Confluent Blog

Building data pipelines isn’t always straightforward. The gap between the shiny “hello world” examples of demos and the gritty reality of messy data and imperfect formats is sometimes all too

Software engineering memes are in vogue, and nothing is more fashionable than joking about how complicated distributed systems can be. Despite the ribbing, many people adopt them. Why? Distributed systems

This blog post presents the use cases and architectures of REST APIs and Confluent REST Proxy, and explores a new management API and improved integrations into Confluent Server and Confluent

My own sense of the passage of time in 2020 is no sure guide, but honestly it seems like Kafka Summit just happened—yet here we are, deep into planning for

It’s almost KubeCon! Let’s talk about the state of cloud-native Apache Kafka® and other distributed systems on Kubernetes. Over the last decade, our industry has seen the rise of container

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

The rise of the cloud introduced a focus on rapid iteration and agility that is founded on specialization. If you are an application developer, you know your applications better than

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

Today, the ability to capture and harness the value of data in real time is critical for businesses to remain competitive in a data-driven world. Apache Kafka®, a scalable, open-source,