Sep 23–26, 2019
Dean Wampler

Dean Wampler
Vice President, Fast Data Engineering, Lightbend

Website | @deanwampler

Dean Wampler, Ph.D., is VP of Fast Data Engineering at Lightbend. He leads the Lightbend Fast Data Platform team, a scalable, distributed stream data processing stack using Kubernetes, Spark, Flink, Kafka, and Akka, with machine learning and management tools. Dean is the author of Fast Data Architectures for Streaming Applications, Programming Scala, Second Edition and Functional Programming for Java Developers and the coauthor of Programming Hive, all from O’Reilly Media. He is a contributor to several open source projects, a frequent Strata speaker, and the co-organizer of several conferences around the world and several user groups in Chicago. Dean yells at clouds on Twitter, @deanwampler.


1:30pm5:00pm Tuesday, September 24, 2019
Location: 1E 15/16
Boris Lublinsky (Lightbend), Dean Wampler (Lightbend)
Boris Lublinsky and Dean Wampler examine ML use in streaming data pipelines, how to do periodic model retraining, and low-latency scoring in live streams. Learn about Kafka as the data backplane, the pros and cons of microservices versus systems like Spark and Flink, tips for TensorFlow and SparkML, performance considerations, metadata tracking, and more. Read more.
4:35pm5:15pm Thursday, September 26, 2019
Location: 1E 10/11
Dean Wampler (Lightbend)
Join me for a discussion of the following problems and their solutions: 1. How (and why) to integrate ML into production streaming data pipelines, to serve results quickly? 2. How to bridge data science and production environments, with different tools, techniques, and requirements? 3. How to build reliable and scalable, long-running services? 4. How to update ML models without downtime? Read more.

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