弹性块存储的黑盒性能评估：契约、速率限制模型与软件探索
Black-Box Performance Evaluation of Elastic Block Storage: Contract, Rate-Limiting Model, and Software Exploration
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中文总结 AI 辅助
研究弹性块存储中ESSD与本地SSD性能差异及软件适配问题，通过用户中心黑盒表征，提出ESSD契约、改进速率限制模型，经RocksDB案例研究得出四条准则，为EBS用户利用ESSD性能提供参考。
中文摘要 AI 辅助
具有存储-计算解耦架构的弹性块存储（EBS）是现代云基础设施的关键组件，以弹性固态硬盘（ESSD）形式为用户提供存储资源。尽管已有从提供商角度记录EBS架构的工作，但ESSD与本地SSD性能差异及主机软件如何适配尚未充分研究。本文以用户为中心对亚马逊AWS和阿里云的ESSD进行黑盒性能表征。主要贡献有：提出ESSD契约，含四个行为观察和五个软件适配可行建议；改进I/O速率限制模型，结合带宽-IOPS双重限制和细粒度令牌重新填充以抑制延迟峰值；通过RocksDB案例研究得出缓存管理、I/O调节、存储预算利用和压缩算法四条准则。希望这些贡献能为EBS用户理解和利用ESSD独特性能特性提供实用参考。
英文摘要
Elastic block storage (EBS) with the storage-compute disaggregated architecture is a key component in modern cloud infrastructure. EBS offers users storage resources in the form of elastic solid-state drives (ESSDs). Nonetheless, despite recent efforts that have documented EBS architectures from the provider's perspective, how ESSDs perform differently from local SSDs and how host software should adapt accordingly have not been sufficiently studied. In this paper, we conduct a user-centric, black-box performance characterization of ESSDs from Amazon AWS and Alibaba Cloud. We make three main contributions: (1) an ESSD contract that presents four behavioral observations and five actionable implications for software adaptation, (2) a refined I/O rate-limiting model combining bandwidth-IOPS dual limiting and fine-grained token refilling to suppress latency spikes, and (3) a case study on RocksDB that derives four guidelines on cache management, I/O regulation, storage budget utilization, and compression algorithms. Collectively, we hope these contributions can serve as a practical reference for EBS users to understand and exploit the distinctive performance properties of ESSDs.
