Systems | Development | Analytics | API | Testing

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.

Bringing real-time capabilities to your product or software-as-a-service (SaaS) is no longer a nice-to-have; it’s a competitive necessity. Whether you're building a real-time payment platform, a patient monitoring system, or any product where instant data processing fuels great user experiences and artificial intelligence (AI)-driven innovation, Apache Kafka data streaming is likely at the core.

Data is in motion, and it’s moving faster than ever. For developers and data architects building modern real-time data platforms, the ability to get data from anywhere and analyze it instantly is a superpower. That’s why we’re excited to announce a major step forward in this journey: the fully managed sink connector for Clickhouse, now generally available on Confluent Cloud.

Playlists for every mood and occasion. Media recommendations grouped by the most niche theme from your watch history. Sophisticated ad algorithms that optimize pay-per-click ads for the customer experience. Whether you call them digital-native, disruptors, or just tech giants, the likes of Spotify, Netflix, and Amazon have long made uncannily personal experiences a key part of their differentiation or business models.

This is the second post in our series exploring the architectural innovations that make Confluent Cloud more cost-effective at scale. Building on our previous post about the operational complexities of Apache Kafka and our cloud-native architecture's solutions, we'll now dive into how we solved a core challenge for any data streaming workload: high cloud networking costs.