A user-centric, black-box performance characterization of ESSDs from Amazon AWS and Alibaba Cloud is conducted and it is hoped these contributions can serve as a practical reference for EBS users to understand and exploit the distinctive performance properties of ESSDs.
Abstract
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.
With the widespread adoption of cloud computing and virtualization, multi-tenant architecture has become the mainstream deployment model for data center storage. Solid-state drives (SSDs), leveraging high IOPS, low latency, and high parallelism, serve as the core storage medium. Nevertheless, internal resource contenti...
Dan-Dan Su, Qi-Hao Liu, Xin-Ming Li et al.· International Conference on...· 0 citations
This paper presents an in-depth analysis of data migration behavior in commercial HSSs, uncovering substantial performance variability when multiple migration tasks execute concurrently, and proposes PASCAL, a system-level bandwidth orchestration framework that improves performance robustness in production-grade HSSs.
Ji Zhang, Li Liu, André Brinkmann et al.· Proceedings of the VLDB Endo...· 0 citations
SOS is a distributed key-value store that bridges this gap by guaranteeing at most one physical disk I/O per operation, enforced by three co-designed components: a flat in-memory hash index with O (1) lookup; a disk storage engine with a hierarchical variable-size layout that limits internal fragmentation to ≈7.93%; an...
Ying-Xin Li, Kai Liu, Hanglun Xie· Proceedings of the VLDB Endo...· 0 citations
KV-cache offload is widely used to stretch GPU memory for LLM serving, but its storage behavior has not been characterized at the block-device level. In this paper, we study LMCache through realworld multi-session workloads that span same/different context $\times$ same/different prompt, using over 100 stateless reques...
Ying He, Dingsen Shi, Yanbo Dai et al.· 2026 International Conferenc...· 0 citations
SolidAttention is introduced, an LLM inference engine which addresses limitations through a tight co-design of dynamic attention sparsity algorithms and SSD-based storage management and minimizes SSD-induced blocking latency.
Xin Zheng, Dong-Liang Wei, Jian-Xiang Gao et al.· 0 citations
The findings demonstrate that modern analytical storage techniques can significantly improve SystemC transaction tracing workflows and show that storage layout is a first-order determinant of footprint and query performance at scale.
George Frazier, Dusti Johnson· International Conference on...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.