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In today’s cost-conscious climate, every line item on your cloud bill is under the microscope. That makes now the ideal time to rethink your data streaming strategy. For many teams, using a hyperscaler-hosted Apache Kafka service feels like the easy choice—one vendor, one bill, no additional contracts, and minimal setup. It makes sense early on, especially for small-scale projects or basic use cases. But, as your Kafka usage grows and becomes mission-critical, that simplicity comes at a cost.

The Apache Kafka community is proud to announce the release of Apache Kafka 4.1.0. This blog post highlights the many new features and improvements included in this release. For a full list of changes, be sure to check the release notes. Queues for Kafka (KIP-932) is now in preview. It's still not ready for production, but you can start evaluating and testing it. See the preview release notes for more details. This release also introduces a new Streams Rebalance Protocol (KIP-1071) in early access.

Based in Delhi, India, Vineet Singh has worked as a Senior Software Engineer at Confluent for the past three years, and he has contributed to various parts of Confluent’s core data streaming engine. Now he’s part of the team that makes Apache Kafka cloud-native, serverless, and able to power robust and scalable solutions for Confluent Cloud customers. Learn more about Vineet’s experience and growth at Confluent and how his team and environment have set him up for success.

Data streaming equips modern organizations to rapidly ingest and understand new information and use it to solve real-world problems at scale. For some of these real-time insights—critical operational cues that demand a timely response—delivering that information directly to your team’s inbox is the best way to act on it.

A data contract is a formal agreement between an upstream component and a downstream component on the structure and semantics of data that’s in motion. In a previous post, I showed how Confluent Schema Registry supports data contracts. By combining data contracts and encryption on streaming workloads, you can shift left the responsibility of data consistency, quality, and security to the producer, allowing the consumer to depend on a trustworthy stream of data.

Streaming at scale just got a lot more powerful and cost-effective. Our Q3 Confluent Cloud launch is packed with innovations to help you do more with less: reduce cloud networking costs while maintaining your security posture, scale effortlessly with boosted connection limits, and build production-ready agentic artificial intelligence (AI) applications with seamless tool integrations.

As AI models become commoditized, the conversation is shifting from building smarter models to building data infrastructure that turns models into real business value. Enterprises are accelerating their adoption of agentic AI—systems that don’t just predict but plan, decide, and act autonomously—across their software and operations.

Taking advantage of Confluent’s pre-built connectors means you’re able to build integration pipelines without having to write, test, and maintain integration code. And with our fully managed connectors on Confluent Cloud, you can connect to any source or sink system with zero ops or infrastructure management and with cost-efficiency. This year, we've been hard at work making the benefits of fully managed connectors a reality for more of our customers.