1. Ken Birman Professor, Dept. of Computer Science

2.  Today’s cloud computing platforms are best for building “apps” like YouTube, web search  Highly elastic, pipelined (“asynchronous”) services  But very weak guarantees and limited security  The cloud comes with its own mantra:  Don’t use ACID! BASE is better…  CAP theorem proves it (or does it?)

3. 3Sept 24, 2009Cornell Dept of Computer Science Colloquium

4.  As described by Randy Shoup at LADIS 2008 Thou shalt… 1. Partition Everything 2. Use Asynchrony Everywhere 3. Automate Everything 4. Remember: Everything Fails 5. Embrace Inconsistency Sept 24, 2009Cornell Dept of Computer Science Colloquium4

5.  Werner Vogels is CTO at Amazon.com…  His first act?  Introduced a series of weak consistency options  Replaced the older strongly consistent “pub/sub” infrastructure with slower but more scalable one  In small systems, raw speed wins  In the cloud  Weaker forms of guarantees often scale far better than strong ones Sept 24, 2009Cornell Dept of Computer Science Colloquium5

6.  Key to scalability is decoupling, loosest possible synchronization  Any synchronized mechanism is a risk  His approach: create a committee  Anyone who wants to deploy a highly consistent mechanism needs committee approval …. They don’t meet very often Sept 24, 2009Cornell Dept of Computer Science Colloquium6

7. 7 Consistency technologies just don’t scale! Sept 11, 2009P2P 2009 Seattle, Washington Sept 24, 2009Cornell Dept of Computer Science Colloquium

8. A consistent distributed system will often have many components, but users observe behavior indistinguishable from that of a single-component reference system Reference ModelImplementation Sept 24, 2009Cornell Dept of Computer Science Colloquium8

9.  We’re being too quick to give up on consistency and other assurance properties  CAP, BASE are really about database consistency  Other very strong forms of consistency can be the foundation for a new science of highly assured, high speed, scalable cloud computing  We have the science to back our vision  The new Isis 2 system makes it real

10.  Named for an old Cornell story  In 1990 our first Isis Toolkit became the core of the NYSE, French Air Traffic Control System and US Navy AEGIS  Isis 2 : A completely new system but same idea  Makes it easy to create high-assurance cloud apps  Offers consistency, fault-tolerance, security  FreeBSD code release later this spring

11.  Virtual synchrony is a “consistency” model:  Synchronous runs: indistinguishable from non-replicated object that saw the same updates (like Paxos)  Virtually synchronous runs are indistinguishable from synchronous runs Synchronous executionVirtually synchronous execution Sept 24, 2009Cornell Dept of Computer Science Colloquium11 Non-replicated reference execution A=3B=7B = B-A A=A+1

12. Replies = g.query(LOOKUP, “Name=*Smith”); g.callback(myReplyHndlr, Replies, typeof(double)); public void myReplyHndlr(double[] fnd) { foreach(double d in fnd) avg += d; … } public void myLookup(string who) { divide work into viewSize() chunks this replica will search chunk # getMyRank(); ….. reply(myAnswer); } Group g = new Group(“/amazon/something”); g.register(LOOKUP, myLookup);

13.  Used if group is really big  Request, updates: still via multicast  Response is aggregated within a tree Level 0 Level 1 Level 2 Agg(v a v b v c v d ) query a a ca c db vava vbvb vcvc vdvd Agg(v c v d ) Agg(v a v b ) reply Example: nodes {a,b,c,d} collaborate to perform a query

14. Replies = g.query(LOOKUP, 27, “Name=*Smith”); g.callback(myReplyHndlr, Replies, typeof(double)); public void myReplyHndlr(double[] fnd) { The answer is in fnd[0]…. } public void myLookup(int rid, string who) { divide work into viewSize() chunks this replica will search chunk # getMyRank(); ….. SetAggregateValue(myAnswer); } Group g = new Group(“/amazon/something”); g.register(LOOKUP, myLookup); Rval = GetAggregateResult(27); Reply(Rval/DatabaseSize);

15.  Partnering with Cisco to apply these ideas in core Internet routers (NEBULA/R3 projects)  Creating a continuously available CRS-1 story  Close dialogs with Microsoft, IBM, Intel  Funding from National Science Foundation, Air Force, talking to DARPA and ARPAe  Government, military and smart power grid will all need highly assured cloud options

16.  Debugging a system that targets thousands of nodes with tens of cores each is hard!  We benefit from our own strong model  But physical access to non-virtualized large-scale systems is “difficult” today  And many block IPMC and UDP  Better tools will need to be part of a better assurance property  Else we know how it should work but not how it does work, or even whether it works correctly!

17.  The word on the street is that cloud computing will rule but that the cloud can’t do high assurance  At Cornell we just don’t believe that  Not long from now we’ll put a solution in your hands showing how it can be done