A brief intro to how Barracuda Networks uses Cassandra and the ways in which they are replacing their MySQL infrastructure, with Cassandra. This presentation will include the lessons they've learned along the way during this migration. Speaker: Michael Kjellman, Software Engineer at Barracuda Networks Michael Kjellman is a Software Engineer, from San Francisco, working at Barracuda Networks. Michael works across multiple products, technologies, and languages. He primarily works on Barracuda's spam infrastructure and web filter classification data.

1. Hindsight is 20/20:
MySQL to Cassandra
Michael Kjellman (@mkjellman)
Barracuda Networks

2. What I Do
• Build and maintain “real-time” Spam
detection and Web Filter classification
• Java/Perl/C (and bits of everything else)
• Author perlcassa (Perl C* client)
• Frontend? Backend? Customer? Internal?
Broken RAID Card? Bad Disk? I touch it all.

3. Our C* Cluster
• In production for ~2 years since 0.8
• Running 1.2.5 + minor patches
• 24 nodes in 2 datacenters
• (2) 2TB Hard Drives (no RAID)
• (1) Small SSD for small hot CFs
• 64GB of RAM
• Puppet for management
• Cobbler for deployment
• Target max load at 600GB per node

4. What is “real-time” exactly?

6. Our Rewrite by the Numbers
Cassandra
Based
MySQL
Based
Average Application
Latency
2.41ms 5.0ms
Elements in Database 32,836,767 3,946,713
Elements Application
Handles
32,836,767 314,974
Element Seen Prior to
Tracking
1st request Various
Thresholds
Datacenters 2 1
Average Latency of
Automated
Classification
3 seconds 8 minutes

7. Should you Rewrite?
• How To Survive a Ground-Up Rewrite Without Losing
Your Sanity[1] – Joel Spolsky
• Past engineering decisions preventing
implementation of new business requirements
• New threats smarter and more targeted
[1]http://onstartups.com/tabid/3339/bid/97052/How-To-Survive-a-Ground-Up-Rewrite-Without-Losing-Your-Sanity.aspx

8. Evolving Legacy Systems
• Even good developers can write sloppy code
• Too much duct tape
– Most layers applied around the database

9. Hitting the Reset Button
• Plan for continuous failure
• Easily Scalable
• No Single Point of Failure – that you know of
• Many smaller boxes vs. one monolithic box

10. Whiteboard to Reality
• Get technical buy-in from all parties
• Migrate and rewrite in stages
– Business requirements forced hybrid period with
the old and new systems operated in parallel

12. Cassandra is Not…
1. Direct MySQL replacement
2. Magic bullet to solve everything

13. Migrating
• Painful
• Painful
• Painful
• Tons of rewriting
• Tons of regressions
• Did I say painful?

14. So Why Migrate?
• C* is the best option for persistence tier
• Business success motivation
• Don’t let your database hold you back

15. Lessons Learned (the good)
• Carefully defining data model up front
• Creating a flexible systems architecture that
adapts well to changes during implementation
• Seriously – “Measure twice, cut once.”

16. Lessons Learned (the bad)
• Consider migration and delivery requirements
from the very beginning
• Adjust expectations – didn’t expect relying on
legacy systems for so long
• Make syncing data between systems a priority

17. Tips
1. Start with the queries
2. Think differently regarding reads
3. Syncing and migrating data
4. Don’t use C* as a queue
5. Estimate capacity
6. Automate, Automate, Automate
7. Some maintenance required

18. 1. Start with the Queries
• C* != “#dontneedtothinkaboutmyschema”
• Counters and Composites
• Optimize for use case
– Don’t be afraid of writes. Storage is cheap.
– Optimize to reduce the number of tombstones

19. 2. Think Differently Regarding Reads
• Do you really need all that data at once?
• mysql> SELECT * FROM mysupercooltable
WHERE foo = ‘bar’;
– Slow, but eventually will work
• cqlsh> SELECT * FROM myreallybigcf
WHERE foo = ‘bar’;
– Won’t work. Expect RPC timeout exceptions on reads
generally after ~10,000 rows even with paging
• Our solutions:
– ElasticSearch
– Hadoop/Pig

20. 3. Syncing and Migrating Data
• Sync and migration scripts – take more
seriously than production code
• Design sync to be continuous with both
systems running in parallel during migration
• Prioritize the sync

21. 4. Don’t use C* as a Queue
• Cassandra anti-patterns: Queues and queue-
like datasets[2] – Aleksey Yeschenko
• Tombstones + read performance
• Our solution:
– Kafka (multiple publisher, multiple consumer
durable queue)
[2]http://www.datastax.com/dev/blog/cassandra-anti-patterns-queues-and-queue-like-datasets

22. 5. Estimate Capacity
• Don’t forget the Java heap (8GB Max)
• Plan capacity – today and future
• Stress Tool – profile node and multiply
• MySQL hardware != Cassandra hardware
• New bottlenecks thanks to C* being so
awesome?
• I/O still an important concern with C*

23. 6. Automate, Automate, Automate
• Love your inner Ops self. Distributed systems
move complexity to operations.
• Puppet or something similar (really)
• Learn CCM earlier rather than later
– www.github.com/pcmanus/ccm

24. 7. Some Maintenance Required
• Repairs & Cleanup ops
– automate and run frequently
• Rolling restart meet rolling
repair
• Learn jconsole
• Solution:
– Jolokia (JMX via HTTP)

25. Where is Barracuda Today?
• 2 years in production with Cassandra
• Definitely the right choice for our persistence
tier
• 2 product lines on C* based system and
another major product in beta
• Achieved “real-time” response

26. 2.0 and Beyond
• Thrift -> CQL
• CQL helps the MySQL to C* migration
– Easier to comprehend / grasp
• Everyone understands SELECT * FROM cf WHERE
key = ‘foo’;
• CAS and other 2.0 features make C* an even
better replacement option for MySQL

27. C* Community
• Supercalifragilisticexpialidocious community!
• Riak, HBase, Oracle are other options. How is
their dev community?
• Great client support. Great people. Great
motivated developers.
• IRC: #cassandra on freenode
• Mailing List: user@cassandra.apache.org