News, guides, and engineering deep dives.
Practical guidance on Kafka, Flink, Iceberg, and real-time data.
How Booking.com uses Apache Flink in production
How Booking.com's Security Platform Services team runs Apache Flink as the engine behind an internal security-as-a-service platform, scaling to more than 250 jobs under Ververica Platform.
Apache Flink: the complete guide
Apache Flink is a distributed stream processing framework for stateful computation over unbounded and bounded data. This hub indexes what we have written about running it in production.
Flink use cases
Companies running Apache Flink in production, the architectures behind their deployments, and what to read next. Indexed as we publish new use-case research.
How Lyft uses Apache Flink in production
How Lyft's Streaming Compute and Marketplace teams run Apache Flink for pricing features, fraud detection, and event persistence, including the 2026 migration off a homegrown Kubernetes operator.
How Netflix uses Apache Flink in production
How Netflix runs more than 30,000 Apache Flink jobs across Keystone, its Data Mesh SQL Processor, and a real-time distributed graph, sourced from its own engineering blog and conference talks.
How Pinterest uses Apache Flink in production
How Pinterest runs 130+ Apache Flink jobs across eight multitenant YARN clusters for image-similarity detection, experiment analytics, ad-budget enforcement, and CDC ingestion into Iceberg.
How Uber uses Apache Flink in production
How Uber runs more than 2,000 Apache Flink SQL jobs processing over 4 trillion messages a day, from its early AthenaX SQL platform through to IngestionNext, its Flink-to-Hudi streaming data lake.
AKHQ vs Confluent Control Center
AKHQ is free and runs against any Kafka. Confluent Control Center is not sold separately and needs Confluent Platform in the brokers. What each costs.
AKHQ vs Kadeck
AKHQ is free under Apache 2.0 with no paid tier. Kadeck sells governance at ten seats. What each costs, where each runs out, and which fits which team.