Practical AppFabric Caching and Session Management
Would you like to learn about high availability, scalability and distributed cache management using Microsoft platform without getting all cloudy? Windows Server AppFabric is a set of application services focused on improving the performance and management of Web, Composite, and Enterprise applications. AppFabric provides a highly scalable in-memory application cache for all types of data. With the caching features of AppFabric you get Scalable in-memory, distributed cache for any serializable data, Seamless integration with ASP.NET, High availability and dynamic scale-out of cluster nodes, Optional local cache with eviction policies and cache change subscriptions and notifications.
In this demo-centric session, we will cover end-to-end implementation of a web solution using AppFabric for caching and session management. Intended audience include web developers who want to build high performance applications leveraging web programming techniques (e.g.ASP.NET, MVC, RESTful services, etc) and enterprise developers who create service oriented middle tier applications using .NET.
About the Author
Adnan Masood works as a web architect / technical lead for a financial institution where he develops SOA based middle-tier architectures, distributed systems, and web-applications using Microsoft technologies. He is a Microsoft Certified Trainer holding several technical certifications, including MCPD (Enterprise Developer), MCSD .NET, and SCJP-II. Adnan is attributed and published in print media and on the Web; he is technical editor for upcoming "Microsoft Windows Server AppFabric Cookbook" and also taught Windows Communication Foundation (WCF) courses at the University of California at San Diego.
Adnan regularly presents at local code camps and user groups. He is actively involved in the .NET community as cofounder and president of the of San Gabriel Valley .NET Developers group. Adnan holds a Masters degree in Computer Science; he is currently a doctoral student working towards PhD in Machine Learning; specifically interestingness measures in outliers using Bayesian Belief Networks. He also holds systems architecture certification from MIT and SOA Smarts certification from CMU.