Confluent Blog

Extensive out-of-the-box functionality, a large user community, and up-to-date, cloud-native features make Spring and its libraries a strong option for anchoring your Apache Kafka® and Confluent Cloud based microservices architecture.

Today, an organization’s strategic objective is to deliver innovations for a connected life and to improve the quality of life worldwide. With connected devices comes data, and with data comes

Self-managing a distributed system like Apache Kafka®, along with building and operating Kafka connectors, is complex and resource intensive. It requires significant Kafka skills and expertise in the development and

Microservice architectures continue to grow within engineering organizations as teams strive to increase development velocity. Microservices promote the idea of modularity as a first-class citizen in a distributed architecture, enabling

Data is the currency of competitive advantage in today’s digital age. All organizations struggle with their data due to the sheer variety of data types and ways that it can

Asynchronous boundaries. Frameworks. Configuring frameworks. Apache Kafka®. All of these share one thing in common: complexity in testing. Now imagine them combined—it gets much harder. This is the final blog

Have you ever had to write a program that needed to handle any data payload that could be thrown at you? If so, did you always have to update the

Event modeling has always been a pain point in organizations. From figuring out the standard format of your schemas, processing said data models effectively, and finally testing before you deploy

You know the fundamentals of Apache Kafka®. You are a Spring Boot developer working with Apache Kafka or Confluent Cloud. You have chosen Spring for Apache Kafka for your integration.

tl;dr When a client wants to send or receive a message from Apache Kafka®, there are two types of connection that must succeed: The initial connection to a broker (the