Debezium Blog

In today’s dynamic data environments, detecting and understanding data mutation patterns is critical for system reliability. In this blog post, we’ll explore how to use Debezium for comprehensive database activity logging and analysis in microservice architectures. We’ll delve into how Debezium captures row-level changes and streams them in real-time, enabling immediate visibility into database operations. By integrating with analytics tools, we’ll see how to build detailed activity dashboards that reveal the volume and nature of operations per table. These insights are invaluable for identifying unexpected patterns, such as a sudden drop in inserts caused by a new microservice deployment with a bug. You will learn how to set up Debezium, configure it for this specific use case, and utilize the generated data to create actionable dashboards.

It’s with immense joy and pleasure to announce the availability of Debezium 3.0.0.Final!

We released Debezium 2.0 nearly 2 years ago, and in that time, the platform has continued to grow, introducing sink-based connectors, new community-led connectors, and an extensive list of features and improvements to the core platform and connectors. With the community’s help, Debezium remains the de facto leader in CDC.

The 3.0 release marks another milestone for Debezium, one that we’re eager to share.

As I mentioned last week, we are in the homestretch for the next major release. We’re happy to announce the next candidate release, Debezium 3.0.0.CR2!. Let’s take a quick look at the changes and improvements in this new release…​

I am happy to announce the third maintenance release of the Debezium 2.7 release stream, 2.7.3.Final. This maintenance release focuses on addressing stability and regressions, with several improvements. Let’s dive into these changes…​