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At P99 CONF 23, ShareChat tackled scaling its ML Feature Store to 1B features/sec—then had to cut costs while maintaining SLAs. Ivan & David share how they optimized compute, reduced waste in Kubernetes, and tackled autoscaling for Apache Flink. It's geared for anyone interested in ML Feature Store and/or cloud cost optimizations.
David Malinge is a Senior Staff 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.
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