Recently I worked on a Coherence data grid and then to set up a SOA cluster on Weblogic. That made me wonder what is the difference between Grid and Clusters. So couple of goggling and there are many links that explain it. However here it is in my own understanding.
Grids: Grid computing would be something to do with to optimize the resource usage like CPU, memory or IO. When we built a Coherence Data grid, It’s basically a cache server to cache the data so that we can avoid the expensive database trip. So we reduce the IO and make the application faster. And these cache servers can be started many in number across machines, they all talk to each other using multicast communication. Which is actually the same technology used in the Weblogic clusters to keep the managed servers in sync. Similarly other grids optimize CPU usage, which would otherwise be unused and so waste of money to keep and maintain them. Server Virtualization is a Grid solution.
Clusters: on the other hand basically provide scalability, so that the application can support more a more user requests, also with high availability due to failover support in cluster aware managed servers. Clusters are an extension to distributed computing and it lets scale the application dynamically meaning add more managed servers anytime you have more demand. Similar failover and dynamically adding more servers is supported in Coherence Grids as well. Coherence Cache servers also partitions the data across multiple servers thus providing more scalability.
Interesting thread on weblogic clusters here
Interetsting discussion on scalability here
So basically the underline technology like multicast communication could be same, and the results like performance (response time), scalability (throughput) could be same, however Grids and Clusters differ in the basic goals they work on. It would not be wrong to say Grids will help you scale up while Clusters will help to Scale out.
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