What are Containers?

Future Techno India
5 min readAug 1, 2021


A container is a form of virtualization of an operating system. Any number of smaller microservices or software processes as well as larger applications can run inside a single container. There are both executables and binary code, libraries, and settings files inside a container. Although containers don’t include operating systems, servers or machines can be virtualized. With less overhead, they are lighter and more portable. Container clusters may be used to deploy multiple containers in larger application deployment. Kubernetes, for example, might manage such clusters.

Tools for containers

Here are some tools for containers which are like this.

TFI / Docker

1. Docker Enterprise:- As Docker orchestration tools make it easy to manage clusters from development through production, Docker swarm handles cluster management. Dispersed applications can be produced rapidly, scalable, and seamlessly. Kubernetes and containers are handled in a proven way.

Teams and large communities can build and share Docker images with it. Developers love the Docker platform. It is the platform that people want, love, and use most, based on a survey by Stack Overflow.

FTI / Kubernetes

2. Kubernetes :- Container orchestration and cluster management are some of the best uses of Kubernetes. Kubernetes is managed by several platforms including Google, AWS, Azure, Pivotal, and Docker. As containerized workloads scale, you have a great deal of flexibility.

Manifests for Docker Swarm and Compose CLI do not work with this software. In addition, learning and setting it up can be quite complex. It’s one of the most popular platforms for managing and deploying clusters despite its drawbacks.


3. Amazon Elastic Kubernetes service(EKS) :- When it comes to the deployment and configuration of clusters, Amazon ECS offers an excellent solution if you’re already familiar with AWS. Integrates with several other AWS services for a fast and convenient way to start, meet demand, and scale. Further, small teams with few resources are ideal for using this technology.

There is one con to this tool. It’s incompatible with nonstandard deployments. The configuration files are also ECS-specific, making troubleshooting more challenging.

FTI / Azure

4. Azure Container Service :- Kubernetes is managed by AKS and delivered by CI/CD with continuous integration and continuous delivery. Serverless Kubernetes can be deployed and managed easily, with more reliable security and governance.

Microservices are a key component of AKS. Systems complex enough for machine learning can be deployed and managed in a simplified manner. With its containers and configurations portable, they can easily be moved to the cloud.

FTI / Open Shift

5. RedHat Open Shift:- It allows you to build, deploy, scale, and manage containerized applications on-premise, privately on the cloud, or in a public cloud using an open-source, enterprise-grade Kubernetes platform.

FTI / Google Cloud Platform

6. Google Container Engine :- Container engines run within Google’s public cloud services such as Google Container Engine (GKE), which manages and orchestrates Docker containers and clusters. A container management system built on Kubernetes, a Google open-source project. The resources on this page provide information on using GKE containers and how to get started

And there are many container management tools which are available in the market.

Benefits of containers

Containerized applications can be built, tested, deployed, and redeployed on multiple locations, from a developer’s local laptop to an on-premises data center or even the cloud. There are many advantages to using containers, such as:

  • Less overhead

Unlike traditional virtual machine environments, containers do not contain an operating system image, so they require fewer resources.

  • Increased portability

Containerized applications can be deployed on different platforms and operating systems easily.

  • More consistent operation

Applications in containers will run as expected in any deployment, and this is understood by DevOps teams.

  • Greater efficiency

Containers make it easier to deploy, patch, and scale applications quickly.

  • Better application development

DevOps and agile efforts will be accelerated by using containers.

Container use cases

  • “Lift and shift” existing applications into modern cloud architectures

Existing applications are migrated into new environments using containers in some organizations. While this practice does provide some of the basic advantages of virtualized operating systems, it does not offer the full advantages of modular, container-based application architectures.

  • Refactor existing applications for containers

The benefits of container environments can only be fully realized with refactoring, even though it is more intensive than lift-and-shift migration.

  • Develop new container-native applications

Individual container building blocks make it easier to isolate, deploy, and scale distributed applications and microservices.

  • Provide DevOps support for continuous integration and deployment (CI/CD)

Building, testing, and deploying can be simplified by using container images.

  • Provide easier deployment of repetitive jobs and tasks

A container is designed to run one or more processes, such as batch jobs or ETL functions, that operate in the background.

Containers vs. virtual machines (VMs)

FTI / Containers vs VMs

Container technology is sometimes confused with virtual machines (VMs) or server virtualization. In spite of some basic similarities, containers differ greatly from virtual machines.

Hypervisors run virtual machines, which each contain their own guest operating system, along with their associated binaries, libraries, and application files. Multiple VMs running on the same physical server, each with its own guest operating system, consume a large number of system resources and overhead.

Unlike containers, which share identical systems and operating systems, individual containers are tiny and can only be several megabytes in size. The result is that a container might start in just seconds (instead of taking multiple gigabytes and minutes to start a typical VM).

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