Designing a Distributed Cloud Database for Dummies

1 . The Webinar! Patrick McFadin VP Developer Relations, DataStax @PatrickMcFadin 1 

2 . What is a Distributed Cloud Database? 2 

3 . What is a Distributed Cloud Database? Private Cloud 3 

4 .What Makes a Distributed Cloud Database? 4 

5 . Masterless No Single Point of Failure Node 1 Node 4 Node 2 Node 3 Hard to Bring Down 5 

6 . Scale for size Data Volume Node Count 6 

7 . Highly Performant Source: https://econsultancy.com/blog/10936-site-speed-case-studies-tips-and-tools-for-improving-your-conversion-rate 7 

8 .Why a Distributed Cloud Database??? 8 

9 .9 

10 . 133 ms Looks like you want to go faster than light. Can I help? Yes No 10 

11 . Highly Performant Source: https://econsultancy.com/blog/10936-site-speed-case-studies-tips-and-tools-for-improving-your-conversion-rate 11 

12 . Angry Users Don’t Give You Money 12 

13 . Happy Users Give You Money 13 

14 . Resilience 14 

15 . Ready for Reality? Data Center 1 Data Center 2 Node 1 Node 1 Node 4 Node 2 Node 4 Node 2 Node 3 Node 3 15 

16 . Remember AWS:Reboot? 16 

17 . Break it on Purpose! 17 

18 . A Way of Life https://principlesofchaos.org/ 18 

19 . Angry Users Don’t Give You Money 19 

20 . Happy Users Give You Money 20 

21 . Choice in Cloud Services 21 

22 . Not All Clouds are the Same Elastic Transcoder Deep Learning 22 

23 . Why Won’t Existing Technology Work? 23 

24 .Primary-Replica Read and Write Primary • One server designated as Primary • All changes must go through Primary • Reads can be from the Replica Client Copy • Failure requires stopping applications and moving Primary to one of the Replicas • Scaling writes requires sharding Read Replica 

25 .Sharding shard 1 shard 2 shard 3 shard 4 Primary Primary Primary Primary App Server client 25 

26 . Scaling Does Not Have to be Shard 26 

27 .Master-Master Primary Read and Write • Multiple servers designated at Primary • Clients read and write to a specific Primary • Primaries resolve change conflicts Conflict between each other Client Resolution • Each node has 100% of data • On failure, clients need to fail to another primary • Conflict management prohibits multi- Read and Write datacenter Primary 

28 . Distributed Architectures Added to an Existing Database* *Watch out for fine print 28 

29 .Masterless • Also known as Peer-to-Peer or Shared Nothing • Each node stores part of the total data with overlap Client • Clients can write to any node • Optimized for working across multiple geographic locations • On node failure, client continues to talk to online nodes