Google I/O 2009 - Transactions Across Datacenters (and Other Weekend Projects) Ryan Barrett -- Contents -- 0:55 - Background quotes 2:30 - Introduction: multihoming for read/write structured storage 5:12 - Three types of consistency: weak, eventual, strong 10:00 - Transactions: definition, background 12:22 - Why multihome? Why try do anything across multiple datacenters? 15:30 - Why *not* multihome? 17:45 - Three kinds of multihoming: none, some, full 27:35 - Multihoming techniques and how to evaluate them 28:30 - Technique #1: Backups 31:39 - Technique #2: Master/slave replication 35:42 - Technique #3: Multi-master replication 39:30 - Technique #4: Two phase commit 43:53 - Technique #5: Paxos 49:35 - Conclusion: no silver bullet. Embrace the tradeoffs! 52:15 - Questions -- End -- If you work on distributed systems, you try to design your system to keep running if any single machine fails. If you're ambitious, you might extend this to entire racks, or even more inconvenient sets of machines. However, what if your entire datacenter falls off the face of the earth? This talk will examine how current large scale storage systems handle fault tolerance and consistency, with a particular focus on the App Engine datastore. We'll cover techniques such as replication, sharding, two phase commit, and consensus protocols (eg Paxos), then explore how they can be applied across datacenters. For presentation slides and all I/O sessions, please go to: code.google.com/events/io/sessions.html
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