily moved. It also increases developer productivity by allowing you to write code in a consistent way without worrying about execution when deployed to a variety of environments, from local computers to local servers to public clouds.
  • Application Development: Containers can accelerate application development and deployment, including changes and updates over time. This is especially true for containerized microservices. This is an approach to software architecture that divides a large solution into smaller pieces. These individual components (or microservices) can be individually deployed, updated, or deprecated without updating and redeploying the entire application. ]
  • Resource Usage and Optimization: Containers are lightweight and have a short lifespan, so they use less resources. For example, you can run many containers on one computer.


Container orchestration automates much of the operational overhead required to run containerized workloads and services. This includes provisioning, provisioning, scaling (up and down), networking, load balancing, and much more that software teams need to manage the life cycle of their containers.


Due to the naturally light weight and short life of containers, operating in a production environment can quickly become costly. Especially when combined with microservices that typically run in their own containers, containerized applications can lead to the operation of hundreds or thousands of containers, especially when building and operating large systems. there is. This can significantly complicate manual management.

Container orchestration provides a declarative way to automate most of the work, allowing development and operations (or DevOps) to manage this operational complexity. This is ideal for DevOps teams and cultures that tend to work much faster and more agile than traditional software teams.


Container orchestration is the key to working with containers and helps businesses get the most out of them. In addition, the containerized environment has the following unique advantages:

Simplified operation: This is the main advantage of container orchestration and the main reason for introducing it. Containers can become very complex and quickly get out of control without container orchestration to manage them.

Resilience: The container orchestration tool can automatically restart or scale the container or cluster to improve resilience.

Additional Security: Container Orchestration’s automated approach helps keep containerized applications safe by reducing or eliminating the risk of human error.


Docker, which is also an open source platform, provides a fully integrated container orchestration tool called Docker Swarm. You can package and run your application as a container, search for container images from other hosts, and deploy containers. Although simpler and less extensible than Kubernetes, Docker provides the ability to integrate with Kubernetes for organizations that want access to the richer features of Kubernetes.

Below are the main architectural components of Docker Swarm :


Swarm is a cluster of Docker hosts that run in Swarm mode and manage membership and delegation while the Swarm service is running.


A node is a Docker engine instance contained in a herd. This is either a manager node or a worker node. Manager nodes distribute work units called tasks to worker nodes. It is also responsible for all orchestration and container management tasks such as cluster state maintenance and service scheduling. The worker node receives and executes the task.


The service is a definition of the tasks that must be performed on a node. Defines the container image to use and the commands to run in the running container. The task has a container next to the commands that are executed inside the container. Once a task is assigned to a node, you cannot move it to another node.


Kubernetes is an open source container orchestration platform that is considered the industry standard. Google-supported solutions allow developers and operators to deliver cloud services as either Platform-as-a-Service (PaaS) or Infrastructure-as-a-Service (IaaS). This is a powerful declarative solution that allows developers to declare the desired state of their container environment via YAML files. Kubernetes then creates and maintains the desired state.

Below are the key architectural components of Kubernetes:


Node is a Kubernetes worker computer. It can be virtual or physical, depending on the cluster. The node receives and executes the tasks assigned by the master node. It also includes the services needed to run the pod. Each node consists of a kubelet, a container runtime, and a kube-proxy.

Master node

This node controls all worker nodes and is the starting point for all assigned tasks. This is done through the orchestration layer, which is a control area that provides APIs and interfaces for defining, provisioning, and managing the life cycle of containers.


A cluster represents a master node and some worker nodes. The cluster combines these machines into one unit and deploys the containerized application. The workload is then distributed across the various nodes, where adjustments are made when nodes are added or removed.


The Pod is the smallest deployable computing device that Kubernetes can create and manage. Each pod is a collection of containers that are packed together and deployed on a node.


Deployments provide declarative updates for pods and replica sets. This allows the user to decide how many replicas of the pod should be running at the same time.

Written by 

Mayuri Dhote is a Software Consultant at Knoldus Software. She has completed her MCA from VIT University. She has very dedicated towards her work. She has always ready to learn new things. Her practice area is Devops. When not working, you will find her writing poems and poetry.