发表机构
TU Wien（维也纳工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出STORE，一种面向无服务器函数的自供给存储架构，通过平台级零接触零配置自动选择最优存储后端，相比Terraform和Pulumi减少高达84%实现工作量，且无性能开销。
AI 中文摘要
无服务器计算提供了按需弹性、按使用付费和简化部署等优势。然而，无服务器函数通常是无状态的，依赖外部存储服务（如对象存储或数据库）来交换数据或支持有状态函数。供给和配置这些存储系统仍然需要手动设置或声明式脚本，这引入了复杂性，减慢了开发速度，并增加了配置错误的风险。为了解决这些挑战，在本文中，我们介绍了STORE，一种面向无服务器函数的自供给存储架构。STORE自动选择最优存储后端，并通过零接触和零配置供给消除开发者的工作量，这是通过将自供给逻辑移至平台层面实现的。我们的评估结果表明，与Terraform和Pulumi等成熟的基础设施即代码框架相比，STORE将实现工作量减少了高达84%，同时在真实工作负载下保持低延迟和线性可扩展性，且不引入性能开销。
英文摘要
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 \textsc{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.
Comments13th International Conference on Future Internet of Things and Cloud, Granada, Spain, 20-22 July 2026
