The document provides a comprehensive overview of Docker, highlighting its advantages for faster application development, diverse environments, and improved deployment strategies. Docker is described as a container execution engine with a build system that enables efficient image distribution and management. The presentation also outlines how to get started with Docker, including resources for both beginners and advanced users.

1. Docker:
Everything you
should know
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2. Who am I?
Aaron Huslage (@huslage)
Sysadmin since 1993
Since April 2014: Solution Engineer @ Docker
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3. Outline
Why Docker?
What's Docker?
How to get started?
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4. Why Docker?
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5. Why Docker?
Faster application development cycle
Multiplication of environments
Scaling requirements
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6. Yesterday: slow cycles (months/years)
Specification
Implementation
Validation
Release
Maintenance
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7. Today: fast cycles (weeks/days)
Minimum Viable Product
Short iterations (sprints)
Continuous Deployment
A project is never "done" or "over"
Agile methods
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8. Yesterday: single environment
One language
One framework
One database
One server
(+ sometimes a dev environment)
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9. Today: many environments
Many languages
Polyglot platforms
Simultaneous use of SQL, NoSQL ...
The right tool for the right job
Many servers
(everybody has their local dev env;
there are many envs for testing, CI, QA, etc.)
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10. Yesterday: slow, vertical deployment
New versions once in a while
Installed to few servers (sometimes just one)
Scaling = scaling up (you're gonna need a bigger server)
Scaling must be planned far ahead
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11. Today: rapid, horizontal deployment
New versions all the time
(every week / day / hour)
Installed to many servers
Scaling = scaling out (MOAR servers!)
Need to be able to scale quickly
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12. What is Docker?
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13. What is Docker?
Container execution engine
Container build system
Container image distribution
Ginormous ecosystem
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14. Container execution engine
~Hypervisor for containers
Container =~ lightweight virtual machine
... What is a container???
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15. 15 / 35

16. Container
It looks and feels like a VM
Standard UNIX processes, isolated by kernel mechanisms:
namespaces
cgroups (control groups)
copy-on-write
Insanely fast boot times
Insanely low resource usage
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17. Build system
Dockerfile= recipe describing the build process
Easy to learn (similar to shell scripting)
Fast (caching system)
Reliable, reproducible
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18. Build system
Dockerfile= recipe describing the build process
Easy to learn (similar to shell scripting)
Fast (caching system)
Reliable, reproducible
Let's have our cake - and eat it too
(Compared to classic scripting, or configuration
management systems like Puppet, Chef, Salt, Ansible...)
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20. Image format
Problem: VM images are big
Solution 1: container images are smaller
doesn't need hardware support, kernel, drivers ...
separate handling of logs, metrics, backups ...
Solution 2: images broken down into layers
1 layer = 1 build step
example: base system, packages, code, config
only transfer updated layers
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21. Distribution protocol
Problem: it's both too simple and too complicated
"just do taror rsync...
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22. Distribution protocol
Problem: it's both too simple and too complicated
"just do taror rsync...
... with these 5 cryptic options, and it works"
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23. Distribution protocol
Problem: it's both too simple and too complicated
"just do taror rsync...
... with these 5 cryptic options, and it works"
(mostly)
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24. Distribution protocol
Problem: it's both too simple and too complicated
"just do taror rsync...
... with these 5 cryptic options, and it works"
(mostly)
Solution: Docker Registry
transfer layers via an open REST API
open source reference implementation
free service for public images
(à la GitHub)
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25. 25 / 35

26. Ecosystem: images
~100 official images
Linux distros
(Debian, Ubuntu, CentOS, Fedora, ...)
components
(MySQL, Redis, PostgreSQL, MongoDB, NGINX...)
languages
(Python, Ruby, Java, Go, Node...)
applications
(Wordpress...)
~150,000 contributed images
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27. Ecosystem: code
~100,000 GitHub repositories have a Dockerfile
~1000 contributors to Docker code
Thousands of projects integrating with Docker
Some official tools:
Machine (deploy Docker hosts)
Compose (manage multi-container applications)
Swarm (cluster multiple Docker hosts together)
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28. One example: Docker Compose
Assemble application from multiple containers
Define parameters of each container
how to build it
how to run it
(command, arguments, environment...)
network port mappings
linking between containers
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30. How to get
started?
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31. If you're in a hurry
OS X, Windows: Docker Toolbox + boot2docker
tiny VM image (less than 30 MB)
works on (most) physical and virtual machines
Linux: get.docker.com
shell script
usable with Cloud Init or |sh*
* Make sure you use https and nobody gets hurt!
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32. If you like reading
docs.docker.com
start with "get started" (duh!)
(it's written in good old "howto" style)
reference documentations
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33. If you like looking at / listening to
training.docker.com
Free, official training videos
Intro to Docker
(general concepts)
Docker Fundamentals
(first steps with Docker)
Docker Operations
(using Machine, Swarm, Compose)
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34. How to "Dockerize" my app?
1. Write a Dockerfilefor the main component
2. Write a docker-compose.ymlfor the app itself
3. Use Docker+Compose during development
4. Use Docker+Compose for testing/QA/acceptance...
5. (Optionally) setup CI/CD
6. Go to production with Docker+Compose
(static resource scheduling)
If you have 100s of apps with 100s of containers (each):
setup a self-service container platform for your developers
(using e.g. Swarm, Mesos, Kubernetes...)
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35. Questions?
@huslage
@docker
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