SpringOne 2GX: October 15-18, 2012 – Final Schedule Available Now
Check out the final schedule of speakers and sessions for this year's event!
SpringOne 2GX is your opportunity to learn from development leads and published authors on the Spring, Groovy/Grails, Tomcat and Cloud technologies—speakers include this year's keynote Adrian Colyer, Juergen Hoeller, Chris Beams, Ben Alex, Chris Richardson, Ramnivas Laddad, Mark Pollack, and Mark Fisher. Sessions are geared to teach you information that is immediately applicable to developing business applications on or off premise, creating multi-device aware web applications, enabling your application for Big Data and NoSQL, and managing high performance infrastructures for your organization.
The second milestone release toward Spring Framework 3.2 is now available from the SpringSource repository. If you're not already familiar, see our quick tutorial on resolving these artifacts via Maven. The complete distribution zip is available as usual from the SpringSource community download site.
Be sure to catch up on the changes in 3.2 M1 if you haven't already.
Highlights from 3.2 M2 include:
Asynchronous @Controller method support now complete (blog post)
Many additional Spring MVC improvements, including plenty of REST support, e.g. content negotiation.
Spring TestContext improvements
Spring Expression Language (SpEL) improvements and fixes
Overall, 45 bugs fixed, 11 new features and 58 improvements implemented.
A major area of focus for 3.2 is ensuring that Spring Framework runs flawlessly on JDK7. M2 artifacts have been built, tested and published against JDK7 and we continue to test JDK6 compatibility in nightly builds as well. We encourage all Spring users on JDK7 to give M2 a spin in your development and test environments and provide as much feedback as possible prior to 3.2 GA. Thanks!
Webinars and Videos
Introducing Spring Hadoop
Part of the Spring Data umbrella, Spring for Apache Hadoop provides support for developing applications based on Apache Hadoop technologies by leveraging the capabilities of the Spring ecosystem. Whether one is writing stand-alone, vanilla MapReduce applications, interacting with data from multiple data stores across the enterprise, or coordinating a complex workflow of HDFS, Pig, or Hive jobs, or anything in between, Spring for Apache Hadoop stays true to the Spring philosophy offering a simplified programming model and addresses "accidental complexity" caused by the infrastructure. Spring for Apache Hadoop, provides a powerful tool in the developer arsenal for dealing with big data volumes.
November 8, 10:00 a.m. Pacific Standard (SF, GMT-08:00) - Register