Scaling Django for X Factor - DJUGL Oct 2012
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Talk at the Django User Group London meeting, October 2012
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Scaling Django for X Factor - DJUGL Oct 2012
- 1. SCALING DJANGO FOR X FACTOR MALCOLM BOX, DJUGL OCTOBER 2012
- 2. WHAT I’M TALKING ABOUT Scaling Django to >10K request/s Caching, Counting and Cassandra Toolbox
- 3. ME Malcolm Box, CTO & Co-Founder @malcolmbox malcolm@tellybug.com http://tellybug.com
- 4. Making TV more entertaining Live interaction Highly social Unique content
- 5. WHO ARE YOU? Technical? Running Django? Scale?
- 7. THE CHALLENGE Millions of people watch the shows we work with
- 8. THE CHALLENGE Millions of people watch the shows we work with TV tells them to buzz/clap/ score....
- 9. THE CHALLENGE Millions of people watch the shows we work with TV tells them to buzz/clap/ score.... A giant DDOS is launched against our servers
- 10. HOW BIG? Peak loads of 10,000 requests/s Read/write mix Write-heavy workload - lots of user interactions
- 11. HOW BIG? 10K REQUESTS/S IS 25,920,000,000 REQUESTS/MONTH
- 12. The Internet ARCHITECTURE Static assets HAProxy layer Entirely cloud based Web layer Chef Nodes come and Cache go - frequently! Monitor Cassandra Cluster Automatic Task deployment direct RDS MySQL Server from Github via Amazon AWS eu-west-1 Logs, backups Amazon S3 Chef
- 13. CACHING Cache as speedup or Cache as mission-critical? Use Django cache framework Pylibmc - consistent hashing and server death patches Problems as you scale up...
- 14. CACHE PROBLEMS Cache miss behaviour value = cache.get(key) if value is None: try: Thundering herds are bad lock = cache.add(lock_key(key)) if lock: Key overload # Do something expensive new_value = calculate_new_value() cache.set(key, new_value) Server overload return new_value finally: Dualcache - https:// if lock: cache.delete(lock_key(key) gist.github.com/953524 return value
- 15. COUNTING Hard to count a few things very fast And have real-time access to the latest result Things we tried: memcache Cassandra counters Final solution: Sharded counters
- 16. SHARDED COUNTERS Implemented in about 350 lines of Python To provide two basic operations! incr() get() Uses a combination of two layers of memcache and Cassandra to provide real-time, scalable counters
- 17. CASSANDRA Core piece of our infrastructure Highly write-scalable Reads scaled from cache Using Acunu Cassandra for virtual nodes “Fake” Django ORM classes to make it feel more natural But no automatic join support
- 18. TOOLBOX Development Django Extensions, Celery, Piston (heavily forked), iPython, pycassa Tsung (load testing tool) Deployment: Fabric, Chef, Boto Operations Sentry, Gargoyle
- 19. THINGS THAT STILL SUCK Monitoring
- 20. Q&A AND YES, WE’RE HIRING SO IF YOU’RE INTERESTED IN BUILDING EXTREMELY LARGE DJANGO SITES THEN GET IN TOUCH MALCOLM@TELLYBUG.COM
Notas del editor
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- XFactor 2012 app. Also Switch, BGT, Arab Voice, Unzipped...\n
- Questions for audience:\n\n- Technical?\n- Running Django in production\n- Scale - 10 ... 100 .... 1000 .... 10000 .... 100000 req/s\n
- XFactor - over 1M installs, 260 Million boos/claps\nBGT - 250K simultaneous users\n\n
- XFactor - over 1M installs, 260 Million boos/claps\nBGT - 250K simultaneous users\n\n
- XFactor - over 1M installs, 260 Million boos/claps\nBGT - 250K simultaneous users\n\n
- XFactor - over 1M installs, 260 Million boos/claps\nBGT - 250K simultaneous users\n\n
- XFactor - over 1M installs, 260 Million boos/claps\nBGT - 250K simultaneous users\n\n
- XFactor - over 1M installs, 260 Million boos/claps\nBGT - 250K simultaneous users\n\n
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- cf Google serving 34K searches/s worldwide\n
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- Cache is either a speedup for your site, or it is mission critical. The deciding factor is whether your DB can handle the load if the cache fails.\nAt > 500 req/s, MySQL on AWS can’t keep up - hence cache is critical\n\n
- Discuss the code:\n- what happens if you return None? How does that affect upstream bits of code?\n- occasional latency problems if the value expires - everything fails for as long as calculate_new_value() takes to return\n\nGhetto locking - if using to protect e.g. DB writes, the key itself can end up as a problem\n\n
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- Describe how sharded counters work\n- and the very interesting challenge of debugging!\n
- Used for write performance rather than data size - still more data in MySQL than Cassandra\n\n
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- Mini rant - trouble finding any tool that copes with a highly scalable infrastructure up and down\n\nTried: Zabbix, Nagios, Cloudwatch, New Relic, Sensu, librato ... and probably some others\nNow building our own :(\n
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