HPC and data center scale application developers are abandoning POSIX IO because file system metadata synchronization and serialization overheads of providing strong consistency and durability are too costly - and often unnecessary - for their applications. Unfortunately, designing file systems with weaker consistency or durability semantics excludes applications that rely on stronger guarantees, forcing developers to re-write their applications or deploy them on a different system. We present a framework and API that lets administrators specify their consistency/durability requirements and dynamically assign them to subtrees in the same namespace, allowing administrators to optimize subtrees over time and space for different workloads. We show similar speedups to related work but more importantly, we show performance improvements when we custom fit subtree semantics to applications such as checkpoint-restart (91.7x speedup), user home directories (0.03 standard deviation from optimal), and users checking for partial results (2% overhead).

Storage systems need to support high-performance for special-purpose data processing applications that run on an evolving storage device technology landscape. This puts tremendous pressure on storage systems to support rapid change both in terms of their interfaces and their performance. But adapting storage systems can be difficult because unprincipled changes might jeopardize years of code-hardening and performance optimization efforts that were necessary for users to entrust their data to the storage system. We introduce the programmable storage approach, which exposes internal services and abstractions of the storage stack as building blocks for higher-level services. We also build a prototype to explore how existing abstractions of common storage system services can be leveraged to adapt to the needs of new data processing systems and the increasing variety of storage devices. We illustrate the advantages and challenges of this approach by composing existing internal abstractions into two new higher-level services: a file system metadata load balancer and a high-performance distributed shared-log. The evaluation demonstrates that our services inherit desirable qualities of the back-end storage system, including the ability to balance load, efficiently propagate service metadata, recover from failure, and navigate trade-offs between latency and throughput using leases.