The Context Gap caused by fragmented tools hinders effective Kafka monitoring and troubleshooting, as it forces engineers to manually piece together logs and metrics. This guide demonstrates how to close that gap using Kpow's unified workflow to identify the stall, inspect the data, and resolve the incident in a single interface.
Apache Kafka 4.1 has landed: with queue support in preview, improved Kafka Streams coordination, and new security and metrics features, this release marks a major milestone for the future of real-time data systems.
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 94.3 now integrates with Google Cloud's managed Schema Registry, enabling native OAuth authentication. This guide walks through the complete process of configuring authentication and using Kpow to create, manage, and inspect data validated against Avro schemas.
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.
