One of the most common scaling problems in any high-throughput system occurs when a producer of data is able to emit events far faster than they can be consumed, eventually resulting in the system "tipping over" as a result of buffer overflows or pegged CPUs.

The goal behind the Reactive Streams initiative (http://www.reactive-streams.org/) is to help provide a means of non-blocking back-pressuring these producer-consumer relationships across service and process boundaries.

In this talk, we're going to learn how to use Akka.Streams, an implementation of the Reactive Streams specification built on top of Akka.NET, to take advantage of this design inside our own applications. We'll learn about how to design a fully connected Akka.Streams Graph, how to use built-in graph stages, how to implement our own custom graph stages, and some best practices and use cases for working with Akka.Streams in production.