Stéphane Maldini explores how the new Reactor design, structure and features can progressively help developers go Reactive.
Sebastien Deleuze and Stephane Maldini talk about developing Reactive applications using Reactor Core 2.5, and using Flux and Mono types with various exercises.
Monica Beckwith discusses the performance introduced by adaptive compilation in the OpenJDK Hotspot VM, focusing on the internals of OpenJDK 8, the reference implementation for Java SE8.
Alex Blewitt presents how HotSpot represents Java objects in memory, how bytecode is compiled into native code to gain the fastest execution time, and how data structures have changed over time.
Rob Valk introduces the JSON-API 1.0 spec, taking a look at JVM ecosystem support for the standard with the katharsis.io library and its integration with the Mule runtime.
Brian Goetz looks at some of the challenges and lessons of steering Java through major evolutionary changes, and a sneak peek at where the Java platform is headed.
Simon Ritter explains the impact Jigsaw will have on developers in terms of building their applications, as well as helping them to understand how things like encapsulation will change in JDK 9.
Alex Blewitt introduces modularity in general, and the choices that OSGi made in bringing modularization to the JVM. He also looks ahead and asks how OSGi and Jigsaw will evolve in the future.
John Oliver takes a look at both G1 and Shenandoah, explaining how they work, what are their limitations, providing tuning advice. He also looks at recent and future changes to garbage collection.
Monica Beckwith talks about G1 pause (young and mixed) composition, G1's remembered sets and collection set and G1's concurrent marking algorithm, providing performance tuning advice.
Mark Price explores the life cycle of Java code, and how the JVM evolves the runtime representation of code during program execution, providing tips to make sure Java code runs fast.
Chris Newland discusses performance-boosting techniques used by the JVM’s JIT and introduces JITWatch, a tool helping to get the best JVM performance for a code.