Eleanor McHugh discusses writing virtual machines using hardware emulation, including code snippets in Go and C.
Mitchell Hashimoto takes a look at VMs, which solution architectures worked there, and discusses why these architectures are no longer adequate and what are the solutions in a containerized world.
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.
Axel Fontaine looks at what Immutable Infrastructure is and how it affects scaling, logging, sessions, configuration, service discovery and more.
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.
Tony Printezis presents how services are deployed and monitored at Twitter, the benefits of using a custom-built JVM, and the challenges of the use of the JVM in an environment like Twitter.
Ian Bull introduces Node4J and explores the performance characteristics and highlights the tools that help one develop, debug and deploy Node.JS applications running directly on the JVM.
Ashley Puls explains what happens to bytecode inside the JVM. It begins with an overview of the Just In Time (JIT) compiler and discusses JIT optimizations such as method inlining and loop unrolling.