Change Data Streaming Patterns in Distributed Systems

Microservices are one of the big trends in software engineering of the last few years; organising business functionality in several self-contained, loosely coupled services helps teams to work efficiently, make the most suitable technical decisions, and react quickly to new business requirements.

In this session, we'll discuss and showcase how open-source change data capture (CDC) with Debezium can help developers with typical challenges they often face when working on microservices. Come and join us to learn how to:

* Employ the outbox pattern for reliable, eventually consistent data exchange between microservices, without incurring unsafe dual writes or tight coupling
* Gradually extract microservices from existing monolithic applications, using CDC, the strangler fig pattern and Apache Flink
* Coordinate long-running business transactions across multiple services using CDC-based saga orchestration, ensuring such activity gets consistently applied or aborted by all participating services.

0:00 Introduction
1:45 Debezium — Log-based Change Data Capture
8:45 Outbox Pattern
14:44 Strangler Fig Pattern
26:47 Saga Pattern
38:40 Takeaways