Defense in depth: unifying RBAC and data policies for transparent governance
Balance Kafka velocity and compliance. Learn how Kpow uses RBAC and Data Policies for safe, self-service production debugging without manual tickets.

Balance Kafka velocity and compliance. Learn how Kpow uses RBAC and Data Policies for safe, self-service production debugging without manual tickets.

From structuring data streams to spinning up full pipelines locally, our latest Kafka x Flink meetup in Melbourne was packed with hands-on demos and real-time insights. Catch the highlights and what's next.

Factor House has opened a public Slack for anyone working with streaming data, from seasoned engineers to newcomers exploring real-time systems. This space offers faster peer-to-peer support, open discussion across the ecosystem, and a friendly on-ramp for those just getting started.
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Learn how to build a real-time "Top-K" analytics pipeline from scratch using a modern data stack. This open-source project guides you through using Apache Kafka, Apache Flink, and Streamlit to ingest, process, and visualize live data, turning a continuous stream of events into actionable insights on an interactive dashboard.

Jumpstart your journey into modern data engineering with Factor House Local. Explore pre-configured Docker environments for Kafka, Flink, Spark, and Iceberg, enhanced with enterprise-grade tools like Kpow and Flex. Our hands-on labs guide you step-by-step, from building your first Kafka client to creating a complete data lakehouse and real-time analytics system. It's the fastest way to learn, prototype, and build sophisticated data platforms.
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Kpow's 94.3 release is here, transforming how you work with Kafka. Instantly query topics using plain English with our new AI-powered filtering, automatically decode any message format without manual setup, and leverage powerful new enhancements to our kJQ language. This update makes inspecting Kafka data more intuitive and powerful than ever before.

This minor hotfix release from Factor House resolves a bug when using Auto SerDes without Data policies, and adds support for UTF-8 String Auto SerDes inference.
We’re building more than products, we’re building a community. Whether you're getting started or pushing the limits of what's possible with Kafka and Flink, we invite you to connect, share, and learn with others.