Image courtesy of dsa-research.org

Ignacio Martín Llorente of the DSA (Distributed Systems Architecture) Research Group at the Universidad Complutense de Madrid discusses the relationship between cloud and grid computing in the group's blog.  A couple of excerpts follow.

Grid is as an interoperability technology, enabling the integration and management of services and resources in a distributed, heterogeneous environment. The technology provides support for the deployment of different kinds of infrastructures joining resources which belong to different administrative domains. In the special case of a compute grid infrastructure, such as EGEE or TeraGrid, grid technology is used to federate computing resources spanning multiple sites for job execution and data processing.

On the other hand, I do not think there is a single definition for cloud computing. From my view, the only new feature offered by cloud systems is the provision of virtualized resources as a service, where virtualization is the enabling technology. (What is virtualization?) In other words, the relevant contribution of cloud computing is the Infrastructure as a Service (IaaS) model. I should remark that virtualization has been used by the grid community before the arrival of the cloud.

A new virtualization layer between the service and the infrastructure layers decouples a server not only from the underlying physical resource but also from its physical location, without requiring any modification within service layers from either the service administrator or the end-user. Such decoupling is the key to supporting the scale-out of an infrastructure to supplement local resources with cloud resources to satisfy peak or fluctuating demands. 

The virtualization of a grid site provides several benefits, which overcome many of the technical barriers for grid adoption:

• Easy support for VO-specific worker nodes
• Reduce gridification cycles
• Dynamic balance of resources between VO’s
• Fault tolerance of key infrastructure components
• Easier deployment and testing of new middleware distributions
• Distribution of pre-configured components
• Cheaper development nodes
• Simplified training machines deployment
• Performance partitioning between local and grid services
• On-demand access to cloud providers

If you are interested in more details about how virtualization and cloud computing can support compute Grid infrastructures you can have a look at my presentation “An Introduction to Virtualization and Cloud Technologies to Support Grid Computing” (EGEE08). I also recommend the report “An EGEE Comparative study: Clouds and grids - evolution or revolution?”.

Read more.

See related articles Virtual Infrastructure (in iSGTW),  What clouds and grids can learn from each other and The new Nimbus: first steps in the clouds.