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Cloud Computing, and what it means for the Grid

I'm nowadays attending the 23rd Open Grid Forum in Barcelona, which is one the largest Grid computing events on the calendar. This year there has been quite a stir caused by the rise of cloud computing services such as Amazon Web services which are seen as a competitor to Grids, such as OSG or EGEE.Today at the keynote by Amazon CTO, Werner Vogels, he presented the cogent business logic which underlines Cloud computing, and why he thinks Amazon AWS has been so successful. Amazon AWS allows anyone from little startups (e.g. animoto ) to large scale companies (e.g. Salesforce) to get access to cheap, reliable, fault tolerant and scalable computing infrastructure. Had these companies thought of doing their computing locally, they would have probably spent 80% of their resources on setting up and running the computing infrastructure which would be an undifferentiated service because anyone who wants to do large scale computing has to setup and run the computing infrastructure. The infrastructure costs money and doesn't make any money for the organization, what does make money for the organization is the 20% business logic the company uses its computing infrastructure for, so with Cloud computing companies can get rid of the 70-80% effort on a largely undifferentiating services and focus on the tasks which would eventually make them money! This has been increasingly realized by all quarters of the industry and hence we see major companies jumping on the bandwagon: Microsoft's Live Mesh, Google's App Engine, IBM and SAP's effort with the EU on Reservoir etc.). So from a layman's perspective it does look like Cloud computing is here to stay.But what about Grid Computing? Grid Computing is analogous to cloud computing but with marked differences: Grids are application specific! EGEE Grid infrastructure is designed to run e-Science applications largely anything from particle collision analysis to neuro-image analysis for Alzheimers. Grids impose application development models: High Energy Physics Grids (such as LCG, EGEE, parts of OSG) are mostly designed to work with Grid applications which are a pipeline of tasks, these Grids schedule and map these tasks onto distributed resources and make the results available to the users. Whereas other Grids like (like made with Globus 4.0, OMII, Taverna based etc.) are service Grids. These Grids assume that Grid applications consist of services instead of tasks. Now we have discussed the major division in modern Grid computing: task based vs. service based. There are other paradigms as well, which are variants of each.Cloud Computing does not impose any such restriction: They provide the infrastructure as a black box and it is up to the user how he wants to use it, if he desires he can virtualize an entire Globus Grid on it, at the same time, he may also setup a gLite Grid and work with tasks or he may not use either and just setup a cluster for MPI applications. Hence we can see that Clous definitely have an edge here.But having said all this, I do believe the Cloud computing and Grid computing will happily co-exist in the future. The infrastructure which Cloud computers will use will be Grids themselves, which will not schedule applications rather they will schedule virtual machines which encapsulate the user's application. But what happens if an application consisting of two virtual machines ends up being scheduling with both VMs in different sites or subnets? These issues and others will be tackled by a recent project which also has been covered extensively in this OGF and I will cover it later.