Docker and Containers for Development and Deployment — SCALE12X

Best practices in
development and deployment,
with Docker and Containers

February 2014—Docker 0.8.1

@jpetazzo
●

Wrote dotCloud PAAS deployment tools
–EC2,

●

LXC, Puppet, Python, Shell, ØMQ...

Docker contributor
–Docker-in-Docker,

VPN-in-Docker,

router-in-Docker... CONTAINERIZE ALL THE THINGS!
●

Runs Docker in production
–You

shouldn't do it, but here's how anyway!

Outline
●

Why should I care?

●

The container metaphor

●

Very quick demo

●

Working with Docker

●

Building images

●

Docker future

Deploy everything
●

webapps

●

backends

●

SQL, NoSQL

●

big data

●

message queues

●

… and more

Deploy almost everywhere

YUP

SOON


YUP

SOON

SOON


YUP

SOON

SOON

CLI


YUP

SOON

SOON

CLI

Yeah,
right...

●

Linux servers

●

VMs or bare metal

●

Any distro

●

Kernel 3.8 (or RHEL 2.6.32)

Deploy reliably & consistently

Deploy reliably & consistently
●

If it works locally, it will work on the server

●

With exactly the same behavior

●

Regardless of versions

●

Regardless of distros

●

Regardless of dependencies

Deploy efficiently
●

Containers are lightweight
–
–

●

Typical laptop runs 10-100 containers easily
Typical server can run 100-1000 containers

Containers can run at native speeds
–

Lies, damn lies, and other benchmarks:
http://qiita.com/syoyo/items/bea48de8d7c6d8c73435

The performance!
It's over 9000!

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 »

How does it work?
Isolation with namespaces
●

pid

●

mnt

●

net

●

uts

●

ipc

●

user

pid namespace
jpetazzo@tarrasque:~$ ps aux | wc -l
212
jpetazzo@tarrasque:~$ sudo docker run -t -i ubuntu bash
root@ea319b8ac416:/# ps aux
USER
root
root

PID %CPU %MEM
1 0.0 0.0
16 0.0 0.0

(That's 2 processes)

VSZ
18044
15276

RSS TTY
1956 ?
1136 ?

STAT START
S
02:54
R+
02:55

TIME COMMAND
0:00 bash
0:00 ps aux

mnt namespace
jpetazzo@tarrasque:~$ wc -l
/proc/mounts
32 /proc/mounts

root@ea319b8ac416:/# wc -l /proc/mounts
10 /proc/mounts

net namespace
root@ea319b8ac416:/# ip addr
1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN
link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
inet 127.0.0.1/8 scope host lo
valid_lft forever preferred_lft forever
inet6 ::1/128 scope host
22: eth0: <BROADCAST,MULTICAST,UP,LOWER_UP>
pfifo_fast state UP qlen 1000

mtu 1500 qdisc

link/ether 2a:d1:4b:7e:bf:b5 brd ff:ff:ff:ff:ff:ff
inet 10.1.1.3/24 brd 10.1.1.255 scope global eth0
inet6 fe80::28d1:4bff:fe7e:bfb5/64 scope link

uts namespace
jpetazzo@tarrasque:~$ hostname
tarrasque
root@ea319b8ac416:/# hostname
ea319b8ac416

ipc namespace
jpetazzo@tarrasque:~$ ipcs
------ Shared Memory Segments -------key
shmid
owner
perms
0x00000000 3178496
jpetazzo
600
0x00000000 557057
jpetazzo
777
0x00000000 3211266
jpetazzo
600

root@ea319b8ac416:/# ipcs
------ Shared Memory Segments -------key
shmid
owner
perms
------ Semaphore Arrays -------key
semid
owner
perms
------ Message Queues -------key
msqid
owner
perms

bytes
393216
2778672
393216

nattch
2
0
2

status
dest

bytes

nattch

status

nsems
used-bytes

messages

dest

user namespace
●
●

●

No demo, but see LXC 1.0 (just released)
UID 0→1999 in container C1 is mapped to
UID 10000→11999 in host;
UID 0→1999 in container C2 is mapped to
UID 12000→13999 in host; etc.
what will happen with copy-on-write?
–

double translation at VFS?

–

single root UID on read-only FS?

How does it work?
Isolation with cgroups
●

memory

●

cpu

●

blkio

●

devices

memory cgroup
●

keeps track pages used by each group:
–

file (read/write/mmap from block devices; swap)

–

anonymous (stack, heap, anonymous mmap)

–

active (recently accessed)

–

inactive (candidate for eviction)

●

each page is « charged » to a group

●

pages can be shared (e.g. if you use any COW FS)

●

Individual (per-cgroup) limits and out-of-memory killer

cpu and cpuset cgroups
●

keep track of user/system CPU time

●

set relative weight per group

●

pin groups to specific CPU(s)
–

Can be used to « reserve » CPUs for some apps

–

This is also relevant for big NUMA systems

blkio cgroups
●

keep track IOs for each block device
–

read vs write; sync vs async

●

set relative weights

●

set throttle (limits) for each block device
–

read vs write; bytes/sec vs operations/sec

Note: earlier versions (<3.8) didn't account async correctly.
3.8 is better, but use 3.10 for best results.

devices cgroups
●

controls read/write/mknod permissions

●

typically:
–
–

deny: everything else

–
●

allow: /dev/{tty,zero,random,null}...
maybe: /dev/net/tun, /dev/fuse, /dev/kvm, /dev/dri...

fine-grained control for GPU, virtualization, etc.

How does it work?
Copy-on-write storage
●

Create a new machine instantly
(Instead of copying its whole filesystem)

●

Storage keeps track of what has changed

●

Since 0.7, Docker has a storage plugin system

Storage:
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

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 is the Future
(probably)

Dodge Ram 3500

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

Alright, I get this.
Containers = nimble VMs.

Problem: shipping goods
?

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Solution:
the intermodal shipping container

Problem: shipping code
?

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Separation of concerns:
Dave the Developer
●

inside my container:
–

my code

–

my libraries

–

my package manager

–

my app

–

my data

Oscar the Ops guy
●

outside the container:
–

logging

–

remote access

–

network configuration

–

monitoring

what it doesn't mean

« I don't have to care »
≠
« I don't care »

Yes, but...
●

●

●

« I don't need Docker;
I can do all that stuff with LXC tools, rsync,
and 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?
History
●

rewrite of dotCloud internal container engine
–
–

●

original version: Python, tied to dotCloud PaaS
released version: Go, legacy-free

remember SCALE11X talk about LXC?
–

Docker was announced one month later!

Docker-what?
Under the hood
●

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

Docker-what?
Take me to your dealer
●

Open Source
–

●

GitHub public repository + issue tracking
https://github.com/dotcloud/docker

Nothing up the sleeve
–

public mailing lists (docker-user, docker-dev)

–

IRC channels (Freenode: #docker #docker-dev)

–

public decision process

Docker-what?
The ecosystem
●

Docker Inc. (formerly dotCloud Inc.)
–
–

●

~30 employees, VC-backed
SAAS and support offering around Docker

Docker, the community
–

more than 300 contributors, 1500 forks on GitHub

–

dozens of projects around/on top of Docker

–

x100k trained developers

One-time setup
●

On your servers (Linux)
–
–

Single binary install (Golang FTW!)

–
●

Packages (Ubuntu, Debian, Fedora, Gentoo, Arch...)
Easy provisioning on Rackspace, Digital Ocean, EC2, GCE...

On your dev env (Linux, OS X, Windows)
–

Vagrantfile

–

boot2docker (25 MB VM image)

–

Natively (if you run Linux)

The Docker workflow 1/2
●

●

●

Work in dev environment
(local machine or container)
Other services (databases etc.) in containers
(and behave just like the real thing!)
Whenever you want to test « for real »:
–

Build in seconds

–

Run instantly

The Docker workflow 2/2
Satisfied with your local build?
●

Push it to a registry (public or private)

●

Run it (automatically!) in CI/CD

●

Run it in production

●

Happiness!

Something goes wrong? Rollback painlessly!

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>
10) docker push <user/image>

Authoring images
with run/commit
●

Pros
–
–

●

Convenient, nothing to learn
Can roll back/forward if needed

Cons
–

Manual process

–

Iterative changes stack up

–

Full rebuilds are boring, error-prone

Authoring images
with a Dockerfile

FROM ubuntu
RUN
RUN
RUN
RUN
RUN

apt-get
apt-get
apt-get
apt-get
apt-get

-y update
install -y
install -y
install -y
install -y

g++
erlang-dev erlang-manpages erlang-base-hipe ...
libmozjs185-dev libicu-dev libtool ...
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" >
/usr/local/etc/couchdb/local.d/docker.ini

EXPOSE 8101
CMD ["/usr/local/bin/couchdb"]

docker build -t jpetazzo/couchdb .

Authoring images
with a Dockerfile
●

Minimal learning curve

●

Rebuilds are easy

●

Caching system makes rebuilds faster

●

Single file to define the whole environment!

Do you even
Chef?
Puppet?
Ansible?
Salt?

Docker and Puppet
●

Get a Delorean

●

Warm up flux capacitors

●

Time-travel to yesterday

●

Check Brandon Burton's lightning talk

●

Check my talk

— Or —
●

Get the slides, ask questions ☺

Coming Soon
●

Network acceleration

●

Container-specific metrics

●

Consolidated logging

●

Plugins (compute backends...)

●

Orchestration hooks

Those things are already possible,
but will soon be part of the core.

Docker 1.0
●

Multi-arch, multi-OS

●

Stable control API

●

Stable plugin API

●

Resiliency

●

Signature

●

Clustering

Recap
Docker:
●

Is easy to install

●

Will run anything, anywhere

●

Gives you repeatable builds

●

Enables better CI/CD workflows

●

Is backed by a strong community

●

Will change how we build and ship software

Thank you! Questions?
http://docker.io/
http://docker.com/
@docker
@jpetazzo

Docker and Containers for Development and Deployment — SCALE12X

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Docker and Containers for Development and Deployment — SCALE12X