Confluent Blog

It has been seven years since we first set out to create the distributed streaming platform we know now as Apache Kafka®. Born initially as a highly scalable messaging system, […]

This guest blog post is the second in a series about the use of Apache Kafka’s Streams API by Zalando, Europe’s largest online fashion retailer. See Ranking Websites in Real-time […]

This article is by Hunter Kelly, Technical Architect at Zalando. Hunter enjoys using technology, and in particular machine learning, to solve difficult problems. He’s a graduate of the University of […]

Kafka Streams makes it easy to write scalable, fault-tolerant, and real-time production apps and microservices. This post builds upon a previous post that covered scalable machine learning with Apache Kafka, […]

At Pinterest, we use Kafka Streams API to provide inflight spend data to thousands of ads servers in mere seconds. Our ads engineering team works hard to ensure we’re providing […]

Scalable Machine Learning in Production with Apache Kafka® Intelligent real time applications are a game changer in any industry. Machine learning and its sub-topic, deep learning, are gaining momentum because […]

This post was originally published at the Codecentric blog with a focus on “old” join semantics in Apache Kafka versions 0.10.0 and 0.10.1. Version 0.10.0 of the popular distributed streaming […]

At The New York Times we have a number of different systems that are used for producing content. We have several Content Management Systems, and we use third-party data and […]

When you build microservices using Apache Kafka®, the log can be used as more than just a communication protocol. It can be used to store events: messaging that remembers. This […]

This article discusses the use of Apache Kafka’s Streams API for sending out alerts to customers of Rabobank. Rabobank is based in the Netherlands with over 900 locations worldwide, 48,000 employees, […]