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In this post, we introduce how to use .NET Kafka clients along with the Task Parallel Library to build a robust, high-throughput event streaming application...
Serverless stream processing with Apache Kafka® is a powerful yet often underutilized field. Microsoft’s Azure Functions, in combination with ksqlDB and Confluent’s sink connector, provide a powerful and easy-to-use set […]
It seems like now more than ever developers are surrounded by a sea of terminology—but what does it really all mean? Here, we will take some often heard terms—some considered […]
Kafka Streams is an abstraction over Apache Kafka® producers and consumers that lets you forget about low-level details and focus on processing your Kafka data. You could of course write […]
I’m proud to announce the release of Apache Kafka 2.7.0 on behalf of the Apache Kafka® community. The 2.7.0 release contains many new features and improvements. This blog post highlights […]
Apache Kafka® is an event streaming platform used by more than 30% of the Fortune 500 today. There are numerous features of Kafka that make it the de-facto standard for […]
Using a powerful, event-driven application can help you unlock insights contained in the event streams of your business. Before we get into the technology, let’s go over some questions you […]
With the release of Apache Kafka® 2.1.0, Kafka Streams introduced the processor topology optimization framework at the Kafka Streams DSL layer. This framework opens the door for various optimization techniques […]
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, […]