Systems | Development | Analytics | API | Testing

Confluent CEO Jay Kreps takes the stage alongside industry leaders at data streaming’s biggest event. Together, they’ll show why free-flowing, real-time data has become the key to unleashing the full potential of intelligent systems across every business. From live demos to real-world use cases to industry-changing product announcements, this year’s keynote is essential viewing for anyone looking to maximize the potential of their AI. Which is pretty much everyone. Don’t miss it.

Wix rewired 85% of its data volume onto Confluent Freight Clusters—and the result was lower costs and elastic scalability that handles Black Friday–scale spikes without manual intervention. Josef Goldstein explains why it felt like a magical solution.

Wix processes 40 billion events a day across use cases that range from minutes to milliseconds. Josef Goldstein explains why the entire upstream architecture has to be built around your most latency-sensitive lane—or none of it works.

Real-time data and AI are converging—and companies that have already solved the data pipeline problem are pulling ahead fast. Wix processes over 40 billion interactions every day across hundreds of millions of websites, and the architecture behind that scale didn't happen by accident. It was built, lane by lane, around the principle that your upstream data must be at least as fast as your fastest use case.

KCP automatically generates custom Terraform modules, allowing you to provision your entire target infrastructure and networking in just a few minutes for Kafka migrations.

Multi-agent systems aren't new architecture—they're microservices evolved. Varun Jasti of AWS explains why Apache Kafka is the natural backbone for agent-to-agent communication at scale.

Most companies aren't trying to build AI—they're trying to use it. Varun Jasti of AWS breaks down why accessible data, not model sophistication, determines whether AI creates real business value.

Varun Jasti of AWS explains why real-time data—not better models—is the true unlock for enterprise AI. Most enterprises don't need to build AI models from scratch—they need to put AI to work. That requires a data foundation that is real-time, reliable, and ready to serve intelligent systems at scale.

The average grocery store has 65 to 80% inventory accuracy. One in 10 products is out of stock at any moment. For an industry operating on razor-thin margins and competing against digital-native challengers, that data gap is existential. In this episode, Kevin Johnson, CEO of Focal Systems, sits down with Joseph to explore how his team is using computer vision, data streaming, and stateful stream processing to close that gap at scale.

What happens when a security intelligence company decides that data contracts aren't optional, they're the foundation? For SecurityScorecard, that decision changed everything: how teams share data, how pipelines are built, and how quickly a new engineer can ship production-grade work on day one.