Introduction to Docker at SF Peninsula Software Development Meetup @Guidewire

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

?

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node.js
async API

?

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background
workers

?

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distributed
DB, big data

?

?

?

?

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message
queue

?

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?

?

SQL database

my laptop your laptop QA

staging

prod on prod on bare
cloud VM metal

Another Matrix from Hell
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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 host distro

–
●

regardless of kernel version
(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); seccompbpf
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
Changing
large files
Diffing

Superfast
Supercheap

Fast
Cheap

Fast
Costly

Slow (first time)
Inefficient (copy-up!)

Fast
Cheap

Fast
Cheap

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 at SF Peninsula Software Development Meetup @Guidewire

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
–
–

HTTP API (over UNIX or TCP socket)

–
●

manages containers, images, and builds
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
erlang-base-hipe ...
libtool ...

g++
erlang-dev erlang-manpages
libmozjs185-dev libicu-dev
make wget

RUN wget http://.../apache-couchdb-1.3.1.tar.gz | tar
-C /tmp -zxfRUN 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.
–
–

storage? cp!

–
●

execution? chroot!
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 at SF Peninsula Software Development Meetup @Guidewire

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