Introduction to Docker and Containers

Introduction
to
Docker
and
Containers
@docker
@charme_g

Outline
● Whom is this for?
● What's the problem?
● What's a Container?
● Docker 101
● Docker images
● Docker future

Ops
● any distro¹
● any cloud²
● any machine (physical, virtual...)
● recent kernels³
¹ as long as it's Ubuntu or Debian ☺ others coming soon
² as long as they don't ship with their custom crappy kernel
³ at least 3.8; support for RHEL 2.6.32 on the way

Devs
● all languages
● all databases
● all O/S
● targetting Linux systems
Docker will eventually be able to target FreeBSD, Solaris, and maybe OS X.

CFO, CIO, CTO, ...
● LESS overhead!
● MORE consolidation!
● MORE agility!
● LESS costs!

The Matrix From Hell
django
web frontend ? ? ? ? ? ?
node.js
async API ? ? ? ? ? ?
background
workers ? ? ? ? ? ?
SQL database
? ? ? ? ? ?
distributed
DB, big data ? ? ? ? ? ?
message
queue ? ? ? ? ? ?
my laptop your laptop QA staging prod on
cloud VM
prod on bare
metal

Another Matrix from Hell
? ? ? ? ? ? ?
? ? ? ? ? ? ?
? ? ? ? ? ? ?
? ? ? ? ? ? ?
? ? ? ? ? ? ?
? ? ? ? ? ? ?

Solution:
the intermodal shipping container

Solution to the deployment problem:
the Linux container

Linux containers...
Units of software delivery (ship it!)
● run everywhere
– regardless of kernel version
– regardless of host distro
– (but container and host architecture must match*)
● run anything
– if it can run on the host, it can run in the container
– i.e., if it can run on a Linux kernel, it can run
*Unless you emulate CPU with qemu and binfmt

High level approach:
it's a lightweight VM
● own process space
● own network interface
● can run stuff as root
● can have its own /sbin/init
(different from the host)
« Machine Container »

Low level approach:
it's chroot on steroids
● can also not have its own /sbin/init
● container = isolated process(es)
● share kernel with host
● no device emulation (neither HVM nor PV)
« Application Container »

Separation of concerns:
Dave the Developer
● inside my container:
– my code
– my libraries
– my package manager
– my app
– my data

Separation of concerns:
Oscar the Ops guy
● outside the container:
– logging
– remote access
– network configuration
– monitoring

How does it work?
Isolation with namespaces
● pid
● mnt
● net
● uts
● ipc
● user

How does it work?
Isolation with cgroups
● memory
● cpu
● blkio
● devices

If you're serious about security,
you also need…
● capabilities
– okay: cap_ipc_lock, cap_lease, cap_mknod,
cap_net_admin, cap_net_bind_service,
cap_net_raw
– troublesome: cap_sys_admin (mount!)
● think twice before granting root
● grsec is nice
● seccomp (very specific use cases); seccomp-
bpf
● beware of full-scale kernel exploits!

How does it work?
Copy-on-write storage
● unioning filesystems
(AUFS, overlayfs)
● snapshotting filesystems
(BTRFS, ZFS)
● copy-on-write block devices
(thin snapshots with LVM or device-mapper)
This is now being integrated with low-level LXC tools as well!

Compute efficiency:
almost no overhead
● processes are isolated,
but run straight on the host
● CPU performance
= native performance
● memory performance
= a few % shaved off for (optional) accounting
● network performance
= small overhead; can be reduced to zero

Storage efficiency:
many options!
Union
Filesystems
Snapshotting
Filesystems
Copy-on-write
block devices
Provisioning Superfast
Supercheap
Fast
Cheap
Fast
Cheap
Changing
small files
Superfast
Supercheap
Fast
Cheap
Fast
Costly
Changing
large files
Slow (first time)
Inefficient (copy-up!)
Fast
Cheap
Fast
Cheap
Diffing Superfast Superfast (ZFS)
Kinda meh (BTRFS)
Slow
Memory usage Efficient Efficient Inefficient
(at high densities)
Drawbacks Random quirks
AUFS not mainline
!AUFS more quirks
ZFS not mainline
BTRFS not as nice
Higher disk usage
Great performance
(except diffing)
Bottom line Ideal for PAAS and
high density things
This might be the
Future
Dodge Ram 3500

Introduction to Docker and Containers

Docker-what?
● Open Source engine to commoditize LXC
● using copy-on-write for quick provisioning
STOP!
HAMMER DEMO TIME.

Yes, but...
● « I don't need Docker;
I can do all that stuff with LXC tools, rsync,
some scripts! »
● correct on all accounts;
but it's also true for apt, dpkg, rpm, yum, etc.
● the whole point is to commoditize,
i.e. make it ridiculously easy to use

What this really means…
● instead of writing « very small shell scripts » to
manage containers, write them to do the rest:
– continuous deployment/integration/testing
– orchestration
● = use Docker as a building block
● re-use other people images (yay ecosystem!)

Docker-what?
The Big Picture
● Open Source engine to commoditize LXC
● using copy-on-write for quick provisioning
● allowing to create and share images
● standard format for containers
(stack of layers; 1 layer = tarball+metadata)
● standard, reproducible way to easily build
trusted images (Dockerfile, Stackbrew...)

Docker-what?
Under The Hood
● rewrite of dotCloud internal container engine
– original version: Python, tied to dotCloud's internal
stuff
– released version: Go, legacy-free
● the Docker daemon runs in the background
– manages containers, images, and builds
– HTTP API (over UNIX or TCP socket)
– embedded CLI talking to the API
● Open Source (GitHub public repository + issue
tracking)

Authoring images
with run/commit
1) docker run ubuntu bash
2) apt-get install this and that
3) docker commit <containerid> <imagename>
4) docker run <imagename> bash
5) git clone git://.../mycode
6) pip install -r requirements.txt
7) docker commit <containerid> <imagename>
8) repeat steps 4-7 as necessary
9) docker tag <imagename> <user/image>

Authoring images
with a Dockerfile
FROM ubuntu
RUN apt-get -y update
RUN apt-get install -y g++
RUN apt-get install -y erlang-dev erlang-manpages
erlang-base-hipe ...
RUN apt-get install -y libmozjs185-dev libicu-dev
libtool ...
RUN apt-get install -y make wget
RUN wget http://.../apache-couchdb-1.3.1.tar.gz | tar
-C /tmp -zxf-
RUN cd /tmp/apache-couchdb-* && ./configure && make
install
RUN printf "[httpd]nport = 8101nbind_address =
0.0.0.0" >

Authoring Images
with Chef/Puppet/Ansible/Salt/...
Plan A: « my other VM is a container »
● write a Dockerfile to install $YOUR_CM
● start tons of containers
● run $YOUR_CM in them
Good if you want a mix of containers/VM/metal
But slower to deploy, and uses more resources

Authoring Images
with Chef/Puppet/Ansible/Salt/...
Plan B: « the revolution will be
containerized »
● write a Dockerfile to install $YOUR_CM
● … and run $YOUR_CM as part of build
process
● deploy fully baked images
Faster to deploy
Easier to rollback

Docker: the community
● Docker: >200 contributors
● <7% of them work for dotCloud Docker inc.
● latest milestone (0.6): 40 contributors
● ~50% of all commits by external contributors
● GitHub repository: >800 forks

Docker: the ecosystem
● Cocaine (PAAS; has Docker plugin)
● CoreOS (full distro based on Docker)
● Deis (PAAS; available)
● Dokku (mini-Heroku in 100 lines of bash)
● Flynn (PAAS; in development)
● Maestro (orchestration from a simple YAML
file)
● OpenStack integration (in Havana, Nova has a
Docker driver)

Docker long-term roadmap
Docker 1.0:
● dynamic discovery
● remove AUFS, THINP, LXC, etc.
– execution? chroot!
– storage? cp!
– we can run everywhere o/
● re-add everything as plugins

Thank you! Questions?
http://docker.io/
http://docker.com/
https://github.com/dotcloud/docker
@docker
@charme_g

Introduction to Docker and Containers

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