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EVOLUTION OF A
WEB ARCHITECTURE WITH
 AMAZON WEB SERVICES
    Richard Poirier @richpoirier
EVOLUTION OF A
WEB ARCHITECTURE WITH
 AMAZON WEB SERVICES
2010




1 million visitors / month
2012




10 million visitors / month
1&1




Web / DB / Mail
Memcached
Read Through Caching
Write Through Caching

  Replication + Caching =
Write Through Caching
Cache Stampedes
Op Code Caching
Scaling Web Servers
Scaling Web Servers
Avatars, Backgrounds, Covers, Text Files
Scaling Web Servers
Scaling the Master Database
Scaling the Master Database
Scaling the Master Database
Moving to RDS
Moving to RDS
Scaling Search
InnoDB > MyISAM
Background Jobs
Still Not Elastic
Thanks!




http://joind.in/7423
      @richpoirier

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Wattpad - Evolution of a Web Architecture with Amazon Web Services

Editor's Notes

  1. \n
  2. - youtube\n- upload\n- 7 million stories\n- mobile readers, website\n\n
  3. - current scale\n- very social\n
  4. - evolution\n- major, why\n
  5. - one server\n- no caching, simple\n
  6. - more complicated, lots more features\n- show you how we went from this (last slide) to this (this slide)\n
  7. - mail, web ok\n- db bottleneck, own server\n
  8. - web alone on ec2\n- mail\n- master for writes, slaves for reads\n- db still bottleneck, what’s hot, stories not changing\n
  9. - high performance, distributed, in memory object caching system\n- in memory key-value store\n- php extension\n- cache everything\n- read-through/write-through, stampedes\n
  10. - code maintainability\n- write through is data integrity\n
  11. - replication LAG\n- example - delete cache\n\n
  12. \n
  13. - explain\n
  14. - db’s humming\n- web server bottleneck, scaled vertically as much as possible\n- don’t want to split them\n
  15. - caching compiled bytecode of scripts\n- apc\n- great except zero-downtime deploy problems\n- bought us a few more months\n\n
  16. - one web server starting to look at a lot like this horse (donkey?)\n- need more horses\n- shared resources\n
  17. - reside on web servers\n- distributed file system\n
  18. - upload s3, cache hd\n- 100M req/month\n- rackspace bad\n- sessions\n- 4 web servers\n\n
  19. - ELB\n- haproxy, don’t skimp on instance size\n\n
  20. - horsedonkey\n- news feed\n\n
  21. - facebook\n- events 150M rows\n- 500M\n- redis\n
  22. - memcached but persist\n- 20k req/s\n- read counts, reading positions\n
  23. - redis added\n- master doing better, slaves struggling again\n
  24. - scalr, in a bad position\n- explain rds\n- concerns\n
  25. - migrate\n- july 1\n- 10 slaves -> 5 slaves\n\n
  26. - major things\n
  27. - full text search\n- real time indexing, really fast\n- easy to scale horizontally\n
  28. - row level locking\n
  29. - upload story\n- worker\n- also easy to scale horiz\n
  30. - this is where we’re at now\n- plus data’s stuff\n
  31. - still evolving\n- next year automated all scaling processess\n
  32. \n