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October 08, 2008
The Grid-Cloud Connection (Pt. I): Compare and Contrast
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Grid computing. Cloud computing. Are there any IT paradigms that have garnered more hype and more skepticism without most people even knowing what they mean? Probably not, but maybe that is because the terms themselves have no real meanings to most IT consumers, just connotations.
And connotations can be scary. Burned to some degree by the existing confusion surrounding grid computing, many grid vendors have drastically cut the term from their marketing strategies. Learning from what might be perceived as mistakes, these vendors are not so quick to latch onto cloud computing. However, many of their new directions could easily fall under the cloud umbrella, and those in the know readily acknowledge that grid technologies underlie the cloud.
So, what's a middleware vendor to do?
First, Compare
Within the Data Center Business Division at Univa UD, messaging around grid computing has been all but eliminated as the division attempts to build traction for its Reliance datacenter orchestration product (from which the company also has nixed the Grid MP middleware component). What division general manager Alex Brown calls the "traffic cop or brains of the operation," Reliance combines application awareness, closed-loop orchestration and SLA automation to deliver optimal application performance, and Univa UD customers and prospects view it as a key part of their cloud or utility infrastructures.
Although no one is talking about grid computing, Univa UD's Gordon Jackson says the company's experiences with grid and large-scale distributing processing management feed directly into its success with Reliance, especially as it relates to resource management and distribution. Jackson is the technical director of the Data Center Business Division former virtualization evangelist at DataSynapse.
Brown agrees that a real cloud-like solution requires a significant understanding of grid concepts. "However, because people thought of grid as so specialized, it got a lot of baggage," he explains. "So while a lot of the core technology is very relevant, a lot of the terminology and a lot of the old processes are not. In fact, they hinder the adoption of the technology for cloud."
Ivan Casanova, vice president of product marketing at the aforementioned DataSynapse sees a connection, too, calling grid computing the starting point for cloud computing -- "a proof point for shared and dynamic infrastructure." A big part of cloud computing is the ability to scale based on demand, and grid computing middleware is a great method for doing so, he says. (Casanova also notes that SOA is the architectural model for cloud computing, and DataSynapse has customers deploying SOAs and using the company's GridServer product to scale those services.)
On the data grid front, Oracle's Cameron Purdy, vice president of Fusion Middleware, says, "Data grid technology ... is almost essential in any transactional processing or other data-intensive system that would be deployed into a cloud environment. I can't imagine how you would run a data-intensive application across any number of servers in that type of environment without the ability to share and coordinate access to and operate and react to changes and events occurring to that information."
According to Platform Computing Chairman and CEO Songnian Zhou, his customers definitely see the grid-cloud connection as they move from HPC-focused enterprise grids to general-purpose, often virtualized, shared-services platforms. "They may not call it cloud, they may not call it on-demand datacenter, but they clearly are doing it," he says.
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