Helena Edelson addresses new architectures emerging for large scale streaming analytics based on Spark, Mesos, Akka, Cassandra and Kafka (SMACK) or Apache Flink or GearPump.
Viktor Klang explores fast data streaming using Akka Streams - how to design robust transformation pipelines with built-in flow control able to take advantage of multicore and go over networks.
Christopher Meiklejohn looks at applying two techniques together, deterministic data flow programming and conflict-free replicated data types, to create highly available and fault-tolerant systems.
Kristoffer Dyrkorn presents the experiences gained by the Norwegian Public Roads Administration in building a new infrastructure for road traffic measurements.
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.