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March 17, 2021 | Episode 148

Event-Driven Architecture - Common Mistakes and Valuable Lessons ft. Simon Aubury

  • Transcript
  • Notes

Event-driven architecture has taken on numerous meanings over the years—from event notification to event-carried state transfer, to event sourcing, and CQRS. Why has event-driven programming become so popular, and why is it such a topic of interest? 

For the first time, Simon Aubury (Principal Data Engineer, ThoughtWorks) joins Tim Berglund on the Streaming Audio podcast to tell all, including his own experiences adopting event-driven technologies and common blunders when working in this area.

Simon admits that he’s made some mistakes and learned some valuable lessons that can benefit others. Among these are accidentally building a message bus, the idea that messages are not events, realizing that getting too fixated on the size of a microservice is the wrong problem, the importance of understanding events and boundaries, defining choreography vs. orchestration, and dealing with passive-aggressive events.

This brings Simon to where he is today, as he advocates for Apache Kafka® as a foundation for building a scalable, event-driven architecture and data-intensive applications. 

Continue Listening

Episode 149March 24, 2021 | 50 min

Smooth Scaling and Uninterrupted Processing with Apache Kafka ft. Sophie Blee-Goldman

Availability in Kafka Streams is hard, especially in the face of any changes. Apache Kafka Committer and Kafka Streams developer Sophie Blee-Goldman shares about how to solve the stop-the-world rebalance and scaling out problem in Kafka Streams using probing rebalances.

Episode 150March 31, 2021 | 30 min

Building Real-Time Data Pipelines with Microsoft Azure, Databricks, and Confluent

Processing data in real time is a process, as some might say. Angela Chu (Solution Architect, Databricks) and Caio Moreno (Senior Cloud Solution Architect, Microsoft) explain how to integrate Azure, Databricks, and Confluent to build real-time data pipelines that enable you to ingest data, perform analytics, and extract insights from data at hand.

Episode 151April 7, 2021 | 24 min

Resurrecting In-Sync Replicas with Automatic Observer Promotion ft. Anna McDonald

As most developers and architects know, data always needs to be accessible no matter what happens outside of the system. This week, Tim Berglund virtually sits down with Anna McDonald (Principal Customer Success Technical Architect, Confluent) to discuss how Automatic Observer Promotion (AOP) can help solve the Apache Kafka 2.5 datacenter dilemma, a feature now available in Confluent Platform 6.1 and above.

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If there's something you want to know about Apache Kafka, Confluent or event streaming, please send us an email with your question and we'll hope to answer it on the next episode of Ask Confluent.

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