AUTOMATED DEPLOYMENT

with open-source tools

2017.03.12Sardor Muminov

Who I am

● Backend software engineer

● IT systems engineer

● Open source enthusiast

● Python, Javascript and Rust (learning)

muminoff

muminoff

Software deployment is all of the activities that make a software system available for use.

― Wikipedia

Manual deployments

● not consistent across environments

● slow, neither repeatable nor reliable

● require extensive documentation (often outdated)

● hinder collaboration (usually conducted by a few experts)

Why automated deployment?

● less error-prone and much more repeatable

● anyone in the team can deploy software

● engineers spend their time developing software

● deploying to somewhere new is not a headache

● you can release more frequently

Traditional workflow (FTP, SFTP, SCP)

FTP, SSH HTTPCodebase

Local

WindowsmacOSLinux

Server

Directory

Web-server

WindowsmacOSLinux

Request

Browser

Mobile

API client

Traditional workflow (Git, SVN, Mercurial)

git push Codebase

Local Server

Directory

Web-server

Request

Browser

Mobile

API client

HTTP

VCS

Repository

versions

git pull

WindowsmacOSLinux

GithubGitlab

Self hosted

WindowsmacOSLinux

Automated workflow

VCS

commitcheckout

Build Automation

poll for changes

www

Productionenvironment

Unit tests

test

Sandboxenvironment

deploy

deployDeveloper

Open source automation tools

● Chef

● Puppet

● Salt

● Ansible

● Fabric

Chef

● Written in Ruby (client) / Erlang (server)

● Not-easy to learn and deploy

● Highly mature and works at massive scale

● Used by big companies

○ (e.g. Facebook, Microsoft, Bloomberg)

Puppet

● Written in Ruby

● Requires master (track infrastructure)

● Depends on agent

● Used by big companies

○ (e.g. RedHat, Microsoft)

Salt

● Written in Python

● Requires agent (minions)

● Depends on PyDSL and Python

● Used by big companies

○ (e.g. Pivotal, CloudFlare)

Ansible

● Written in Python

● Agent-less

● Supports any programming language

● Excellent security using SSH / SSH2

● Being used by companies:

○ NASA, Twitter, Attlasian

○ Evernote, RedHat, Cisco

○ EASports, GoPro, etc.

Fabric

● Written in Python

● Easy to learn, extend

● Programmatically integration

● Can be integrated with 3rd party tools

Summary

Benefits Manual deployment Automated deployment

Less time consumption ⚝ ◾

Less error prone ⚝ ◾

Repeatable ⚝ ◾

Collaboration ⚝ ◾

Continuous Delivery Vs. Continuous Deployment

Continuous Delivery Vs. Continuous Deployment

Example workflow (Ansible)10.1.2.40

Ubuntu/xenial

10.1.2.41

CentOS/7

10.1.2.43

Debian/jessie

localhost

Docker

192.168.2.3

VMWare

Developer

Host inventory10.1.2.4010.1.2.4110.1.2.43

playbook

Example workflow (Ansible)

Developer10.1.2.60

Server

deploy

$ git pull origin master

…

$ npm install

…

$ bower install

…

$ gulp run build

…

$ supervisorctl restart all

…

$ service nginx reload

…

Demo

References

1. https://en.wikipedia.org/wiki/Software_deployment

2. https://en.wikipedia.org/wiki/Software_release_life_cycle

3. https://en.wikipedia.org/wiki/Release_management

4. https://en.wikipedia.org/wiki/DevOps

5. https://en.wikipedia.org/wiki/Ansible_(software)

6. https://www.ansible.com

7. http://www.fabfile.org/

Thank you