GithubHelp home page GithubHelp logo

leogallego / automation-good-practices Goto Github PK

View Code? Open in Web Editor NEW

This project forked from redhat-cop/automation-good-practices

0.0 1.0 0.0 192 KB

Recommended practices for all elements of automation using Ansible, starting with collections and roles, continuing with playbooks, inventories and plug-ins... These good practices are planned to be used by all Red Hat teams interested but can of course be used by others.

Makefile 100.00%

automation-good-practices's Introduction

Good Practices for Ansible - GPA

Introduction

Ansible is simple, flexible, and powerful. Like any powerful tool, there are many ways to use it, some better than others.

This document aims to gather good practices from the field of Ansible practitioners at Red Hat, consultants, developers, and others. And thus it strives to give any Red Hat employee, partner or customer (or any Ansible user) a guideline from which to start in good conditions their automation journey.

Those are opinionated guidelines based on the experience of many people. They are not meant to be followed blindly if they don’t fit the reader’s specific use case, organization or needs; there is a reason why they are called good and not best practices.

The reader of this document is expected to have working practice of Ansible. If they are new to Ansible, the Getting started section of the official Ansible documentation is a better place to start.

This document is split in six main sections. Each section covers a different aspect of automation using Ansible (and in a broader term the whole Red Hat Ansible Automation Platform, including Ansible Tower):

  1. structures: we need to know what to use for which purpose before we can delve into the details, this section explains this.

  2. roles: as we recommend to use roles to host the most actual Ansible code, this is also where we’ll cover the more low level aspects of code (tasks, variables, etc…​).

  3. collections

  4. playbooks

  5. inventories

  6. plugins

Each section is then made of guidelines, one sentence hopefully easy to remember, followed by description, rationale and examples. The HTML version of this document makes the content collapsable so that all guidelines can be seen at once in a very overseeable way, for the reader to uncollapse the content of guidelines they is interested in.

A rationale is expected for each good practice, with a reference if applicable. It is really helpful to know not only how to do certain things, but why to do them in this way. It will also help with further revisions of the standards as some items may become obsolete or no longer applicable. If the reason is not included, there is a risk of keeping items that are no longer applicable, or alternatively blindly removing items that should be kept. It also has great educational value for understanding how things actually work (or how they don’t).

automation-good-practices's People

Contributors

bontreger avatar djdanielsson avatar ericzolf avatar fale avatar jeichler avatar jillr avatar jscar-hawk avatar kubealex avatar mophahr avatar pcfe avatar richm avatar spetrosi avatar vvaldez avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.