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Billy Newport, IBM's senior technical staff member and chief architect for WebSphere XD ObjectGrid, feels that conventional applications built in multiple tiers, such as data tiers and application tiers, have served the IT industry well.

However, the growth of data-intensive have both raised the implementation challenges and heightened the application benefits of data grid architecture.

“In some kinds of environments with the kind of work loads, and the way they have been increasing -- those application architectures have kind of been showing their age,” Newport said.

One solution includes transitioning to data grid-type architectures where “instead of pulling the application data from the database, the data is co-resident with the application,” Newport observed. 

Other Ways To Increased Performance

In the Middleware

Usually the role of middleware is to do all the hard stuff so customers can just work on their business logic, and middleware is a very important part of any data grade architecture.

“The Middleware handles things like fault tolerance, data replication, where the data gets placed on the grid, and other technical details,” Newport said.

Challenges Still Exist

Customers are getting tired of dealing with middleware that requires them to tell it how to do everything. They are saying that they want a much smarter middleware that can configure the data grid at runtime. And this middleware needs to figure how it's going to place the data on that grid, and how it's going to repair faults.

Large-Scale Applications Can Benefit Most

As an example, Newport points to the telco space where the requirements include extremely high availability and millisecond response times. “So when a customer wants to send a text message, it’s necessary to find out if they have text messaging enabled on their plan and to do that extremely quickly, with very high availability. And a data grid-type architecture to store what services are enabled for what customer is much more scalable a big box.”

If grids get larger, like 10,000 servers, that kind of architecture is absolutely essential because a leading requirement from customers is to lower the TCO. And, adds Newport, “They want to be able to have the same number of administrators with 1,000 servers, as with 2,000, 5,000 or 10,000. They need to keep the cost down. And that means you've got to automate as much as possible, to make a data grid economical to deploy.”

Industry-Specific Approaches

The telecom industry is one space with mixed architectures. It is now moving to voice-over IP. The voice sessions work well in a data grid architecture, where you route the calls to where the data is and we can maintain back-up copies for fail-over. The systems can be scaled up by adding more and more boxes. “Another important aspect for Telco is service provisioning. Where you want to know what given services a customer has when he makes a call. And you want to be able to look up the services very quickly. And you want to add and remove those services very quickly,” Newport explained.

The idea here is that as the telco company grows it can just add more boxes to the grid. The data grid middleware, like ObjectGrid from IBM will scale out the data across the new boxes. “So as you add more boxes, you're adding more CPUs, more network, and more memory. So that it's just going to become faster and faster and faster more servers are added,” Newport pointed out.

He concluded by noting that more information is available on the IBM extended deployment website. A trial version of ObjectGrid is available there for customers to download and to try out these features.

“The product addresses a lot of the problems in the middleware, and we're starting to see a lot of customers pick it up now, and move from the conventional architectures to these new data grid-type architectures,” Newport said.

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