Join Hugh McKee, Akka expert and Developer Advocate at Lightbend, on an illustrated journey that goes deep into how Akka works–from individual Akka actors to fully distributed clusters across multiple datacenters.

This technical white paper by Hugh McKee (@mckeeh3) and Oliver White (@theotown) of Lightbend will take you on an illustrated journey that goes deep into how Akka works

In this talk by Dean Wampler, PhD., VP of Fast Data Engineering at Lightbend, we’ll look at the criteria you need to consider when selecting technologies, plus the context and background to make good decisions when it comes to adopting streaming frameworks.

Reactive Streams expert and Lightbend Deputy CTO, Viktor Klang, provides a Reactive take on integration, where streaming is a first-class concept and Resilience and Responsiveness is achieved through flow control, back pressure, and feedback control.

This blog post brings together several resources into “get started kit” to learn what’s going on with streaming technologies like Akka Streams, Akka HTTP and Alpakka (all based on the Reactive Streams initiative) and connecting with your legacy integration points as a starting point.

In this webinar, Dr. Dean Wampler, VP of Fast Data Engineering at Lightbend, discusses the strengths and weaknesses of Kafka Streams and Akka Streams for particular design needs in data-centric microservices.

In this webinar, we are joined by O’Reilly author and Lightbend Principal Architect, Boris Lublinsky, as he discusses one of the hottest topics in software engineering today: serving machine learning models.

In this session by Konrad Malawski, author, speaker and Senior Akka Engineer at Lightbend, you will learn how to build these streaming ETL pipelines with Akka Streams, Alpakka and Apache Kafka, and why they matter to enterprises that are increasingly turning to streaming Fast Data applications.

In this technical webinar by Hugh McKee, O’Reilly author and Developer Advocate at Lightbend, we introduce Akka from A to Z, starting with a tour from the humble actor and finishing all the way at the clustered systems level.

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...

Today's Lightbend Podcast is with special guest Colin Breck, a longtime Akka user that has been creating some excellent technical content on his personal blog lately. Today we're here to talk about Akka Streams and Akka Actors, two very important modules for building resilient streaming, distributed systems with the overall Akka toolkit.

Watch this webinar with Dean Wampler, VP of Fast Data Engineering at Lightbend, Inc., to better equip you and your team with the context and background to make the right decision when it comes to adopting streaming frameworks.

In this webinar, Lightbend’s Senior Product Director, Craig Blitz reviews five early challenges enterprises face when building streaming and Fast Data systems, what to consider and how Lightbend aims to make these choices more straightforward with our upcoming Fast Data Platform.

In this webinar, Dustin Lyons, Engineering Manager at Credit Karma, discusses how his team migrated away from PHP and successfully implemented Akka Streams with Apache Kafka to ingest, process and route real-time events throughout their data ecosystem.

In this new white paper, we outline the functions a modern monitoring solution must perform in order to truly benefit from the advantages promised by Fast Data and streaming applications.

In this podcast with Patrik Nordwall, Akka Tech Lead at Lightbend, we review what’s new and improved in Akka 2.5 and what your teams should know in order to get the most out this release.

In this webinar for JVM Architects, Konrad Malawski explores the what and why of Reactive integrations, with examples featuring technologies like Akka Streams, Apache Kafka, and Alpakka, a new community project for building Streaming connectors that seeks to “back-pressurize” traditional Apache Camel endpoints.

In this talk for Architects and Dev Managers by Akara Sucharitakul, Principal MTS for Global Platform Frameworks at PayPal, we look at how back-pressure based on Akka Streams and Kafka is being used in PayPal's mission-critical production systems to handle very bursty workloads.

I recently had a chat with Raymond Roestenburg, co-author of Akka In Action, to ask him about how Akka brings the brilliance of the Actor Model, first developed over 40 years ago, to the mainstream embrace of the JVM, and namely Java 8.

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.