June 29, 2020 | Episode 107

Open Source Workflow Automation with Apache Kafka ft. Bernd Ruecker

  • Notes

What started out as a consulting company, Camunda eventually turned into a developer-friendly, open source vendor that now focuses on workflow automation. 

Bernd Ruecker, a co-founder and the chief technologist at Camunda, talks through the company's journey, how he ended up in open source, and all things automation, including how it differs from business process management and the issue of diagrams. 

Bernd also dives into dead letter topics in Apache Kafka®, software interacting with software, orchestration tension, and best practices for approaching challenges that pop up along the way. This episode will take you through a thorough introduction of Camunda Cloud, a cloud-native workflow engine, as well as Camunda’s Kafka connector. 

Continue Listening

Episode 108July 8, 2020 | 46 min

Benchmarking Apache Kafka Latency at the 99th Percentile ft. Anna Povzner

The five components of latency are produce time, publish time, commit time, catch-up time, and fetch time. When consumer pulling adds to latency, Anna Povzner shares some best practices to keep in mind for how to think about partitioning in conjunction with latency. She also discusses client configuration in the cloud, interesting problems she's helped solve for customers, and her top two tips for debugging latency.

Episode 109July 15, 2020 | 54 min

Fault Tolerance and High Availability in Kafka Streams and ksqlDB ft. Matthias J. Sax

Apache Kafka® Committer Matthias J. Sax explains fault tolerance, high-availability stream processing, and Kafka Streams. He explains the differences between changelogging and checkpointing, as well as making changes in Kafka versus hot standbys, explaining what qualifies nodes as a hot standby, why Kafka Streams doesn’t do watermarking, and finally, why Kafka Streams is a library and not infrastructure.

Episode 110July 20, 2020 | 41 min

Modernizing Inventory Management Technology ft. Sina Sojoodi and Rohit Kelapure

Inventory management systems are crucial for reducing real-time inventory data drift, improving customer experience, and minimizing out-of-stock events. Kafka provides seamless inventory tracking at scale, saving billions of dollars in the supply chain, making modernized data architectures more important to retailers now more than ever. In this episode, we’ll discuss how Kafka enables stateful event streaming on a cloud-native platform for application and architecture modernization, leveraging Spring Boot, Kafka Streams, and Apache Cassandra.

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