Life happens as a continuous flow of events (a stream). Ted Dunning and Ellen Friedman describe new designs for streaming data architecture that help you get real-time insights and greatly improve the ...

The Apache Kafka distributed streaming platform features an architecture that – ironically, given the name – provides application messaging that is markedly clearer and less Kafkaesque when compared ...

In the previous article, we gained an understanding of the main Kafka components and how Kafka consumers work. Now, we’ll see how these contribute to the ability of Kafka to provide extreme ...

Events offer a Goldilocks-style approach in which real-time APIs can be used as the foundation for applications which is flexible yet performant; loosely-coupled yet efficient. Apache Kafka offers a ...

Ensuring that distributed systems like Apache Kafka are resilient is crucial to withstanding disruptions, adapting to changing conditions and maintaining essential functions. Those who implement these ...

Five key innovations that increased the performance, availability, and cost-efficiency of the engine at the heart of Confluent’s managed Apache Kafka service. When we set out to rebuild the engine at ...

Shiny new objects are easy to find in the big data space. So when the industry’s attention shifted towards processing streams of data in real time–as opposed to batch-style processing that was popular ...

The first step to sizing or scaling Kafka for optimal cost and performance is understanding how the data streaming platform uses resources. Here’s a primer. Teams implementing Apache Kafka, or ...