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Asynchronous Erasure Coding for Scalable, Resilient, and Efficient Storage

Abstract

Erasure Coding is increasingly adopted in on-premises environments to enable data reduction for critical applications while maintaining high durability and fault tolerance. Compared to traditional replication, implementing Erasure Coding at scale introduces unique challenges, particularly around performance, consistency, and garbage management. An asynchronous, MapReduce-like approach to encoding data allows for eventual encoding while maximizing storage savings. This talk will explore the architectural considerations, trade-offs between resiliency and efficiency, and the practical aspects of using flexible strip sizes and handling immutable and mutable data. We will also delve into techniques to manage garbage efficiently, ensuring space reclamation without impacting user experience.