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HOW TO
SCALE YOUR
APP SOME ADVICE FROM
THE GUY WHO HANDLES
YOUR APP UPTIME
QUENTIN ADAM AT SCALA.IO
@WAXZCE

2013
MY DAY TO DAY WORK :
CLEVER CLOUD, MAKE YOUR APP RUN
ALL THE TIME
THERE ARE 2 WAYS

WHEN YOU
NEED TO
SCALE
GROWING AND GROWING
UNTIL YOU EXPLODE OR
BECOME WEIRD
OR SPLIT THE WORK AND
MAKE YOUR SOFTWARE
WORK AS A TEAM
YOU CAN DO BOTH
Build an army of fat app
SO WE NEED TO BE ABLE
TO DISPATCH THE WORK
SCALE OUT

SCALE UP

• Many workers
doing the same
thing

• 1 Fat instance

• 1 Fat application

• No SPOF

• SPOF (single point
of failure)

• Growing is more
easy

• Hard to maintain

• Introduce best
practice

• Always has a limit
• Short term
meaning
SO, HOW TO
SCALE OUT
?
JUST SOME FACTS
SPLIT PROCESS AND
STORAGE
Storage
• Databases
• Files
• Sessions
• Events
•…

Code
• Can be replicated
• Stateless
• Process
STATELESSNESS IS THE KEY
Picking one instance or another doesn’t matter
CONSIDER MORE
THINGS AS DATA
• User account

• Users data
• Files
• Sessions
• Events
TRUST YOUR
MIDDLEWARE
USE AN EVENT BROKER
TO MODULARIZE YOUR
APP
• AMQP

• Celery
• 0MQ
• Redis
• JMS
• Even some http chunk or websocket
• Some case : hadoop, akka…
• …
CRON + FS IS NEITHER AN EVENT
QUEUE NOR A JOB SCHEDULER
CHOOSE
YOUR
DATASTORE
WISELY
YOU CAN SHOULD USE MANY DATASTORES
DATASTORE CHOICES
ARE DRIVEN BY USAGE
Do I mostly
read or
write ?

Do I need
relational ?

Do I need
concurrent
access ?

Do I need
atomicity of
requests ?

Do I need
big storage
capacity ?

Make
decisions
based on
needs

Do I need
high
availability ?
USE ONLINE
DATABASE / BE
READY TO TEST
IN JUST A FEW
MINUTES
NO NEED TO TRASH YOUR COMPUTER
COMMON MISTAKES
DO NOT USE THE FILE
SYSTEM AS A DATASTORE
File system are POSIX compliant

•
•
•
•
•

POSIX is ACID
POSIX is powerful but is a bottleneck
File System is the nightmare of ops
File System creates coupling (host provider/OS/language)
SPOF-free multi tenant File System is a unicorn

STORE IN DATABASE, OR IN A DATASTORE LIKE
S3/RIAKCS DEDICATED TO FILE MANAGEMENT
LOGS IN FILES
I HATE IT
USE STREAMING I/O TO
STREAM DATA DIRECTLY
TO DATABASE

HTTP Post data

Temporarily
store as file
or in memory

Store it into
your storage
backend

Say OK to
client
USE STREAMING I/O TO
STREAM DATA DIRECTLY
TO DATABASE

HTTP Post data

Directly stream
your data to
Storage
backend

Say OK to
client
DO NOT USE
MEMORY AS
DATABASE
LIKE : SHARED / GLOBAL VARIABLE,
CACHE “IN THE CODE”, INTENSIVE
SESSION USAGE…
DO NOT USE A VARIABLE
FOR MORE THAN ONE
REQUEST
F(X) = X * 2
F(2) = 4

^ WE ASSUME THAT
FOR SAME INPUT, SAME OUTPUT
IT’S LIKE MATH FUNCTION
You have to understand that : you’re functional programing addicts ;-)
RESPECT HTTP
Example : GET should not change data on server
CODE
WILL
FAIL
data will be lost
CAREFUL USE OF
DARK MAGIC
DO NOT CREATE MONSTERS
MAKE HARD
COMPUTATION ASYNC
SPLIT THE CODE :
MODULES
• Smallest code
base

• Deploy as
service for
each other
• Focus on best
technology for
a problem
SCALE YOUR TEAM
MODULARIZE YOUR TEAM
ALWAYS USE A
REVERSE PROXY

Y U NO USE ONE ?
DO NOT BUILD “THE
SERVER” WITH NO DOC
USE PROCESS
DEPLOYMENT
THE GOOD WAY OF
DEPLOY AN APP :

git push
EASY MOVING OR
INCIDENT MANAGEMENT
KEEP CALM UNDER FIRE
TRACK BUG & GET METRICS
THX FOR LISTENING
& QUESTIONS TIME
I’m @waxzce on twitter

I’m the CEO of

sponsors
a non exclusive scala PaaS
provider, give it a try ;-)

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Some advice from the guy who handle your applications uptime - scalaIO 2013