Apache Flink 1.13 introduced a couple of important changes in the area of backpressure monitoring and performance analysis of Flink Jobs. This blog post aims to introduce those changes and explain how to use them.
Apache Flink 1.13 introduced Reactive Mode, a big step forward in Flink's ability to dynamically adjust to changing workloads, reducing resource utilization and overall costs. This blog post showcases how to use this new feature on Kubernetes, including some lessons learned.
The Apache Flink community is excited to announce the release of Flink 1.13.0! Around 200 contributors worked on over 1,000 issues to bring significant improvements to usability and observability as well as new features that improve the elasticity of Flink's Application-style deployments.