May 2026· International Conference on Future Internet of Things and Cloud· pp. 185-192· 0 citations· 39 references
Computer Science
TL;DR
STORE automatically selects the optimal storage backend and eliminates developer effort through zero-touch and zero-configuration provisioning, achieved by moving the self-provisioning logic to the platform level.
Abstract
Serverless computing provides on-demand elasticity, pay-per-use, and simplified deployment. However, serverless functions are typically stateless and depend on external storage services such as object stores or databases to exchange data or support stateful functions. Provisioning and configuring these storage systems still requires manual setup or declarative scripts, introducing complexity, slowing development, and increasing the risk of configuration errors. To address these challenges, in this paper, we introduce STORE, a self-provisioning storage architecture for serverless functions. STORE automatically selects the optimal storage backend and eliminates developer effort through zero-touch and zero-configuration provisioning, achieved by moving the self-provisioning logic to the platform level. Our evaluation results show that STORE reduces implementation effort by up to 84% compared to well-established Infrastructure-as-Code frameworks such as Terraform and Pulumi while maintaining low latency and linear scalability under realistic workloads, without introducing performance overhead.
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Kira Duwe, Andrew Lamb, L. Lersch et al.· Datenbank-Spektrum· 0 citations
Serverless computing has emerged as a compelling cloud paradigm due to its simplified development model, automatic scalability, and fine-grained billing. While its stateless execution model enables high elasticity and resource efficiency, it poses noteworthy challenges for building complex stateful applications. To bri...
Yijie Liu, Zhuo Huang, Han-Xiang Huang et al.· IEEE Transactions on Paralle...· 0 citations
Large-scale online services—including web search, recommendation, and LLM inference workloads such as Retrieval-Augmented Generation (RAG) and KV-cache offloading—demand storage that handles petabyte-scale data under millisecond tail-latency SLAs. In-memory stores are cost-prohibitive at scale; disk-based systems sacri...
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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.
Modern cloud applications and AI-driven workloads demand elastic compute, instant environment isolation, and open data interoperability. However, production databases remain largely based on monolithic architectures designed in the 1980s, tightly coupling storage and compute and creating operational fragility, cost ine...
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