Way back in the 1980s companies like Digital Equipment Corp (now part of HP) developed clustering technology which allowed two or more computers to appear as if they were just one to the end-user, thereby enabling load-balancing and hot standby.
Oracle (starting with Oracle 9i) absorbed this technology into the database software so that databases could benefit from the load-balancing and hot-standby capabilities. This avoids the need to manually switch users from one database instance to another should a failure occur and just as importantly,and the need for applications to be cluster-aware.
That was one stepping stone in the evolutionary process, but companies like Sun Microsystems extended the concept of clusters to be able to include different types (makes) of computers running different operating systems in a "pool" of computing resources that can be made available as and when required to meet peak demands and then released back into the pool when no longer needed (so that other applications may use the resources).
The motivation for the development of grid computing is to reduce the need to have dedicated resources sized for peak capacity. Research has shown that the average CPU usage is only 15-20% and storage usage is only 50%. Having dedicated resources for each major application also means that there can be a large number of systems to maintain. The solution to this is to create a grid - a pool of low-cost servers + storage that can be allocated to applications to meet peak loads.
The idea of grid computing is to use many inexpensive devices to provide the total resources required, thereby providing intrinsic redundancy (if one device fails, replace it) and scalability (add more devices as the load increases). This is similar to the concept used with RAID. Grid Computing, however, takes this one stage further by enabling you to dynamically add or remove devices to adjust the amount of available resources to match the workload or to replace devices that have failed. Furthermore, this does not apply solely to storage devices, but also to computing devices - i.e. servers.
A few of the problems that grid computing is trying to solve are:
Oracle 10g fits into this scenario by including Real Application Clusters which is a technology (originally introduced with Oracle9i) that transforms a network of heterogeneous servers into a single entity. This is the processing grid which is managed by Oracle Enterprise Manager and provides:
The storage grid is the other essential part of the infrastructure and this is managed by the Automatic Storage Management (ASM) tool which is actually a separate, special Oracle instance (in the same way as RMAN the Recovery Manager). ASM enables the management of disparate disks which might be Network Attached Storage (NAS) or a Storage Area Network (SAN) or just a bunch of disks (JBOD). The advantages of ASM are that you don't have to create file systems on the disks, you can just use them raw, and ASM will create and manage the necessary files for you (in fact ASM created files won't be visible from the operating system at all). ASM will also provide load balancing by striping the files across all the disks that make up the disk group (which is the fundamental unit as far as the dba is concerned) and data integrity if another disk group is associated with the first as a mirror.
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The resources section has recommendations for further reading to enhance your knowledge of Oracle and contains links to information on OTN and other places. For more information on grid computing and Oracle 10g in particular see http://www.oracle.com/technology/tech/grid/collateral/idc_oracle10g.pdf and http://www.oracle.com/technology/tech/grid/collateral/GridTechWhitePaper_final.pdf
For more information about the new features of Oracle 10g see Robert Freeman's book "Oracle Database 10g New Features".
This book provides details on many of the new features that are important for both DBAs and developers. Click here to see more details on amazon.co.uk or here to see more details on amazon.com.
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