Docker is one of the most popular tools for application containerization. it enables efficiency and reduces operational overheads so that any developer, in any dev environment, can build stable and reliable applications.
Let’s take a look, starting with application development.
One common challenge for DevOps teams is managing an application’s dependencies and technology stack across various cloud and development environments. As part of their routine tasks, they must keep the application operational and stable—regardless of the underlying platform that it runs on.
Development teams, on the other hand, focus on releasing new features and updates. Unfortunately, these often compromise the application’s stability by deploying codes that introduce environment-dependent bugs.
To avoid this inefficiency, organizations are increasingly adopting a containerized framework that allows designing a stable framework without adding:
Put simply, containerization is the process of packaging an application’s code—with dependencies, libraries, and configuration files that the application needs to launch and operate efficiently—into a standalone executable unit.
Initially, containers didn’t gain much prominence, mostly due to usability issues. However, since Docker entered the scene by addressing these challenges, containers have become practically mainstream.
Docker is a Linux-based, open-source containerization platform that developers use to build, run, and package applications for deployment using containers. Unlike virtual machines, Docker containers offer:
Fundamentally, Docker containers modularize an application’s functionality into multiple components that allow deploying, testing, or scaling them independently when needed.
Take, for instance, a Docker containerized database of an application. With such a framework, you can scale or maintain the database independently from other modules/components of the application without impacting the workloads of other critical systems.
Docker comprises the following different components within its core architecture:
Images are like blueprints containing instructions for creating a Docker container. Images define:
You can get images from DockerHub or create your own images by including specific instructions within a file called Dockerfile.
Containers are live instances of images on which an application or its independent modules are run.
In an object-oriented programming analogy, an image is a class and the container is an instance of that class. This allows operational efficiency by allowing to you to multiple containers from a single image.
A Docker registry is like a repository of images.
The default registry is the Docker Hub, a public registry that stores public and official images for different languages and platforms. By default, a request for an image from Docker is searched within the Docker Hub registry.
You can also own a private registry and configure it to be the default source of images for your custom requirements.
The Docker Engine is of the core components of a Docker architecture on which the application runs. You could also consider the Docker Engine as the application that’s installed on the system that manages containers, images, and builds.
A Docker Engine uses a client-server architecture and consists of the following sub-components:
There are numerous benefits that Docker enables across an application architecture. These are some of the benefits that Docker brings across multiple stages of the software development lifecycle (SDLC):
When it comes to the enterprise use of containers, you can rest easy knowing that Docker works with so many popular tools, including:
Although it is one of the most popular choices for application containerization, there are alternatives:
A few other lesser-known alternatives include OpenVz and RunC.
The idea of an agile, consistent, and independent environment that allowed faster builds and application interoperability turned out to be more challenging in virtual machines than initially thought.
Thanks to Docker, an organization can now fill the gaps left by virtual machines—without duplicating computing resources and while avoiding effort redundancy. In today’s cloud native environment, Dockers are synonymous with application efficiency and maintainability.
No wonder organizations continue adopting it!