Peter Harrington explains what you do with machine learning, and what are the building blocks for an application that uses machine learning from collected data to creating predictions for customers.
Matt Stine presents how combine Spring Boot, Spring Data, Spring Reactor, Spring XD, Hadoop and run them in the cloud.
Scott Frederick and Ramnivas Laddad introduce the Spring Cloud project, show how you can simplify configuring applications for cloud deployment, discuss its extensibility mechanism, and much more.
Ken Krueger and Rob Winch provide an overview of testing Spring Web applications.
Gunnar Hillert provides an overview of the current landscape and illustrate the choices the Spring XD team has made for its user interface.
Grant Shipley deploys an application to the cloud and then turns up the heat by leveraging the right mix of elasticity and auto-scaling.
John Hann presents the benefits of using RaveJS. Rave eliminates configuration, machinery, and complexity.
Brian Clozel, Rossen Stoyanchev discuss Spring MVC performance techniques aimed at keeping users happy.
Chris Beams shares his findings from over two years of research into bitcoin and related technologies.
Michael Plöd addresses the advanced usage of Spring's caching abstraction such as integrating a cache provider that is not integrated by the default Spring Package and overviews JCache. Demos.
Gunnar Hillert and Chris Schaefer examine various scalability options in order to improve the robustness and performance of the Spring Batch applications.
Michael Hunger and Lorenzo Speranzoni show how easy it is to get started with Spring Data Neo4j using Spring Boot.