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