Ansible vs Docker Compose: What are the differences?
Developers describe Ansible as "Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine". Ansible is an IT automation tool. It can configure systems, deploy software, and orchestrate more advanced IT tasks such as continuous deployments or zero downtime rolling updates. Ansible’s goals are foremost those of simplicity and maximum ease of use. On the other hand, Docker Compose is detailed as "Define and run multi-container applications with Docker". With Compose, you define a multi-container application in a single file, then spin your application up in a single command which does everything that needs to be done to get it running.
Ansible and Docker Compose are primarily classified as "Server Configuration and Automation" and "Container" tools respectively.
"Agentless", "Great configuration " and "Simple" are the key factors why developers consider Ansible; whereas "Multi-container descriptor", "Fast development environment setup" and "Easy linking of containers" are the primary reasons why Docker Compose is favored.
Ansible and Docker Compose are both open source tools. It seems that Ansible with 37.8K GitHub stars and 15.8K forks on GitHub has more adoption than Docker Compose with 16.4K GitHub stars and 2.52K GitHub forks.
According to the StackShare community, Ansible has a broader approval, being mentioned in 955 company stacks & 578 developers stacks; compared to Docker Compose, which is listed in 787 company stacks and 608 developer stacks.
What is Ansible?
What is Docker Compose?
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By 2014, the DevOps team at Lyft decided to port their infrastructure code from Puppet to Salt. At that point, the Puppet code based included around "10,000 lines of spaghetti-code,” which was unfamiliar and challenging to the relatively new members of the DevOps team.
“The DevOps team felt that the Puppet infrastructure was too difficult to pick up quickly and would be impossible to introduce to [their] developers as the tool they’d use to manage their own services.”
To determine a path forward, the team assessed both Ansible and Salt, exploring four key areas: simplicity/ease of use, maturity, performance, and community.
They found that “Salt’s execution and state module support is more mature than Ansible’s, overall,” and that “Salt was faster than Ansible for state/playbook runs.” And while both have high levels of community support, Salt exceeded expectations in terms of friendless and responsiveness to opened issues.
Heroku was a decent choice to start a business, but at some point our platform was too big, too complex & too heterogenic, so Heroku started to be a constraint, not a benefit. First, we've started containerizing our apps with Docker to eliminate "works in my machine" syndrome & uniformize the environment setup. The first orchestration was composed with Docker Compose , but at some point it made sense to move it to Kubernetes. Fortunately, we've made a very good technical decision when starting our work with containers - all the container configuration & provisions HAD (since the beginning) to be done in code (Infrastructure as Code) - we've used Terraform & Ansible for that (correspondingly). This general trend of containerisation was accompanied by another, parallel & equally big project: migrating environments from Heroku to AWS: using Amazon EC2 , Amazon EKS, Amazon S3 & Amazon RDS.
Since #ATComputing is a vendor independent Linux and open source specialist, we do not have a favorite Linux distribution. We mainly use Ubuntu , Centos Debian , Red Hat Enterprise Linux and Fedora during our daily work. These are also the distributions we see most often used in our customers environments.
For our #ci/cd training, we use an open source pipeline that is build around Visual Studio Code , Jenkins , VirtualBox , GitHub , Docker Kubernetes and Google Compute Engine.
For #ServerConfigurationAndAutomation, we have embraced and contributed to Ansible mainly because it is not only flexible and powerful, but also straightforward and easier to learn than some other (open source) solutions. On the other hand: we are not affraid of Puppet Labs and Chef either.
Currently, our most popular #programming #Language course is Python . The reason Python is so popular has to do with it's versatility, but also with its low complexity. This helps sysadmins to write scripts or simple programs to make their job less repetitive and automating things more fun. Python is also widely used to communicate with (REST) API's and for data analysis.
Recently I have been working on an open source stack to help people consolidate their personal health data in a single database so that AI and analytics apps can be run against it to find personalized treatments. We chose to go with a #containerized approach leveraging Docker #containers with a local development environment setup with Docker Compose and nginx for container routing. For the production environment we chose to pull code from GitHub and build/push images using Jenkins and using Kubernetes to deploy to Amazon EC2.
We also implemented a dashboard app to handle user authentication/authorization, as well as a custom SSO server that runs on Heroku which allows experts to easily visit more than one instance without having to login repeatedly. The #Backend was implemented using my favorite #Stack which consists of FeathersJS on top of Node.js and ExpressJS with PostgreSQL as the main database. The #Frontend was implemented using React, Redux.js, Semantic UI React and the FeathersJS client. Though testing was light on this project, we chose to use AVA as well as ESLint to keep the codebase clean and consistent.
Ansible is the deployment tool for people who don't like deployment tools. It's close to scripting, doesn't pollute your servers with agents or centralized servers, and just makes immediate sense. The entire stack at Cloudcraft.co is orchestrated by Ansible. What does that mean? Beyond the obvious of installing packages and configuring services, Ansible coordinates all the machines into a working deployment: It adds API servers to the loadbancer pool, opens ports on the DB server for the backend servers to connect, gracefully upgrades services in a rolling fashion for zero-downtime deployments etc. And it's so easy to use, it's easier to use than doing things by hand, meaning it's a deployment tool you'll actually use every time!
Since our production deployment makes use of the Convox platform, we use this to describe the containers to be deployed via Convox to AWS ECS.
We also use this for our local dev environment (previously used vagrant with chef).
Aside from our Minecraft-infrastructure, we compose it with ... Docker Compose! (kinda obious, eh .. ?) This includes for example the web-services, aswell as the monitoring and mail-infrastructure.
We use Ansible to synchronize the few configuration-options we've taken on our CoreOS-Machines. This makes deployment even easier and the fact that it's Agentless made the decision even easier.
Ansible is used in both the development and production deployment process. A playbook couple with a Vagrantfile, easy deploys a local virtual machine that will mirror the setup in production.
I use Ansible to manage the configuration between all of the different pieces of equipment, and because it's agentless I can even manage things like networking devices all from one repo.
Docker Compose is just another part of my "infrastructure as code" initiative and allows me to build isolated pieces of systems with their own volumes and networks.
- Configuration management:
- deploy/install all web/app environments
- simple with Galaxy and playbooks.
- No need any pre-installed agent on remote servers.
Our application will consist of several containers each communicating with each other. Using docker-compose, we can orchestrate several containers at once.