HOW LINKEDIN SCALED THEIR SYSTEM TO 5 MILLION QUERIES PER SECOND

Summary from the TLDR Web Dev newsletter

LinkedIn scaled its restriction enforcement system to handle 5 million queries per second using a multi-faceted approach. It used BitSets for efficient boolean storage and Bloom Filters for probabilistic set membership checks. Its final architecture incorporated a Venice database as the central source of truth, Kafka for near real-time updates, and a client layer utilizing a REST API.