Today, we invariably operate in ecosystems: groups of applications and services which together work towards some higher level business goal. When we make these systems event-driven they come with a […]
We are pleased to invite Tom Underhill to join us as a guest blogger. Tom is Head of R&D at Rittman Mead, a data and analytics company who specialise in […]
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, […]
KSQL is the streaming SQL engine for Apache Kafka®. It lets you do sophisticated stream processing on Kafka topics, easily, using a simple and interactive SQL interface. In this short […]
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 […]
Update: KSQL is now available as a component of the Confluent Platform. I’m really excited to announce KSQL, a streaming SQL engine for Apache Kafka®. KSQL lowers the entry bar to […]
