Systems | Development | Analytics | API | Testing

How to Protect PII in Apache Kafka With Schema Registry and Data Contracts

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.

Visualizing BigQuery geospatial data in Colab

Geospatial data is a powerful tool for gaining insights into everything from customer behavior to environmental patterns. BigQuery allows you to store and analyze this location data using standard SQL, and bringing that data into a Colab notebook gives you the flexibility to combine BigQuery's power with popular Python visualization libraries. This approach is perfect for ad-hoc or iterative analysis. In this video, we'll give you an overview of these capabilities and walk through a demo of how you can analyze and visualize your geospatial data.

Hitachi Vantara's Virtual Storage Platform One Now Available in the Microsoft Azure Marketplace

Expanded cloud compatibility and built-in capabilities like compression, provisioning and replication can help enterprises simplify operations and reduce storage costs by up to 40%. Microsoft Azure customers worldwide now gain access to Hitachi Vantara Virtual Storage Platform One to take advantage of the scalability, reliability and agility of Azure to drive application development and shape business strategies.

Moesif + Gloo Gateway: Deep API Analytics and Observability at the Edge

Solo.io Gloo Gateway gives teams a reliable way to secure, route, and monitor API traffic in real time. With its high-performance Envoy core and Kubernetes-native design, it meets the demands of distributed applications and modern service architectures. However, performance metrics alone don’t reveal how developers engage with your APIs or why adoption stalls.

Unleash Real-Time Agentic AI: Introducing Streaming Agents on Confluent Cloud

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.

New in Confluent Cloud: Unleashing Cost-Effective Streaming for Any Workload

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.

AI for UX design: 5 best practices for product designers

AI is no longer a fringe experiment: it’s a mainstream mandate. But with that shift comes a new kind of pressure: to act quickly, to appear modern, to bolt on something “intelligent” before someone else does. For many teams, this leads to reactive choices. Features get prioritized because they sound impressive, not because they solve a real user problem. Familiar interfaces get copied instead of questioned.

Demo: Streaming Agents automate competitive pricing in real time

Streaming Agents enable you to build, deploy, and orchestrate event-driven agents natively on Apache Flink and Apache Kafka. By unifying stream processing and agentic AI workflows, they leverage fresh context to continuously monitor and act on what’s happening in the business. In this demo, Brenner Heintz, Staff Technical Marketing Manager at Confluent, shows how to build agents that automate real-time competitive price matching on sales orders.