Rebuilding LinkedIn’s Tracking Infrastructure: Scaling, Migrating, and Hardening a High-Volume Event Pipeline
By Pravesh Gupta, Senior Staff Software Engineer at LinkedIn & Pranav Mutharia, Senior Software Engineer at LinkedIn
LinkedIn’s tracking infrastructure turns product interactions such as impressions, clicks, page views, and media playback into signals used for experimentation, product analytics, platform health, and product experiences across LinkedIn. The quality and freshness of this data affect how quickly teams can understand product behavior and make informed decisions.
The system processes hundreds of billions of events per day—millions of events per second at peak Member activity—across several hundred event types. At this scale, even a small inefficiency or correctness issue can have a large cumulative impact.
That system had carried LinkedIn’s tracking traffic for years, but the technical environment around it had changed. It ran on Java 8 and the Play Framework while LinkedIn’s service ecosystem standardized on gRPC and a modern Java runtime—and adopting gRPC meant a new request contract and...
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