Organizations increasingly rely on streaming data sources not only to bring data into the enterprise but also to perform streaming analytics that accelerate the process of being able to get value from the data early in its lifecycle. As lakehouse architectures (including offerings from Cloudera and IBM) become the norm for data processing and building AI applications, a robust streaming service becomes a critical building block for modern data architectures.

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.

The Q3 Confluent Cloud Launch comes to you from Current 2023, where data streaming industry experts have come together to share insights into the future of data streaming and new areas of innovation. This year, we’re introducing Confluent Cloud’s fully managed service for Apache Flink®, improvements to Kora Engine, how AI and streaming work together, and much more.