Confluent Blog

Failures are inevitable in any system, and there are various options for mitigating them automatically. This is made possible by event-driven applications leveraging Apache Kafka® and built with fault tolerance

One of the most highly requested enhancements to ksqlDB is here! Apache Kafka® messages may contain data in message keys as well as message values. Until now, ksqlDB could only

How do you process IoT data, change data capture (CDC) data, or streaming data from sensors, applications, and sources in real time? Apache Kafka® and Apache Spark® are widely adopted

Since I first started using Apache Kafka® eight years ago, I went from being a student who had just heard about event streaming to contributing to the transformational, company-wide event

We launched a transformation initiative three years ago that transitioned SEI Investments from a monolithic database-oriented architecture to a containerized services platform with an event-driven architecture based on Confluent Platform.

Organizations define standards and policies around the usage of data to ensure the following: Data quality: Data streams follow the defined data standards as represented in schemas Data evolvability: Schemas

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

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

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