8. Monthly @
Thousands of developers hitting API
Hundreds of thousands of publishers
Tens of millions of shares & clicks
Hundreds of millions of pageviews & events
9. Tech @
JRuby on Rails (via Torquebox)
MySQL (Master, Read Slave)
Elastic MapReduce (similar to Hadoop)
Redis
Formerly Mongo, Now Riak
10. Why Not Mongo?
Working set needs to fit in memory
Global write lock blocks all queries
despite not having transactions/joins
Standbys not “hot”
12. Next @
Options: Goals:
HBase Linear scalability
Cassandra Full-text search
Riak Flexible indexing
Easier Devops
13. HBase
Pros Cons
Battle tested Complex
Architecture
High performance
SPOFs
Requires Hive for
Indexing/Querying
Expensive to deploy
at small scale
14. Cassandra
Pros Cons
Native secondary Known users all
indices domain experts
Linear scalability Search requires
Lucene
Tunable CAP
Heavy Weight
MapReduce
15. Riak
Pros Cons
Operationally simpler Multi-data center
replication requires
Linear scalability Enterprise product
Integrated search leveldb puts high
strain on CPU
Secondary indices
Tunable CAP
Vector clocks solve
time-sync problems
29. In a Nutshell
EC2 specs poorly proportioned for leveldb
Multiple AZs in one location works well
Scale vertically for better latency & consistency
Scale horizontally for more throughput/$