News, guides, and engineering deep dives.
Practical guidance on Kafka, Flink, Iceberg, and real-time data.
How Grab uses Apache Kafka in production
A deep-dive into Grab's Kafka architecture — how the Coban team built a terabyte-per-hour streaming platform serving 300 billion events a week across GrabFood, GrabPay, mobility, and more.
How JPMorgan uses Apache Kafka in production
A deep dive into JPMorgan Chase's Kafka architecture, covering multi-tenant cluster design, managed Kafka Connect, the Photon Framework, and decisions behind a large-scale deployment.
How LinkedIn uses Apache Kafka in production
A deep-dive into LinkedIn's Kafka architecture, covering use cases, scale, engineering decisions, and key contributors.
How PayPal uses Apache Kafka in production
A deep-dive into PayPal's Kafka architecture — covering use cases, scale, engineering decisions, and key contributors across a fleet handling 1.3 trillion messages per day.
How Reddit uses Apache Kafka in production
A deep-dive into Reddit's Kafka architecture — covering use cases, scale, engineering decisions and key contributors.
How Robinhood uses Apache Kafka in production
A deep-dive into Robinhood's Kafka architecture: use cases, scale, and engineering decisions. Robinhood processes 2.2 million messages per second across equities, crypto, and fraud detection.
How Spotify used Apache Kafka in production
A deep-dive into Spotify's Kafka architecture — covering their event delivery system, 700K events/second scale, engineering decisions, and why they ultimately migrated to Google Cloud Pub/Sub.
How The New York Times uses Kafka
A deep-dive into The New York Times' Kafka publishing pipeline, covering the Monolog architecture, single-partition design, Kafka Streams usage, and treating Kafka as a permanent content store.
How Uber uses Apache Kafka in production
A deep-dive into Uber's Kafka architecture - covering use cases, scale, engineering decisions, and key contributors. From one region to trillions of messages a day.