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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 Kafkaยฎ is a powerful yet often underutilized field. Microsoftโs Azure Functions, in combination with ksqlDB and Confluentโs sink connector, provide a powerful and easy-to-use set [โฆ]
It seems like now more than ever developers are surrounded by a sea of terminologyโbut what does it really all mean? Here, we will take some often heard termsโsome considered [โฆ]
Kafka Streams is an abstraction over Apache Kafkaยฎ producers and consumers that lets you forget about low-level details and focus on processing your Kafka data. You could of course write [โฆ]
Iโm proud to announce the release of Apache Kafka 2.7.0 on behalf of the Apache Kafkaยฎ community. The 2.7.0 release contains many new features and improvements. This blog post highlights [โฆ]
Apache Kafkaยฎ 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 [โฆ]
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, letโs go over some questions you [โฆ]
With the release of Apache Kafkaยฎ 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 [โฆ]
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, [โฆ]