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.
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.
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.
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. Bernd also dives into dead letter topics in 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 the Komodo Cloud as well as Camunda’s Kafka connector.
We've all been affected by COVID-19 in one way or another, resulting in big changes in workplace functionality, productivity, and even our relationships within the Apache Kafka and Confluent communities as meetings and events have needed to turn virtual. Ale Murray shares interesting trends, changes in community metrics, and what we’ve done to adapt as a response.
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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