How LinkedIn Serves Over 4.8 Million Member Profiles per Second
Summary
LinkedIn introduced Couchbase as a centralized caching tier for scaling member profile reads to handle increasing traffic that had outgrown their existing database cluster. The new solution achieved over 99% hit rate, and helped reduce tail latencies by more than 60% and costs by 10% annually. Rather than reworking the core components of the Espresso platform, the team decided to introduce a caching tier using Couchbase, considering that over 99% of requests are reads. Following the changes, the Profile Backend service became responsible for some operations that Espresso previously handled. The LinkedIn team has implemented further performance optimizations, streamlining reading data from Avro/binary format, and achieved around 30% improvement in deserialization times.
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