Jonas Bonér explains the Akka project and the types of actors it offers as well as its transactional features. Also: a preview of how Akka 2.0 changes the management of (remote) actors.
Orion Henry explains what make Heroku's PaaS tick, in particular the new extensible Cedar stack as well as Doozer, the implementation of the Paxos algorithm created at Heroku.
Terracotta creator Ari Zilka talks about about the RAM is the new disk and argues for scaling up before scaling out, comparing the architectural approaches of lots of VMs with small heaps vs. a few JVMs with very large heaps. Ari introduces BigMemory, a Java add-on to Enterprise Ehcache, which allows app designs with huge amounts of memory accessible in-process, with minimal garbage collection.
Aaron Patterson talks about performance in Ruby and Rails, some of the challenges Rails and Rack pose for the Ruby GC, and much more.
Justin Sheehy and Damien Katz discuss Riak and CouchDB, the strengths and trade-offs of different approaches to NoSQL, and why both databases are written in Erlang.
Kostis Sagons talks about how type checking can help with a dynamic language like Erlang and how static analysis tools like Dialyzer or automated refactoring tools like Tidier help keep code clean.
Ville Tuulos talks about Disco, the Map/Reduce framework for Python and Erlang, real-world data mining with Python, the advantages of Erlang for distributed and fault tolerant software, and more.
Gregory Collins talks about Snap, a high performance web framework for Haskell, where it fits in the web framework spectrum, the Iteratee I/O model, Haskell performance and much more.
Francesco Cesarini and Simon Thompson discuss how Erlang's design allows fault tolerance and resilience, modular error handling, details of the actor model implementation and distributed programming.
Rob Pike discusses Google Go: OOP programming without classes, Go interfaces, Concurrency with Goroutines and Channels, and the Go features that help keep GC pauses short.
Cliff Click discusses the Pauseless GC algorithm and how Azul's Zing implements it on plain x86 CPUs. Also: what keeps dynamic languages slow on the JVM, invokedynamic, concurrency and much more.
In this interview Gil Tene dives deep into the history of Azul Systems and its commitment to deliver robust, scalable Java systems. He tells of the origins of the company and its early Vega hardware. Tene also talk about the new Zing elastic runtime platform for Java apps. And he speaks on the Managed Runtime Initiative Azul launched. He also talks on Pauseless GC and elastic memory.