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Bryce "BonzoESC" Kerley
April 26, 2014
Programming
0
55
Growing Distributed Systems: Abril Pro Ruby
The Abril Pro Ruby version of my Growing Distributed Systems talk.
Bryce "BonzoESC" Kerley
April 26, 2014
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Transcript
Growing Distributed Systems
Hello Bryce Kerley @bonzoesc basho
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Distributed Systems What even are they?
Distributed Systems
Distributed Systems Always Broken
Distributed Systems Light Cones
Mutual visibility Soldier Fires Sniper Fires
Distributed Systems A distributed system is one in which the
failure of a computer you didn’t even know existed can render your own computer unusable. Lamport, 1987
Distributed Systems •Rules and Theory •Inconsistency and Unavailability •Distributed Rails
Byzantine Generals Two armies One town
Byzantine Generals Horse messengers
Byzantine Generals Consensus on when to attack
Byzantine Generals No Right Answer
Criticality •Amazon S3, July 2008 •GitHub, Dec. 2012 •Northeast US,
2003
Murphy’s Law at Scale •Backblaze •Gears of War 2
CAP Theorem Consistency Availability Partition tolerance
Rules, Theory, and Practice Compromise
Distributed Systems •Rules and Theory •Inconsistency and Unavailability •Distributed Rails
CAP Theorem lose Consistency or Availability during Partitions
Partitions
Partitions
CP Systems Zookeeper
Unavailability Don’t fill requests
Unavailability oonbeamlabs
AP Systems Riak
Inconsistency Accept writes Perform reads
Inconsistency
Hybrid Multiple Stores
Hybrid Where It Counts
Hybrid Riak 2 Strong Consistency
Distributed Systems •Rules and Theory •Inconsistency and Unavailability •Distributed Rails
Distributed Rails You’re Already Distributed
Distributed Rails Rails
Distributed Rails Rails Web DB
Distributed Rails SQL Rules
Distributed Rails NoSQL No Rules
Distributed Rails Temptation
Temptation “We’ll put everything in Rails models.”
None
Distributed Rails Service Oriented Architecture
Service Oriented Extract Parts
Service Oriented Documented Protocols
Service Oriented Smaller Deployments
Service Oriented Simpler Organization
Service Oriented Break Coupling
Service Oriented Flexible Implementation
Testing Unit Tests
Testing Service Tests
Testing Acceptance Tests
Testing Refactoring [GitHub] with Science Wynn Netherland, Big Ruby, Feb.
2014
Offline Apps Latency Garbage Collection Packet loss Airplane rides Local
internet
Offline Apps Smarter clients
Offline Apps You’re Already Doing It
Offline Strategies Conflicts
Offline Strategies Operational Transform
Offline Strategies Git
Offline Strategies Vesper
Distributed Systems •Rules and Theory •Inconsistency and Unavailability •Distributed Rails
Ruby Works
Make Something Awesome
Grow When You Need To
Thanks Bryce Kerley @bonzoesc
[email protected]
http://bitly.com/aprb-dist
Bonus Slides
Consensus Algorithm Paxos 1989
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Consensus Algorithm Raft 2013
Harvest & Yield Harvest: fraction of data Yield: probability of
success
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NoSQL and Rails SQL ACID
NoSQL and Rails Atomicity Consistency Isolation Durability
NoSQL and Rails NoSQL BASE
NoSQL and Rails Basically Available Soft-state Eventually consistent
Offline Libraries Breeze PouchDB Lawnchair
Must Watch Jeff Hodges “Practicalities of Productionizing Distributed Systems” youtu.be/BKqgGpAOv1w