Twitter deals with scalability problems through architectural solutions like decoupling systems, caching, database sharding, and moving to Scala on Rails. This allows individual components to scale independently. They also focus on monitoring all systems, testing deployments, and avoiding synchronous calls. Lessons learned are to keep systems simple, test extensively, and collect comprehensive metrics to address unexpected problems as traffic grows rapidly.

1. Highly scalable
architectures
How Twitter deals with its scalability problems
Benjamin Hiltpolt Master Seminar 3

2. ● Scalability
● Twitter
○ Introduction
○ Problems
○ Solutions
● Summary
Overview

3. ... is the ability of a system, network, or
process, to handle a growing amount of
work in a capable manner or its ability to
be enlarged to accommodate that growth.
Scalability
1. André B. Bondi, 'Characteristics of scalability and their impact on performance', Proceedings of the 2nd international workshop on
Software and performance, Ottawa, Ontario, Canada, 2000, ISBN 1-58113-195-X, pages 195–203

4. ● Horizontally
● Vertically
Scalability

5. ● load scalability
● functional scalability
● administrative scalability
● geographic scalability
Scalability challenges

6. ● microblogging
● tweets: 140 chars
● 500M registered users
● 1.6 Billion searches per day
● 90M TPD
Twitter

7. downtime 2007: 5d 23h
~2% downtime
FIFA World Cup 2010: Service Rejections
~10-20%
Scalability problems

8. June 2009 Twitpocalypse
September 2009 Twitpocalypse
solution: Snowflake
Scalability problems

9. presidential elections
● 31 M tweets
● 327452 TPM
● 455000 retweets of this photo
how do they manage this?
Twitter now

10. starting October 2010
● do a lot of monitoring
● use open source
● decoupling -> soft launches
● review system
Redesign

11. Puppet
Review Board
Murder (bittorrent)
Darkmode
Management

12. open API
● single point to optimize
● use the crowd to extend twitter
● 90% of all calls
API

13. ● cache (DB only Backup)
● memcache
● denormalize
● avoid joins
● sharding
○ (Flock DB --> MySQL)
Database

15. biggest rails application
unicorn (no downtime during deploy)
rails scales
ruby doesn't ?
Ruby on Rails

16. faster (20%)
JVM: Garbage collection
scalable
static types
Scala on Rails

17. first Starling (Ruby)
● mid-2008 queue crashed
now Kestrel (Scala, Memcache)
Queue

18. big problem
● e.g. bot harvesting friends
solutions:
● realistic limits
● delete such accounts
Abuse

19. Unexpected problems:
● Twitpocalypse
● UNIX: Cron, Syslog fail
● most (first) solutions will fail
Lessions

20. ● DRY, KISS
● testing (deploy only if tests pass)
● monitoring (collect everything)
● caching
● avoid synchronous calls
Lessions:

21. Thank you!
Questions?

22. http://engineering.twitter.com/2010/09/tech-behind-new-twittercom.html
http://www.theregister.co.uk/2012/11/08/twitter_epic_traffic_saved_by_java/
http://engineering.twitter.com/2012/11/bolstering-our-infrastructure.html
http://blog.twitter.com/2010/09/better-twitter.html
http://highscalability.com/blog/2009/6/27/scaling-twitter-making-twitter-10000-percent-faster.html
http://www.youtube.com/watch?v=gxUWfQmN8-4&feature=gv
http://www.youtube.com/watch?v=z8LU0Cj6BOU
http://blog.redfin.com/devblog/2010/05/how_and_why_twitter_uses_scala.html
http://www.artima.com/scalazine/articles/twitter_on_scala.html
http://www.technologyreview.com/view/412834/the-secret-behind-twitters-growth/?nlid=1908
http://www.unlimitednovelty.com/2009/04/twitter-blaming-ruby-for-their-mistakes.html
http://www.infoq.com/news/2009/06/Twitter-Architecture Twitter architecture overview
http://highscalability.com/blog/2009/4/5/at-some-point-the-cost-of-servers-outweighs-the-cost-of-prog.html
http://blog.obiefernandez.com/content/2009/04/my-reasoned-response-about-scala-at-twitter.html
refs