Google defines containers as follows: “Containers offer a logical packaging mechanism in which applications can be abstracted from the environment in which they actually run.”

To put it simply, containers take their structural makeup by removing the inefficiencies in the traditional architecture. A container is an enclosed unit of a cloud environment, comprising all that is required for code to run in isolation. The isolation boundary encapsulates the application and its dependencies, while the OS is abstracted on top of hardware virtualization, making it highly efficient and scalable.

The container engine allows an application to run as if it had a completely dedicated, resource-independent server. Containers benefit from management and orchestration tools but end up running several times faster than your average virtual machines. This means teams can deploy and destroy applications more frequently as updates roll in.

It is a modern virtualization method that accesses a single OS kernel to power multiple distributed applications that are each developed and run in their own container. Because containers don’t require their own operating systems to execute applications, they consume fewer resources in a server, virtual or cloud environment. Containers hold all of the pieces needed to run a program. This runtime environment could include files, libraries, and environment variables that allow a program to be executable.

In a traditional cloud infrastructure, applications and related files reside within a single virtual machine with isolation boundaries at the server level. This is critical because containerization reduces the likelihood of integration issues, as applications can run on separate operating systems—connected to a host OS—within a single server.

In the event that an application suddenly malfunctions, there is no snowball effect throughout the rest of the server—the damage is contained. On top of that, cloud infrastructure managers do not have to install an entire OS within each separate container or integrate containers with server hardware. These computational pockets require minimal software and libraries to run.

Containers have seen rapid growth and are on the verge of mainstream adoption as they offer invaluable benefits.

1. Environment inconsistencies don’t exist

Traditionally IT ops and developers spend their valuable time diagnosing, debugging, and troubleshooting the inconsistencies in various environments, which increases the time required to ship software. With containers, applications are separated from the OS that they run in and from other applications, which gives peace of mind to developers. No matter where the application is deployed, they can expect guaranteed consistency.

2. Lightweight, fast, and agile

Containers can rapidly deploy, patch, and scale applications. The overall footprint for a container in comparison to a VM is very small as containers share resources from the host OS across containers. Unlike VM technology, where each VM needs to have its own OS and libraries, containers take up only a few megabytes. This lightness makes containers extremely fast, as they don’t need a typical OS boot and can start in milliseconds. Creating and destroying containers can be done in seconds, thereby accelerating development operations and time to market. It’s highly beneficial for customer experience since feature insertion or bug fixes can be implemented at great speed.

3. Run your applications anywhere

Platform independence is a key advantage of adopting containers. The very nature of containers allows you to run applications in any environment, be it physical servers, virtual servers, or private or public clouds. And you can seamlessly move your applications from production to testing to staging environments without any hassle.

4. Improve your team’s overall productivity

Overall, as containers take away much of the cumbersomeness when it comes to software development, IT teams can focus on their key activities and developers can focus on app logic, while not having to worry about configurations and versions. This translates to less time spent on testing and debugging and more time spent innovating.

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