Recap: This is the last part of our four chapters: It’s been a long time coming, but we’ve finally arrived at the fourth and final installment of our blog series. In this series, we’ve been peeling back the layers of Apache Kafka to get a deeper understanding of how best to interact with the cluster using producer and consumer clients. At a high level, a fetch request is comprised of two parts: Let’s dive in.

The Connect with Confluent (CwC) Technology Partner Program consistently expands the reach of Confluent’s data streaming platform across an ever-growing landscape of enterprise data systems. In this blog, you’ll meet the latest program entrants who have built fully managed integrations with Confluent and discover new ways to leverage real-time data across your business.

Raw data from IoT devices, like GPS trackers or electronic logging devices (ELDs), often lacks meaning on its own. However, if combined with information from other business systems, such as inventory management or customer relationship management (CRM), this data can now provide a richer, more complete picture for more effective decision-making. For example, combining GPS data with inventory levels can optimize logistics and delivery routes.

In today's data-driven world, staying ahead means acting on the most up-to-date information. That's where change data capture (CDC) comes in. CDC is a design pattern that tracks your database tables, capturing every row-level insert, update, and delete as it happens. This real-time monitoring allows downstream systems to react to changes instantly, without batch-based updates and resource-intensive full scans.

We are proud to announce the release of Apache Kafka 3.9.0. This is a major release, the final one in the 3.x line. This will also be the final major release to feature the deprecated Apache ZooKeeper mode. Starting in 4.0 and later, Kafka will always run without ZooKeeper.