De-siloing microservice data with change capture and Apache Flink
We all know and love our micro service architectures. As every service has ownership of its own code base and data, we can iterate on each service separately. However, sometimes we need to combine data from different services. In a monolith, it could be a single SQL join. In most micro service systems, this is not easy to do efficiently. This aspect tends to be overlooked when discussing micro services: Try as we might to decouple systems into sensible domains, sooner or later there will be a business requirement that does goes right across those boundaries and we will need to find a way to reunite this data. We will look at Debezium, a change capture solution by Red Hat, and Apache Flink, a stream processing framework, and of course a little bit of Kafka.
Cloud Architect at Quin.md
Developer and architect with 20+ years in Java. Stream processing and reactive enthusiast.