Taming and Composing High Performance Stream-Oriented Processing

Real time applications are dominating the industry! Data is the main ingredient in Internet-based, social media and Internet of things (IoT) systems, which generate continuous streams of events used for real time analytics. This poses a tremendous challenge due to the massive volume of data collected and processed. These event-based Real-time analysis systems can easily process millions of messages per second through new generation solutions by simply defining small flows and then combining them together to create processing graphs. In this talk, will cover the concepts behind high-performance streamed-oriented big data processing systems. We will explore messaging queue systems like Kafka and Akka Streams which let developers define their process workflows at a higher level to define a graph system enabling a high throughput. You will learn how to integrate high performance stream message queues and how to define process workflows in C# and F#.

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About the presenter:

Riccardo is a .NET seasoned software engineer, senior software architect and Microsoft MVP who is passionate about functional programming. He organized the Open F# conference in San Francisco, runs the Washington DC F# User Group, and has authored the books: Functional Concurrency in .NET (http://a.co/cVthlZs) and Highly Scalable Systems in .NET (http://a.co/5h6KdeL).

Presenter GitHub Account: @rikace (https://github.com/rikace)
Presenter Blog: http://www.rickyterrell.com
Presenter Twitter: @TRikace (https://twitter.com/TRikace)