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Ansible

Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine
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What is Ansible?

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鈥檚 goals are foremost those of simplicity and maximum ease of use.
Ansible is a tool in the Server Configuration and Automation category of a tech stack.
Ansible is an open source tool with 40.8K GitHub stars and 17.7K GitHub forks. Here鈥檚 a link to Ansible's open source repository on GitHub

Who uses Ansible?

Companies
1315 companies reportedly use Ansible in their tech stacks, including DigitalOcean, 9GAG, and Typeform.

Developers
3752 developers on StackShare have stated that they use Ansible.

Ansible Integrations

Docker, Amazon EC2, New Relic, Kubernetes, and Microsoft Azure are some of the popular tools that integrate with Ansible. Here's a list of all 37 tools that integrate with Ansible.

Why developers like Ansible?

Here鈥檚 a list of reasons why companies and developers use Ansible
Ansible Reviews

Here are some stack decisions, common use cases and reviews by companies and developers who chose Ansible in their tech stack.

Tymoteusz Paul
Tymoteusz Paul
Devops guy at X20X Development LTD | 15 upvotes 366.8K 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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Pedro Arnal Puente
Pedro Arnal Puente
CTO at La Cupula Music SL | 7 upvotes 71.3K views
atLa Cupula Music SLLa Cupula Music SL
Debian
Debian
Amazon EC2
Amazon EC2
Amazon S3
Amazon S3
Amazon RDS for Aurora
Amazon RDS for Aurora
Redis
Redis
Amazon ElastiCache
Amazon ElastiCache
Terraform
Terraform
Packer
Packer
Ansible
Ansible

Our base infrastructure is composed of Debian based servers running in Amazon EC2 , asset storage with Amazon S3 , and Amazon RDS for Aurora and Redis under Amazon ElastiCache for data storage.

We are starting to work in automated provisioning and management with Terraform , Packer , and Ansible .

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Sebastian G臋bski
Sebastian G臋bski
CTO at Shedul/Fresha | 6 upvotes 59.8K views
atFresha EngineeringFresha Engineering
Docker
Docker
Docker Compose
Docker Compose
Kubernetes
Kubernetes
Terraform
Terraform
Ansible
Ansible
Amazon EC2
Amazon EC2
Amazon EKS
Amazon EKS
Amazon S3
Amazon S3
Amazon RDS
Amazon RDS

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.

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Marcel Kornegoor
Marcel Kornegoor
CTO at AT Computing | 5 upvotes 134.8K views
atAT ComputingAT Computing
Linux
Linux
Ubuntu
Ubuntu
CentOS
CentOS
Debian
Debian
Red Hat Enterprise Linux
Red Hat Enterprise Linux
Fedora
Fedora
Visual Studio Code
Visual Studio Code
Jenkins
Jenkins
VirtualBox
VirtualBox
GitHub
GitHub
Docker
Docker
Kubernetes
Kubernetes
Google Compute Engine
Google Compute Engine
Ansible
Ansible
Puppet Labs
Puppet Labs
Chef
Chef
Python
Python
#ATComputing

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.

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djhaskin987
djhaskin987
| 5 upvotes 17.7K views
atVerisk AnalyticsVerisk Analytics
Ansible
Ansible

We use Ansible. While Chef was considered for our configuration management and automation needs, the unique needs of our department pointed towards Ansible. To wit, that we needed to configure the machine and then hand it off to some other business unit. That business unit may in turn use an agent-based configuration management tool themselves to manage their machine, like Chef, Puppet or Salt. We couldn't use one of those, therefore, because if we did our agent would fight with that of our client's, so we chose Ansible.

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David Galoyan
David Galoyan
Docker
Docker
Concourse
Concourse
Ansible
Ansible
Vault
Vault
#DeploymentWorkflow

We use Docker for our #DeploymentWorkflow along with Concourse for build pipelines and Ansible for deployment together with Vault to manage secrets.

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Ansible's Features

  • Ansible's natural automation language allows sysadmins, developers, and IT managers to complete automation projects in hours, not weeks.
  • Ansible uses SSH by default instead of requiring agents everywhere. Avoid extra open ports, improve security, eliminate "managing the management", and reclaim CPU cycles.
  • Ansible automates app deployment, configuration management, workflow orchestration, and even cloud provisioning all from one system.

Ansible Alternatives & Comparisons

What are some alternatives to Ansible?
Puppet Labs
Puppet is an automated administrative engine for your Linux, Unix, and Windows systems and performs administrative tasks (such as adding users, installing packages, and updating server configurations) based on a centralized specification.
Chef
Chef enables you to manage and scale cloud infrastructure with no downtime or interruptions. Freely move applications and configurations from one cloud to another. Chef is integrated with all major cloud providers including Amazon EC2, VMWare, IBM Smartcloud, Rackspace, OpenStack, Windows Azure, HP Cloud, Google Compute Engine, Joyent Cloud and others.
Salt
Salt is a new approach to infrastructure management. Easy enough to get running in minutes, scalable enough to manage tens of thousands of servers, and fast enough to communicate with them in seconds. Salt delivers a dynamic communication bus for infrastructures that can be used for orchestration, remote execution, configuration management and much more.
Terraform
With Terraform, you describe your complete infrastructure as code, even as it spans multiple service providers. Your servers may come from AWS, your DNS may come from CloudFlare, and your database may come from Heroku. Terraform will build all these resources across all these providers in parallel.
Jenkins
In a nutshell Jenkins CI is the leading open-source continuous integration server. Built with Java, it provides over 300 plugins to support building and testing virtually any project.
See all alternatives

Ansible's Followers
3744 developers follow Ansible to keep up with related blogs and decisions.
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