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What does it means for our programs to be asynchronous and back pressured and why is it so important for scalable services?
During this talk, you will explore the following:
Thread per request vs asynchronous services
What back pressure is and how to do it all the way down to the network layer
How to achieve all of this with Akka HTTP and Akka Streams
How it compares to other tools for asynchronous programming e.g. CompletableFutures, Observables
Time permitting, you will also discover a demo on a networked application sending back pressure through the application layer, through TCP and into the client application.
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Building Scalable, Back Pressured Services with Akka
Christopher is a Senior Engineer at Lightbend. He is currently on the core Akka team responsible for developing Akka (https://akka.io/), Akka Http, Akka Streams, Reactive Kafka and Alpakka (https://github.com/akka/alpakka). He has previously built trading systems, online television platforms and worked extensively with Apache Cassandra. Likes: Scala, Java, the JVM, Akka, distributed databases, XP, TDD, Pairing. Dislikes: Untested software and code ownership.