Engineering the Future of Software
Feb 25–26, 2018: Training
Feb 26–28, 2018: Tutorials & Conference
New York, NY
Dean Wampler

Dean Wampler
Head of Developer Relations, Anyscale

Website | @deanwampler

Dean Wampler is an expert in streaming data systems, focusing on applications of machine learning and artificial intelligence (ML/AI). He’s head of developer relations at Anyscale, which is developing Ray for distributed Python, primarily for ML/AI. Previously, he was an engineering VP at Lightbend, where he led the development of Lightbend CloudFlow, an integrated system for building and running streaming data applications with Akka Streams, Apache Spark, Apache Flink, and Apache Kafka. Dean is the author of Fast Data Architectures for Streaming Applications, Programming Scala, and Functional Programming for Java Developers, and he’s the coauthor of Programming Hive, all from O’Reilly. He’s a contributor to several open source projects. A frequent conference speaker and tutorial teacher, he’s also the co-organizer of several conferences around the world and several user groups in Chicago. He earned his PhD in physics from the University of Washington.

Sessions

1:30pm–5:00pm Monday, February 26, 2018
Building streaming applications with Kafka
Application architecture
 Location: Regent
Secondary topics:  Case Study, Hands-on
Dean Wampler (Anyscale), Boris Lublinsky (Lightbend)
Average rating: **...
(2.33, 3 ratings)
Dean Wampler and Boris Lublinsky walk you through building several streaming microservices applications based on Kafka using Akka Streams and Kafka Streams for data processing. You'll explore the strengths and weaknesses of each tool, helping you choose the best tools for your needs, and contrast them with Spark Streaming and Flink, so you can determine when to choose them instead. Read more.
10:15am–10:45am Tuesday, February 27, 2018
Meet the Experts with Dean Wampler
Location: Table B
Dean Wampler (Anyscale)
Come talk with Dean about anything from trends in streaming data and microservice architectures and how they are converging to specific tools like Spark, Flink, Akka Streams, Kafka Streams, and data backplanes like Kafka. Read more.