Robinhood uses Kafka in every line of its business, from stock and crypto trading to its self-clearing system and online data analytics. Most critical is the order path, which refers to all microservices and operations required for placing and filling customer orders in equities, options and crypto. Robinhood’s order path relies heavily on kafka for interservice communication and queueing needs, and it also leverages outbox patterns using postgres and kafka for at least once guarantees for order execution. Previously we have been using a single production kafka cluster for all of these purposes, thus making the cluster a single point of failure (SPoF) for the order-path.

This talk discusses how we removed this SPoF through investments in Kafka infrastructure and our client libraries, letting us horizontally shard our order path kafka clusters. We would also discuss about the following:
* Intelligent and reactive client libraries we built to make this sharding easier
* Producer proxy sidecars to help our python processes work with sharded architecture
* How we do safe sharded kafka cluster rollouts
* Sharding vs Redundancy for different use cases