In the first three parts of our Inside Flink blog series, we discussed the benefits of stream processing, explored why developers are choosing Apache Flink® for a variety of stream processing use cases, and took a deep dive into Flink's SQL API. In this post, we'll focus on how we’ve re-architected Flink as a cloud-native service on Confluent Cloud. However, before we get into the specifics, there is exciting news to share.
Navigating the intricacies of Apache Kafka just got a lot more intuitive. With Lenses 5.3 we bring you peace of mind, regardless of where you are in your Kafka journey. Our newest release is all about smoothing out the bumps, and making sure you're equipped to handle Kafka's challenges with confidence. Here's a sprinkle of what's in store, ahead of our big 6.0 release later this year.
We like to reduce the most mundane, complex and time-consuming work associated with managing a Kafka platform. One such task is backing up topic data. With a growing reliance on Kafka for various workloads, having a solid backup strategy is not just a nice-to-have, but a necessity. If you haven’t backed up your Kafka and you live in fear of disaster striking, worry no more.
An effective data platform thrives on solid data integration, and for Kafka, S3 data flows are paramount. Data engineers often grapple with diverse data requests related to S3. Enter Lenses. By partnering with major enterprises, we've levelled up our S3 connector, making it the market's leading choice. We've also incorporated it into our Lenses 5.3 release, boosting Kafka topic backup/restore.
