Conduktor

You are running a central service for Apache Kafka? Or you are planning to create one within your company? Then this event is for you! We are bringing together Kafka Teams in Frankfurt - onsite and virtually! So make sure you don't miss this key event on October 22 and register now!

You are running a central service for Apache Kafka? Or you are planning to create one within your company? Then this event is for you! We are bringing together Kafka Teams in Munich - onsite and virtually! So make sure you don't miss this key event on October 20 and register now!

We're helping more and more teams rethink how they protect data in Kafka. For years, security and governance have relied on documentation, CI checks, Terraform modules, and PR approvals. Those are all valuable, but they don't stop someone from connecting directly to Kafka and bypassing those controls. That's why our customers are moving policy enforcement into the Kafka data path, where masking, encryption, schema validation, and access controls are applied automatically to every request. As AI agents become Kafka clients, we're seeing this shift become even more important.

Some headlines make you pause. Meta's $250B data center in Louisiana was one of them for me this week. The most important name in that project isn't Zuckerberg. It's Blue Owl. An asset manager owns 80% of the financing behind the campus now. The signal? Wall Street is now structuring AI infrastructure the way it structures real estate. Think about what that means. When engineers own infrastructure, utilization is a dashboard metric. When financiers own it, utilization is a covenant. Meta is even reportedly exploring renting spare capacity to outside customers, because financed capacity is not allowed to sit idle. And this discipline won't stay at the top. Once the largest infrastructure projects on earth are financed against efficiency, that expectation reaches every company running its own data platforms. At Conduktor, we see the downstream version of this every day. Five years ago, nobody asked what their streaming infrastructure cost per team, per topic, or per use case. Today it's a board question, and storing data is just one step of a larger goal. Our customers are now constantly asked to prove their data is used, and that every part of the platform earns its cost. I believe this is a good thing. Accountability forces clarity, clarity forces focus, and focus is how great platforms get built. If Meta has to prove utilization to Blue Owl, your CFO will ask you to prove it too. The teams who can answer are the ones who will get to keep building. #meta #ai #datacenter

Every team and AI agent touches your Kafka. Who controls what they access? Conduktor governs both, on the Kafka you already run.

The Kafka agent isn’t the moat. The context and permissioning layer around it is. A capable model is useful, but it doesn’t operate in a vacuum. In production, the hard part is the surrounding system: what the agent can observe, what it can reason over, and what it’s allowed to change. In Kafka, that means more than seeing a lag spike. It means understanding schemas, lineage, ownership, ACLs, recent changes, and how services depend on each other. Without that context, the agent’s guessing. Without the right permissions, it’s a faster path to an outage. That’s where agentic Kafka operations gets interesting: not just better agents, but better context and control around them.