Carl Hewitt keynotes on the Actor Model and ActorScript, providing examples of using them for large-scale datacenters and IoT.
Paul Butcher discusses difficulties with concurrency and some of the alternatives that help with this, focusing on Actors and how they help deal with threads and locks and make code clearer.
Jamie Allen reviews some of the actor patterns as implemented in Akka and Scala.
Jamie Allen describes three patterns using Akka actors: handling a lack of guaranteed delivery, distributing tasks to worker actors and implementing distributed workers in an Akka cluster.
Joshua Suereth designs a scalable distributed search service with Akka and Scala using actors, and covering practical aspects of how to scale out with Akka’s clustering API.
Josh Suereth designs a distributed search service with Akka using Actors, covering: message passing, designing topologies, handling failure, service overload detection and tracking user sessions.
Stuart Halloway discusses concurrency features in Clojure: atoms, agents, futures, delays, promises, STM, and dynamic vars.
Jamie Allen explains some of the terminology encountered by Scala developers and not only: OO features, pattern matching, functional programming, actors, futures, tuples, implicits, type theory, etc.
Jonas Bonér explains solving scalability issues, including adaptive automatic load-balancing, cluster rebalancing, replication and partitioning, with Akka 2.
Steve Vinoski believes that actor-oriented languages such as Erlang are better prepared for the challenges of the future: cloud, multicore, high availability and fault tolerance.
Dierk König introduces GPars, Groovy’s library for concurrent programming, explaining a simpler and less error-prone way to use fork/join, map/reduce, actors, and dataflow in Java and Groovy.