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We are getting some of the best data-specialists from Craft Conference to give a few talks here at our meetups right before they speak at the conference!

This is a joint event with the Budapest Big Data Meetup group

Building Event Driven Systems with Apache Kafka & Kafka Streams

Event Driven Systems come in many shapes and sizes from tiny functions that dip into an event stream right through to heavy, stateful streaming services. This talk examines the fundamentals of distributed logs and stateful stream processing, contrasting the event driven approach with REST/RPC-based methods. Then we’ll walk through a number of patterns for putting such systems together, evolving a typical monolith into a rich, globally deployed, event-driven ecosystem.

*Ben Stopford*
Ben is a technologist working in the Office of the CTO at Confluent Inc (the company behind Apache Kafka) where he’s worked on a wide range of projects, from implementing the latest version of Kafka’s replication protocol through to writing a book on Event Driven Systems. Before Confluent Ben led the design and build of a company-wide data service in a large financial services firm. His earlier career spanned projects at Thoughtworks and UK-based enterprise companies. He is the author of the book “Designing Event Driven Systems”, O’Reilly, 2018. Find out more at

Talk Title Will be announced soon.
Abstract will be announced soon.

* Chris Fregly *
Chris Fregly is Founder and Research Engineer at PipelineAI, a Real-Time Machine Learning and Artificial Intelligence Startup based in San Francisco.

He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly Training and Video Series titled, "High Performance TensorFlow in Production."

Previously, Chris was a Distributed Systems Engineer at Netflix, a Data Solutions Engineer at Databricks, and a Founding Member and Principal Engineer at the IBM Spark Technology Center in San Francisco.

More talks will be announced soon.