From 1M to 1B Features Per Second: Scaling ShareChat’s ML Feature Store

ShareChat’s Ivan Burmistrov and Andrei Manakov walk through how they built a low latency ML Feature Store based on ScyllaDB which initially failed to meet the scalability requirements and failed on 1 million features per second load, but has been successfully scaled 1000 times to handle 1 billing features per second without scaling the underlying database.

19 minutes
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Andrei Manakov, Staff Software Engineer at ShareChat

Andrei has over 12 years of experience as a Software Engineer in building high-load distributed systems. Currently, he is developing cutting-edge ML infrastructure.

Ivan Burmistrov, Senior Staff Software Engineer at ShareChat

Ivan is an experienced Software Engineer, ex-Facebook, ex-ScyllaDB, passionate about performance problems in distributed systems. He is leading the effort to build a world-class Feature Engineering framework at ShareChat.

P99 CONF OCT. 23 + 24, 2024

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