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Streaming Data with Kafka and Microservices

YOW! 2018 Brisbane

When we think of modern data processing, we often think of batch-oriented ecosystems like Hadoop, including processing engines like Spark. However, the sooner we can extract useful information from our data, the better, which is driving an evolution towards stream processing or “fast data”. Many of the legacy tools, including Spark, provide various levels of support for stream processing, but deeper architectural changes are emerging.

Dean Wampler

Head of Developer Relations

United States

Dean Wampler is an expert in streaming data systems, focusing on applications of ML/AI. He is head of evangelism at, which is focused on distributed Python 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 popular open source tools. Dean is the author or co-author of three O’Reilly books on Scala, Functional Programming, and Hive. He contributes to several open source projects and he co-organizes and speaks at many technology conferences and Chicago-based user groups. Dean has a Ph.D. in Physics from the University of Washington.