Kora Engine, Data Quality Rules and more within our Q2'23 Launch | Register for demo
The Apache Kafka community was crazy-busy last month. We released a technical preview of Kafka Streams and then voted on a release plan for Kafka 0.10.0. We accelerated the discussion of few key proposals in order to make the release, rolled out two release candidates, and then decided to put the release on hold in order to get few more changes in.
That’s all for now! Got a newsworthy item? Let us know. If you are interested in contributing to Apache Kafka, check out the contributor guide to help you get started.
Companies are looking to optimize cloud and tech spend, and being incredibly thoughtful about which priorities get assigned precious engineering and operations resources. “Build vs. Buy” is being taken seriously again. And if we’re honest, this probably makes sense. There is a lot to optimize.
Operating Kafka at scale can consume your cloud spend and engineering time. And operating everyday tasks like scaling or deploying new clusters can be complex and require dedicated engineers. This post focuses on how Confluent Cloud is 1) Resource Efficient, 2) Fully Managed, and 3) Complete.