As with nearly every IT trend, including service-oriented architectures and Web services, just because we're all talking about
cloud computer science doesn't intend we're talking about the same thing.
I recently joined a LinkedIn/Google grouping on cloud computing, a member of which posted what should have got been an guiltless question:
Is there a difference between cloud computer science and what we cognize as power system computing? I was ready with my ain answer, but overnight
about a twelve responses had already flooded in, creating an e-mail concatenation that offered some interesting niceties on the terminology.
[ Learn more than about the cloud computer science tendency in "" and "." ]
I trust this doesn't acquire me kicked out of this group, but Iodine idea it might be interesting to reproduce some of these as food
for thought. In the involvements of privacy, I'm not publishing anyone's names, and I've edited some of the definitions for the
interest of lucidity and length. Here are the top five:
1. "Vendors, as always, film over the existent definitions of new terms. In my sentiment (and the sentiment of others), cloud computing
isn't the same as public utility computing, which isn't the same as power system computing:
"Grid computer science generally mentions to resource pooled environments for running play calculate occupations (like mental image processing) rather than
long running procedures (such as a Web land site or e-mail server).
"Utility computer science generally mentions to resource-pooled environments for hosting long running play processes, and be givens to be focused
on meeting service degrees with the optimal amount of resources necessary to make so.
"Cloud computer science mentions (for many) to a assortment of services available over the Internet that present calculate functionality
on the service provider's substructure (e.g. Google Apps or Amazon EC2 or Salesforce.com). A cloud computer science environment
may actually be hosted on either a power system or public utility computer science environment, but that doesn't substance to a service user."
2. "Cloud computer science = Power System computing. The workload is sent to the IT substructure that dwells of dispatching Masters and
working slave nodes. The Masters control resource statistical distributions to the workload (how many slaves run the parallelized workload). This is crystalline to the client, who only sees that workload have been dispatched to the cloud/grid and consequences are returned
to it. The slaves may or may not be practical hosts.
"Cloud computer science = Software-as-Service. This is the Google apps model, where apps are located 'in the cloud,' i.e. somewhere
in the Web.
"Cloud computer science = Platform-as-Service. This is the Amazon EC2 et aluminum theoretical account where an external physical thing keeps the IT infrastructure
(masters/slaves) and the client purchases time/resources on this infrastructure. This is 'in the cloud' in so much that it is across
the Web, outside of the organisation that is leasing clip off it. Continued1 | | »