Containerization technology and its vague terms are making a lot of fuss these days. If you are a developer you have no doubt heard the phrases Docker, Container, Kubernetes, and so forth. What are those technologies? Where do they come from? And, most importantly, what are they used for? In this article, we will learn about not only these terms but more.
Container technology is a kind of virtualizing platform used mostly in cloud computing and designed as a practical alternative solution to run applications in different operating system platforms without the need for Virtual Machine requirements. It’s used mainly for facilitating various stages of software development, especially during the testing phase.
What is Docker Container?
Container platform technology is packaged items of software applications in virtual containers. Each software container is a standardized executable component. It combines the core OS needed to run it with every dependency and library as an “image”. They are portable and reusable in any operating system. They have separated execution environments from each other.
Launched in 2013, Docker has recently become the de facto industry standard open-source software for containers. It is increasingly getting more popular alongside the integration of companies using cloud-native and hybrid solutions. It is also characterized as making containerizing easier and simpler. With a few commands, developers can create a container environment all in one place.
Usually, the Docker container images become containers when run by Docker Engine. It is available for every Linux and Windows-based OS and application, enabling containerization to run natively regardless of the environment or infrastructure. This seeks to put an end to the “dependency” tragedy and eliminate the curse of “it doesn’t work on my laptop!.”
Benefits of Docker Containers
The main goals and benefits of Docker containers are to allow developers to improve the following processes:
- Shortening the delay of writing code until running it.
- Flexibility in deploying, cloning, and moving the workload.
- Unifying a one-way streamline for shipping, running, and testing.
- Reducing the need for server resources and costs with better performance.
- Simplifying infrastructure maintenance, update, and support.
- Increasing security strength by containing isolation capabilities.
Common Docker Usage
We can not imagine that Docker containers as a giant project have been developed, for instance, just to enable a handful of Linux users around the world to run Windows applications in Linux OS! That is not really the case or function. There are some other solutions for that use case. Docker mainly exists to serve software developing projects and increase the consistent delivery of applications.
We can not define every detail of Docker’s common usage. Instead, we will look at the most major use cases which are mainly related to better delivery of (CI/CD) and enhancement of workflows. These uses include but are not limited to:
- Simplifying and standardizing the software development lifecycle (SDLC) by creating a worldwide unified environment to integrate the processes of providing your applications and services.
- Enabling developers to easily share local written code with colleagues and testers for peer review and executing automated and manual tests smoothly.
- Facilitating fixing bugs and composability thanks to easy movements between development and test environments, in addition to the final customer.
- Creating dynamic and high portability workloads, from local laptops, on-prime servers, virtual machines, on the cloud, on local data centers, and hybrid platforms.
- Scaling up and down workloads and applications in real-time as per the needs of the business and to run more than one workload in high-density environments.
- Facilitating the orchestration of the deployment of many items. The Kubernetes orchestration software can organize them in clusters.
How Does Docker Architecture Work?
Docker is a manifestation of the new generation of virtualization. It uses a client-server architecture to call with the Docker daemon which can run on the same OS or be connected remotely. The heavy workload of building and running containers falls on the shoulders of the Docker engine. And the user interacting is with the Docker client. They communicate through a REST API either on UNIX sockets or a network interface.
In order to list all the Docker Objects, let’s make the following list:
- Docker Client CLI: An interface for users to interact with Docker.
- Docker Daemon and Engine: A process for building and running the containers.
- Docker Registry: To store the Docker images in public or private Docker Hub.
- Docker Volumes: The persisting data of Docker containers.
- Docker Image: A read-only object has the instructions to create a Docker container.
- Docker File: A simple text file contains the command-line of building Docker images.
- Docker Container: The final runnable Docker image.
The containerizing process by Docker is very simple: creating DockerFile => pulling Docker Image => running Docker Container. Just by using the pull command, you will pull a specific image from the Docker hub. Then by the run command, you will run it. Images are mostly based on other images such as Ubuntu or Node.js. Also, you can create your images from scratch by Dockerfile. The container usually is defined by its image and other configurations in its Dockerfile.
Containers vs Virtual Machines
Containers and Virtual Machines are similar, we can think of Virtual Machines as full virtualization and Containers as limited virtualization. However, we can’t assume containers are better for all cases; each of them has its best situations and case usage.
Far away from complex details, from a big picture perspective, we can compare Dockers and Virtual Machines (VMs) briefly as follows:
- VMs are an abstraction emulating the physical hardware that makes the physical server branch out into many internal servers. The Hypervisor software is managing the whole process of installing full copies of each operating system, which makes it need more resources.
- Containers, on the other hand, dispense abstraction of virtual hardware and full operating systems, satisfied with the OS kernel only. It just abstracts an application package layer. This provides an extra layer of burden to allow for more containers to run on the same server. You share OS kernel with some other containers in isolated environments which also can make some networks between containers as desired.
