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March 8, 2021 | Episode 147

The Human Side of Apache Kafka and Microservices ft. SPOUD

  • Transcript
  • Notes

Many industries depend on real-time data, requiring a range of solutions that Apache Kafka® can help solve. Samuel Benz (CTO) and Patrick Bönzli (Product Owner) explain how their company, SPOUD, has fully embraced Kafka for data delivery, which has proven to be successful for SPOUD since 2016 across various industries and use cases. 

The four Kafka use cases that Sam and Patrick see most often are microservices, event processing, event sourcing/the data lake, and integration architecture. But implementing streaming software for each of these areas is not without its challenges. It’s easy to become frustrated by trivial problems that arise when integrating Kafka into the enterprise, because it’s not just about technology but also people and how they react to a new technology that they are not yet familiar with. Should enterprises be scared of Kafka? Why can it be hard to adopt Kafka? How do you drive Kafka adoption internally? All good questions.

When adopting Kafka into a new data service, there will be challenges from a data sharing perspective, but with the right architecture, the possibilities are endless. Kafka enables collaboration on previously siloed data in a controlled and layered way. Sam and Patrick’s goal today is to educate others on Kafka and show what success looks like from a data-driven point of view. It’s not always easy, but in the end, event streaming is more than worth it. 

Continue Listening

Episode 148March 17, 2021 | 42 min

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

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? Simon Aubury (Principal Data Engineer, ThoughtWorks) is here to tell all, including his own experiences adopting event-driven technologies and common blunders when working in this area.

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.

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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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