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Docker vs OpenShift: What are the differences?

Developers describe Docker as "Enterprise Container Platform for High-Velocity Innovation". The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere. On the other hand, OpenShift is detailed as "Red Hat's free Platform as a Service (PaaS) for hosting Java, PHP, Ruby, Python, Node.js, and Perl apps". OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.

Docker belongs to "Virtual Machine Platforms & Containers" category of the tech stack, while OpenShift can be primarily classified under "Platform as a Service".

Some of the features offered by Docker are:

  • Integrated developer tools
  • open, portable images
  • shareable, reusable apps

On the other hand, OpenShift provides the following key features:

  • Built-in support for Node.js, Ruby, Python, PHP, Perl, and Java (the standard in today's Enterprise)
  • OpenShift is extensible with a customizable cartridge functionality that allows developers to add any other language they wish. We've seen everything from Clojure to Cobol running on OpenShift.
  • OpenShift supports frameworks ranging from Spring, to Rails, to Play

"Rapid integration and build up" is the top reason why over 816 developers like Docker, while over 95 developers mention "Good free plan" as the leading cause for choosing OpenShift.

Docker and OpenShift are both open source tools. Docker with 54K GitHub stars and 15.6K forks on GitHub appears to be more popular than OpenShift with 915 GitHub stars and 563 GitHub forks.

Spotify, Pinterest, and Twitter are some of the popular companies that use Docker, whereas OpenShift is used by Accenture, Vungle, and Hazeorid. Docker has a broader approval, being mentioned in 3527 company stacks & 3449 developers stacks; compared to OpenShift, which is listed in 50 company stacks and 52 developer stacks.

What is Docker?

The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere

What is OpenShift?

OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.
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What are some alternatives to Docker and OpenShift?
LXC
LXC is a userspace interface for the Linux kernel containment features. Through a powerful API and simple tools, it lets Linux users easily create and manage system or application containers.
rkt
Rocket is a cli for running App Containers. The goal of rocket is to be composable, secure, and fast.
Kubernetes
Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.
Cloud Foundry
Cloud Foundry is an open platform as a service (PaaS) that provides a choice of clouds, developer frameworks, and application services. Cloud Foundry makes it faster and easier to build, test, deploy, and scale applications.
Vagrant
Vagrant provides the framework and configuration format to create and manage complete portable development environments. These development environments can live on your computer or in the cloud, and are portable between Windows, Mac OS X, and Linux.
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Decisions about Docker and OpenShift
Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD · | 15 upvotes · 348.6K views
Vagrant
Vagrant
VirtualBox
VirtualBox
Ansible
Ansible
Elasticsearch
Elasticsearch
Kibana
Kibana
Logstash
Logstash
TeamCity
TeamCity
Jenkins
Jenkins
Slack
Slack
Apache Maven
Apache Maven
Vault
Vault
Git
Git
Docker
Docker
CircleCI
CircleCI
LXC
LXC
Amazon EC2
Amazon EC2

Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

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Node.js
Node.js
Docker
Docker
Docker Swarm
Docker Swarm
GitLab CI
GitLab CI
Google Compute Engine
Google Compute Engine
React
React
Webpack
Webpack
#DeploymentWorkflow

I have got a small radio service running on Node.js. Front end is written with React and packed with Webpack . I use Docker for my #DeploymentWorkflow along with Docker Swarm and GitLab CI on a single Google Compute Engine instance, which is also a runner itself. Pretty unscalable decision but it works great for tiny projects. The project is available on https://ch1ller.com

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Heroku
Heroku
OpenShift
OpenShift
Docker
Docker

Heroku vs OpenShift. I've never decided which one is better. Heroku is easier to configure. Openshift provide a better machine for free. Heroku has many addons for free. I've chosen Heroku because of easy initial set-up. I had deployment based on git push. I also tried direct deployment of jar file. Currently Heroku runs my Docker image. Heroku has very good documentation like for beginners. So if you want to start with something, let's follow Heroku. On the other hand OpenShift seems like a PRO tool supported by @RedHat.

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