Speaker: Tim Berglund

Senior Director of Developer Experience @Confluent

Tim is a teacher, author, and technology leader with Confluent, where he serves as the Senior Director of Developer Experience. He can frequently be found at speaking at conferences in the United States and all over the world. He is the co-presenter of various O’Reilly training videos on topics ranging from Git to Distributed Systems, and is the author of Gradle Beyond the Basics. He tweets as @tlberglund, blogs very occasionally at http://timberglund.com, and lives in Littleton, CO, USA with the wife of his youth and their youngest child, the other two having mostly grown up.

Find Tim Berglund at

@tlberglund
LinkedIn

Workshop : Agile Streams With Apache Kafka

Location : Liberty, 8fl.
Day of week : Monday
Duration : 9:00am - 4:00pm

Apache Kafka is a de facto standard streaming data processing platform, being widely deployed as a messaging system, and having a robust data integration framework (Kafka Connect) and stream processing API (Kafka Streams) to meet the needs that commonly attend real-time message processing. In 2017, Confluent open sourced KSQL. A declarative, SQL-like stream processing language that lets you define stream processing applications easily. This allows rapid development of streaming applications and—more importantly—rapid iteration and improvement.

In this workshop we will explore best practices and architectural patterns of modern data integration with Apache Kafka and its ecosystem. This is one of the main use cases of Apache Kafka, and the use of Kafka allows integrating data systems and microservices in completely new ways. This leads to more performant, flexible, and robust data integrations. The workshop will combine theoretical discussion of best practices, lessons learned, and architecture patterns that we found useful, together with hands-on experimentation with a variety of projects from the Apache Kafka Ecosystem.

What you'll learn:

  • Apache Kafka basics
  • Data modeling for Apache Kafka
  • Use of Schemas and Schema Registry
  • Importance of Stream-Table duality for data integration
  • Stream enrichment and Stream-Join patterns
  • Rapid development of stream processing with KSQL
  • Power and Flexibility of Kafka’s Streams APIs
  • Hipster Stream Processing
  • Best practices for taking data pipelines to production
  • Common mistakes to avoid

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Schedule