When most people think of Data Grids, they think of distributed caching with a bunch of fancy vendor specific features. Ok, Data Grids have proven themselves to improve application performance and scalability but what if we "pimped" the idea of distributing data management and handling data change events with remote method invocation, groovy, spring and/or CEP engines? What would that mean for application performance, scalability and resilience? What new or existing classes of application could we simply scale out?

In this technical talk Brian reveals several "pimped" architectural approaches that have enabled many global investment banks, their trading systems, exchanges and online transaction processing sites to deliver much needed application performance, scalability and resilience (systems that are responsible for multi-billion and trillion dollar portfolios) over that of traditional master/worker approaches on Oracle Coherence.

Following these "pimped" patterns Brian mixes things up a little and introduces the concepts of Groovy Data Grids (agile dynamic development with Groovy on a Grids) and Unstoppable Spring (embedding Spring applications into resilient Data Grids) to increase developer productivity together with application performance, scalability and reliability.