Apache Flink is a distributed stream processing framework built for stateful computation over both unbounded and bounded data, commonly run alongside Kafka as the event backbone it consumes from.
This hub is the entry point to what we have written about running Flink in production. It is new and will grow section by section as we publish more, starting with Flink use cases: real deployments, with the architecture and the numbers behind them.
Everything the Flink cluster covers
Companies running Apache Flink in production and the architectures behind their deployments, indexed as we publish them.
Learn moreHow Netflix runs more than 30,000 Apache Flink jobs across Keystone, its Data Mesh SQL Processor, and a real-time distributed graph.
Learn moreHow Uber runs more than 2,000 Apache Flink SQL jobs processing over 4 trillion messages a day, from AthenaX through to IngestionNext, its Flink-to-Hudi streaming data lake.
Learn moreHow Lyft runs Apache Flink across pricing and matching features, fraud detection, and one of its largest streaming jobs, moving 80 gigabytes of events a minute from Kinesis to S3.
Learn moreHow 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.
Learn moreHow 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.
Learn moreHow Airbus's AirSense unit processes more than 2 billion aircraft-position events a day with Apache Flink, fusing multi-provider ADS-B feeds into real-time global flight tracking.
Learn moreHow Alibaba built Blink, its internal Apache Flink fork, to handle 4 billion records a second during Double 11, then merged its isolation and checkpointing innovations into Apache Flink 1.9 and 1.10.
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