Confluent Blog

Updating a fundamental paradigm in your React app can be as easy as search and replace, or at other times, as difficult as convincing your entire frontend engineering to buy

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.

When building API-driven web applications, there is one key metric that engineering teams should minimize: the blocked factor. The blocked factor measures how much time developers spend in the following

This tutorial describes how to set up a sample Spring Boot application in Pivotal Application Service (PAS), which consumes and produces events to an Apache Kafka® cluster running in Pivotal

TL;DR Following on from How to Work with Apache Kafka in Your Spring Boot Application, which shows how to get started with Spring Boot and Apache Kafka®, here I will

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