Confluent Blog

The Kafka Streams API boasts a number of capabilities that make it well suited for maintaining the global state of a distributed system. At Imperva, we took advantage of Kafka

Using Jaeger tracing, I’ve been able to answer an important question that nearly every Apache Kafka® project that I’ve worked on posed: how is data flowing through my distributed system?

Have you ever realized that, according to the latest FBI report, more than 80% of all crimes are property crimes, such as burglaries? And that the FBI clearance figures indicate

Building off part 1 where we discussed an event streaming architecture that we implemented for a customer using Apache Kafka, KSQL, and Kafka Streams, and part 2 where we discussed

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

At TokenAnalyst, we are building the core infrastructure to integrate, clean, and analyze blockchain data. Data on a blockchain is also known as on-chain data. We offer both historical and

Following part 1 and part 2 of the Spring for Apache Kafka Deep Dive blog series, here in part 3 we will discuss another project from the Spring team: Spring

Red Pill Analytics was recently engaged by a Fortune 500 e-commerce and wholesale company that is transforming the way they manage inventory. Traditionally, this company has used only a few

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

So you’ve convinced your friends and stakeholders about the benefits of event-driven systems. You have successfully piloted a few services backed by Apache Kafka®, and it is now supporting business-critical