Confluent Blog

This blog post is the third in a four-part series that discusses a few new Confluent Control Center features that are introduced with Confluent Platform 6.2.0. It focuses on inspecting

I previously showed how to install and set up Apache Kafka® on Windows in minutes by using the Windows Subsystem for Linux 2 (WSL 2). From there, it’s only a

Consuming messages in parallel is what Apache Kafka® is all about, so you may well wonder, why would we want anything else? It turns out that, in practice, there are

In the article Should You Put Several Event Types in the Same Kafka Topic?, Martin Kleppmann discusses when to combine several event types in the same topic and introduces new

The rise of IoT devices means that we have to collect, process, and analyze orders of magnitude more data than ever before. As sensors and devices become ever more ubiquitous,

Part 1 of this series discussed the basic elements of an event streaming platform: events, streams, and tables. We also introduced the stream-table duality and learned why it is a

For event streaming application developers, it is important to continuously update the streaming pipeline based on the need for changes in the individual applications in the pipeline. It is also

Stream processing is a data processing technology used to collect, store, and manage continuous streams of data as it’s produced or received. Stream processing (also known as event streaming or

Our new cat, Snowy, is waking early. She is startled by the noise of jets flying over our house. Can I determine which plane is upsetting her by utilizing Apache

If you adopt a streaming platform such as Apache Kafka, one of the most important questions to answer is: what topics are you going to use? In particular, if you