As we reviewed in our recent webinar with Roland Kuhn Reactive Streams 1.0.0 and Why You Should Care, the first version of the Reactive Streams specification is now live, and among other technologies from engineers at Netflix, Pivotal, Red Hat and Oracle, so are Typesafe's implementations of Akka Streams 1.0 and Slick 3.0.
Reactive Streams is an engineering collaboration between heavy hitters in the area of streaming data on the JVM. Reactive Streams Special Interest Group set out to standardize a common ground for achieving statically-typed, high-performance, low latency, asynchronous streams of data with built-in non-blocking back pressure—with the goal of creating a vibrant ecosystem of interoperating implementations, and with a vision of one day making it into a future version of Java.
In this webinar, Typesafe engineer Endre Varga looks deeper into Reactive Streams and demonstrates Akka Streams 1.0, Akka HTTP 1.0 and Slick 3.0 for harnessing the power of streaming with back-pressure in your system.
Akka (recent winner of “Most Innovative Open Source Tech in 2015”) is a toolkit for building message-driven applications. With Akka Streams 1.0, Akka has incorporated a graphical DSL for composing data streams, an execution model that decouples the stream’s staged computation—it’s “blueprint”—from its execution (allowing for actor-based, single-threaded and fully distributed and clustered execution), type safe stream composition, an implementation of the Reactive Streaming specification that enables back-pressure, and more than 20 predefined stream “processing stages” that provide common streaming transformations that developers can tap into (for splitting streams, transforming streams, merging streams, and more).
Slick is a relational database query and access library for Scala that enables loose-coupling, minimal configuration requirements and abstraction of the complexities of connecting with relational databases. With Slick 3.0, Slick now supports the Reactive Streams API for providing asynchronous stream processing with non-blocking back-pressure. Slick 3.0 also allows elegant mapping across multiple data types, static verification and type inference for embedded SQL statements, compile-time error discovery, and JDBC support for interoperability with all existing drivers.
With clusters of "fast data" streaming applications seeing increasing adoption in enterprises, Operations teams continue to struggle to effectively manage and deploy distributed applications (or microservices) running on dozens or even hundreds of clusters. As a way to help Operations cope with the demands of production Reactive applications, we've announced a four-part series of 30-min presentation plus Q/A called Reactive for DevOps, featuring Typesafe's recently released ConductR 1.0, a solution for managing Typesafe Reactive Platform-based applications using Play, Akka and Scala or Java across a cluster of machines.
In Part 1 - Using ConductR to manage and deploy Reactive applications to the [hybrid] cloud on July 14th at 9:00 PST / 16:00 UTC, we’ll see how ConductR manages this new wave of message-driven, elastic, resilient and responsive applications while complementing development workflow and existing configuration/management tools like Amazon EC2, Ansible, Docker, Mesos and others.
