Mark Reinhold keynotes on Java 9’s impact and features –platform module system, security, performance, maintenance-, and speculates on what might come after that, including the Java VM.
Dave McCrory talks about what is Data Gravity, how it affects performance and portability and why these effects are amplified when there are larger volumes of data.
Emily Green is taking a look at how SoundCloud uses Cassandra. She describes a couple of Cassandra instances, from the point of view of the products and functionality they support.
Roy Rapoport shares some of the lessons Netflix learned building a monitoring system, the challenges, pitfalls and opportunities encountered along the way.
Francesco Cesarini illustrates how the Erlang way of thinking about problems leads to scalable and fault-tolerant designs, describing 3 ways of clustering Erlang nodes within the server side domain.
John Wilkes shares lessons learned managing clusters at the scale of Google.
Lari Hotari discusses how to optimize Grails' performance to get full benefits from it.
Martin Thompson focuses on the design of Aeron, what they learned trying to achieve consistent performance, and challenges performing UDP messaging in a lock-free and wait-free manner.
The panelists discuss Java performance topics, bringing their specific experiences to bear.
Mike Barker shares lessons learned at LMAX Exchange: starting from a clean domain model is imperative and understanding the trade-offs between performance and safety/generality/functionality.
James Richardson, Nat Pryce discuss some of the challenges faced using Neo4J for interactive analysis of large data imports (80K nodes, 150k relationships) and how they overcame them.
John Davies shows a Spring work-flow consuming 7.4kB XML messages, binding them to 25kB Java but storing them in just 450 bytes each, 10 million derivative contracts in-memory on a laptop.
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