Get Started Free
November 23, 2021 | Episode 187

Explaining Stream Processing and Apache Kafka ft. Eugene Meidinger

  • Notes

Many of us find ourselves in the position of equipping others to use Apache Kafka® after we’ve gained an understanding of what Kafka is used for. But how do you communicate and teach others event streaming concepts effectively? As a Pluralsight instructor and business intelligence consultant, Eugene Meidinger shares tips for creating consumable training materials for conveying event streaming concepts to developers and IT administrators, who are trying to get on board with Kafka and stream processing. 

Eugene’s background as a database administrator (DBA) and immense knowledge of event streaming architecture and data processing shows as he reveals his learnings from years of working with Microsoft Power BI, Azure Event Hubs, data processing, and event streaming with ksqlDB and Kafka Streams. 

Eugene mentions the importance of understanding your audience, their pain points, and their questions, such as why was Kafka invented? Why does ksqlDB matter? It also helps to use metaphors where appropriate. For example, when explaining what is processing typology for Kafka Streams, Eugene uses the analogy of a highway where people are getting on a bus as the blocking operations, after the grace period, the bus will leave even without passengers, meaning after the window session, the processor will continue even without events. He also likes to inject a sense of humor in his training and keeps empathy in mind. 

Here is the structure that Eugene uses when building courses:

  1. The first module is usually fundamentals, which lays out the groundwork and the objectives of the course
  2. It's critical to repeat and summarize core concepts or major points; for example, a key capability of Kafka is the ability to decouple data in both network space and in time 
  3. Provide variety and different modalities that allow people to consume content through multiple avenues, such as screencasts, slides, and demos, wherever it makes sense


Continue Listening

Episode 188December 1, 2021 | 30 min

ksqlDB Fundamentals: How Apache Kafka, SQL, and ksqlDB Work Together ft. Simon Aubury

What is ksqlDB and how does Simon Aubury (Principal Data Engineer, Thoughtworks) use it to track down the plane that wakes his cat Snowy in the morning? Experienced in building real-time applications with ksqlDB since its genesis, Simon provides an introduction to ksqlDB by sharing some of his projects and use cases.

Episode 189December 7, 2021 | 33 min

Using Apache Kafka as Cloud-Native Data System ft. Gwen Shapira

What does cloud native mean, and what are some design considerations when implementing cloud-native data services? Gwen Shapira (Apache Kafka Committer and Principal Engineer II, Confluent) addresses these questions in today’s episode. She shares her learnings by discussing a series of technical papers published by her team, which explains what they’ve done to expand Kafka’s cloud-native capabilities on Confluent Cloud.

Episode 190December 14, 2021 | 28 min

Lessons Learned From Designing Serverless Apache Kafka ft. Prachetaa Raghavan

You might call building and operating Apache Kafka as a cloud-native data service synonymous with a serverless experience. Prachetaa Raghavan (Staff Software Developer I, Confluent) spends his days focused on this very thing. In this podcast, he shares his learnings from implementing a serverless architecture on Confluent Cloud using Kubernetes Operator.

Got questions?

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.

Email Us

Never miss an episode!

Confluent Cloud is a fully managed Apache Kafka service available on all three major clouds. Try it for free today.

Try it for free