In this Lightbend podcast, we sit down with special guest Jan Machacek, CTO of Cake Solutions, conference speaker, and author of the upcoming O’Reilly book, Reactive Systems Architecture: Designing And Implementing An Entire Distributed System.

With Akka Streams providing the "glue" between both microservices and the real-time analysis performed in the Fast Data space, we wanted to shine the spotlight on three industry leaders in their respective markets–PayPal, Credit Karma, and Flipkart–collectively worth well over $50 billion in market capitalization...

Last week, the Lightbend team volunteered at the SF Food Bank, and our VP of Engineering, Derek Henninger, was utterly surprised to find the experience to be an abject lesson in managing Reactive systems (in production!)

In this talk by noted hAkker Konrad Malawski, we'll disambiguate what streams are and what they aren't, taking a deeper look into Akka Streams (the implementation) and Reactive Streams (the standard).

Everyone wants to talk with Konrad Malawski on a 1:1 basis. I'm the lucky person who got 15 minutes of his time.

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. 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.  

In our most popular webinar to date with over 1500 registrants, Akka Team Lead and author Roland Kuhn presents the freshly released final specification for Reactive Streams 1.0.0 for the JVM. This work was done in collaboration with engineers representing Netflix, Red Hat, Pivotal, Oracle, Typesafe and others to define a standard for passing streams of data between threads in an asynchronous and non-blocking fashion. This is a common need in Reactive systems, in which the volume of streaming "live" data to process is not predetermined.