Debezium Blog
Last week’s announcement of Quarkus sparked a great amount of interest in the Java community: crafted from the best of breed Java libraries and standards, it allows to build Kubernetes-native applications based on GraalVM & OpenJDK HotSpot. In this blog post we are going to demonstrate how a Quarkus-based microservice can consume Debezium’s data change events via Apache Kafka. For that purpose, we’ll see what it takes to convert the shipment microservice from our recent post about the outbox pattern into Quarkus-based service.
The Debezium team is happy to announce the release of Debezium 0.9.2.Final!
This is mostly a bug-fix release and a drop-in replacement for earlier Debezium 0.9.x versions. Overall, 18 issues were resolved.
A couple of fixes relate to the Debezium Postgres connector:
As part of their business logic, microservices often do not only have to update their own local data store, but they also need to notify other services about data changes that happened. The outbox pattern describes an approach for letting services execute these two tasks in a safe and consistent manner; it provides source services with instant "read your own writes" semantics, while offering reliable, eventually consistent data exchange across service boundaries.
Last week I had the pleasure to do a webinar on change data streaming patterns for microservices with the fabulous Burr Sutter at DevNation Live.
The recording of that 30 min session is available on YouTube now. It also contains a demo that shows how to set-up a data streaming pipeline with Debezium and Apache Kafka, running on OpenShift. The demo begins at 12 min 40 into the recording.
Enjoy!
Quickly following up to last week’s release of Debezium 0.9, it’s my pleasure today to announce the release of Debezium 0.9.1.Final!
This release fixes a couple of bugs which were reported after the 0.9 release. Most importantly, there are two fixes to the new Debezium connector for SQL Server, which deal with correct handling of LSNs after connector restarts (DBZ-1128, DBZ-1131). The connector also uses more reasonable defaults for the selectMethod and fetchSize options of the SQL Server JDBC driver (DBZ-1065), which can help to significantly increase through-put and reduce memory consumption of the connector.
