Gwen Shapira and Dominik Benz talk Kafka

Join us for an Apache Kafka meetup on October 8th from 6:30pm, hosted by inovex. The address, agenda and speaker information can be found below. See you there!

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Agenda:
6:30pm: Doors open
6:30pm - 7:00pm: Networking, Pizza and Drinks
7:00pm - 7:45pm: Presentation #1: Dominik Benz, inovex
7:45pm - 8:30pm: Presentation #2: Gwen Shapira, Confluent
8:30pm - 9:00pm: Additional Q&A and Networking

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First Talk
Speaker:
Dominik Benz

Bio:
Dominik Benz works as Head of Machine Learning Engineering at inovex GmbH. His research background lies in the field of Data Mining from the Social Web, where he obtained a PhD at the Chair of Knowledge and Data Engineering, University of Kassel. Since 2012, he was involved at inovex in engineering and architecting analytic data platforms in various projects for major companies. He is most experienced in tools around the Hadoop ecosystem, and has hands-on experience in productionizing analytical applications, with a special focus on streaming and realtime approaches.

Title:
Down the event-driven road: Experiences of integrating streaming into analytic data platforms

Abstract:
The requirements of many modern data platforms develop along two directions: (1) Low latency, i.e. the shift from batch-oriented to event-driven processes, which facilitate much more timely and reactive insights; and (2) complex analytics, i.e. the ability to efficiently apply analytic functions or models to the incoming data streams. However, many companies don't start from scratch, and already have well-established data infrastructure and processes with various degrees of affinity and compatibility to these novel paradigms. Based on extensive experience of building data platforms with customers, we describe in this talk some key challenges and aspects of introducing streaming-based approaches in real-world productive environments. These include e.g. integrating existing batch-oriented data sources and APIs, checking consistency when using event sourcing to exchange data, and building realtime analytical visualizations. For all cases, architectural options are discussed, and the final solution is explained, including technologies like Apache Nifi, Airflow, Phoenix, Druid and the Confluent Platform. We close the talk by describing non-technical aspects like building up an event-driven mindset among analysts.

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Second Talk
Speaker:
Gwen Shapira

Bio:
Gwen Shapira is a principal data architect at Confluent, where she helps customers achieve success with their Apache Kafka implementation. She has 15 years of experience working with code and customers to build scalable data architectures, integrating relational and big data technologies. Gwen currently specializes in building real-time reliable data-processing pipelines using Apache Kafka. Gwen is an Oracle Ace Director, the coauthor of Hadoop Application Architectures, and a frequent presenter at industry conferences. She is also a committer on Apache Kafka and Apache Sqoop. When Gwen isn’t coding or building data pipelines, you can find her pedaling her bike, exploring the roads and trails of California and beyond.

Title:
How much Kafka do you need? The art and science of capacity planning

Abstract:
No matter if you are new to Apache Kafka or an experienced expert, capacity planning questions seem to show up at every step of the adoption journey. Architects and developers need to know how many topics, how many partitions, what are the right message sizes and how to plan to scale. Operations teams need to know how many brokers, which hardware and even how many clusters are required. In a short talk that will attempt to cover lots of ground, we’ll go over the basics of planning Kafka deployments.

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If you would like to speak or host our next event please let us know! community@confluent.io