Elasticity is a key component in reactive systems and James Ward navigates the different characteristics of different implementations of this concept: Akka, Scala, RxJava, and more.
Viktor Klang shows the purpose and power of streaming concurrent data processing with safe bounds using back pressure, discussing Akka streams and dynamic runtime as well as compile time optimizations
Jan Machacek demos creating and using reactive APIs in Scala with Spray and Akka.
Roland Kuhn introduces the guiding principles behind Reactive Streams’ design and along with examples using its actor-based implementation in Akka.
Duncan DeVore reviews the challenges of concurrent programming on the JVM and explores Akka, a toolkit and runtime for building highly concurrent, distributed applications on the JVM.
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.
Jan Machacek introduces writing Scala applications to Spring developers, demoing using Akka actors with mix-in composition, higher-order functions, higher-order kinds, and REST API.
Jonas Bonér explains solving scalability issues, including adaptive automatic load-balancing, cluster rebalancing, replication and partitioning, with Akka 2.
Josh Suereth presents the new features available in Akka 2.0: clustered actors, including stateless and stateful ones, replication and the Cluster API.