Workshop: Build Event-Driven Microservices with Apache Kafka (Afternoon Section)

Location: Seacliff A

Duration: 1:00pm - 4:00pm

Day of week: Thursday

Level: Intermediate

Key Takeaways

  • What is Apache Kafka and when do you want to use it

  • Using Kafka producer and consumer

  • Using Kafka Streams and KSQL

  • Stream/Table duality

  • Common design patterns for event-driven and async microservices

  • Common problems and tradeoffs involved

Prerequisites

  • Should be fairly familiar with either Java or Scala
  • Should be able to run Docker containers and bash scripts (either Linux or MacOS recommended)

No Kafka experience necessary.

Apache Kafka is a de facto standard streaming data processing platform and is being widely deployed as a persistent messaging system in event-driven architectures. 

In this workshop, we’ll explore several of the design patterns commonly used in event-driven microservices architectures, discuss some of the challenges and trade-offs that are made when designing event-driven systems and put all these ideas to practice as we’ll build an event-driven order processing application.

Speaker: Gwen Shapira

Principal Data Architect @Confluent, PMC Member @Kafka, & Committer Apache Sqoop

Gwen is a principal data architect at Confluent helping customers to achieve success with their Apache Kafka implementation. She has 15 years of experience working with code and customers to build scalable data architectures, integrating microservices, relational and big data technologies. She currently specializes in building real-time reliable data processing pipelines using Apache Kafka. Gwen is an author of “Kafka - the Definitive Guide”, "Hadoop Application Architectures", and a frequent presenter at industry conferences. Gwen is also a committer on the Apache Kafka and Apache Sqoop projects. When Gwen isn't coding or building data pipelines, you can find her pedaling on her bike exploring the roads and trails of California, and beyond.

Find Gwen Shapira at

Tracks

Monday, 5 November

Tuesday, 6 November

Wednesday, 7 November

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