8 Good Reasons to Learn Docker
8 Good Reasons to Learn Docker There are probably a lot of technologies you must learn in order to master the modern development and DevOps ecosystem but Docker (and of course orchestration and the containers’ ecosystem) is one of the important skills to have nowadays. Optimize Hardware Usage Distribution & Collaboration Multi Tenancy & High Availability CI/CD — Build Once, Run Everywhere Isolation & The Dependency Hell Using The Ecosystem Development in a cross-platform environment is easier Deployment of Applications is easier
Optimize Hardware Usage
Like virtual machines, containerization changed the way we optimize our hardware usage. With virtual machines you can have some limits. Let’s imagine a scenario where you should host two applications using the same language but not the same version. You may find a solution or probably a hack to do it in a single VM, but you can finish by creating a new VM in order to host the second application. VMs can have some limits, but using Docker you can easily deploy multiple applications, using different versions of the same language without creating a new VM.
Distribution & Collaboration If you would like to share images and containers, Docker allows this “social” feature so that anyone can contribute to a public (or private) image. Individuals and communities can collaborate and share images. Users can also vote for images. In Docker Hub, you can find trusted (official) and community images. Some images have a continuous build and security scan feature to keep them up-to-date.
Multi Tenancy & High Availability
Using the right tools from the ecosystem, it is easier to run many instances of the same application in the same server with Docker than the “main stream” way. Using a proxy, a service discovery and a scheduling tool, you can start a second server (or more) and loadbalance your traffic between the cluster nodes where your containers are “living”.
CI/CD — Build Once, Run Everywhere
Docker is used in production systems but it is considered as a tool to run the same application in developer’s laptop/server. Docker may move from development to QA to production without being changed. If you would like to be as close as possible to production, then Docker is a good solution. Since it solves the problem of “it works on my machine”, it is important to highlight this use case. Most problems in software development and operations are due to the differences between development and production environments.
Isolation & The Dependency Hell
Dockerizing an application is also isolating it into a separate environment. Same thing as the first point, imagine you have to run two APIs with two different languages or running them with the same language but with different versions. You may need two incompatible versions of the same language, each *API* is running one of them, for example Python 2 and Python 3. If the two apps are dockerized, you don’t need to install nothing on your host machine, just Docker, every version will run in an isolated environment.
Using The Ecosystem ď‚—
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You can use Docker with multiple external tools like configuration management tools, orchestration tools, file storage technologies, filesystem types, logging softwares, monitoring tools, self-healing tools ..etc On the other hand, even with all the benefits of Docker, it is not always the best solution to use, there are always exceptions.
Development in a cross-platform environment is easier
If you are like me, you love your Mac running OSX. The problem is, most of the code that I deploy runs on Linux based machines. I develop code to run on the cloud or I develop code to run on embedded systems like a Raspberry PI. However, I can’t give up OSX as my daily use operating system and development environment. Linux just doesn’t cut it for me as a general use operating system. In my opinion, it’s ugly and just doesn’t have all the applications I need to get through my day.
Deployment of Applications is easier ď‚—
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If you have ever tried to deploy a software application with a large number of software dependencies, you know it can be a very painful process. On a Linux based system, it often involves a lot of apt-get installs for different software projects just to be able to run your code. With Docker, all of those dependencies are built into the image itself. This means that when you want to deploy your application built into a Docker image, all you need installed on the system itself is Docker plus the image.
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