In order to provide the computing power you need in a flexible manner. This hardware would be servers like the Intel-based blade servers, and the software would include the free (or almost free) open-source Linux operating system. By choosing small, generic servers, your system will cost much less than a traditional large server system, and because you can dynamically reallocate or provision resources based on actual needs, you’ll be using resources efficiently. Grid computing (also referred to as computing on demand and utility computing) isn’t a new innovation invented solely by Oracle DBA. The idea of grid computing has been around for a while, primarily in the academic world.
In fact, grid computing arose out of the academic community’s need for extremely fast and scalable computers to perform complex, massive research tasks. Another overriding goal of the academic community was to permit the sharing of computing resources among large numbers of researchers. Of course, the academics also aimed to keep the cost as low as possible. Grid computing emerged out of these efforts as a viable way to create huge sharable computing environments that are dynamically adjustable to changes in the demand for computing power. When we talk about harnessing the power of a number of commodity servers, realize that the number of computers may not be limited to just a handful. We are talking about combining the power of a fairly large number of small servers linked together to form a grid. Obviously, the key idea here is that the sum is far greater than the individual components. Enterprise grid computing, as envisioned by Oracle DBA, uses large pools of modular storage and commodity servers. Underutilization of resources will be cut down, because capacity could be altered from the centralized pool of resources as necessary. The total cost of a grid environment could be considerably lower than a traditional single, big server environment.