Kirin：云原生WebAssembly服务编排
Kirin: Cloud-native WebAssembly Service Orchestration
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中文总结 AI 辅助
本文提出Kirin，一个云原生WebAssembly服务编排器，支持资源调度、生命周期管理等核心功能，评估显示其在服务工作负载上性能与容器相当，是容器的可行替代方案。
中文摘要 AI 辅助
现代云计算基础设施严重依赖虚拟化来提供工作负载隔离和资源效率。尽管容器因其相对于传统虚拟机更快的编排能力而成为主导的部署原语，但它们仍然引入了不可忽视的开销。WebAssembly（Wasm）作为一种替代性隔离技术出现，提供了轻量级的执行模型。由于兼容性限制，WebAssembly主要应用于函数即服务（FaaS）和边缘计算场景，在这些场景中已吸引了越来越多的研究兴趣。然而，WebAssembly生态系统的最新进展已显著成熟了该技术，引发了它能否在云原生工作负载中作为容器的可行替代品的问题。在本文中，我们提出了Kirin，一个用于云原生WebAssembly服务的编排器。它支持核心编排职责，包括资源调度、生命周期管理、扩缩容和请求路由。我们针对多种服务工作负载，将Kirin与基于容器的部署进行了评估，并展示了有前景的结果，尤其是在服务生命周期管理方面。同时，我们确认了CPU密集型工作负载中已知的限制。然而，对于典型的服务工作负载，Kirin展示了具有竞争力的性能，表明WebAssembly作为云原生部署技术，是更广泛采用的可行候选方案。
英文摘要
Modern cloud computing infrastructure relies heavily on virtualization to provide workload isolation and resource efficiency. While containers have become the dominant deployment primitive due to their fast orchestration compared to traditional virtual machines, they still introduce non-trivial overhead. WebAssembly (Wasm) has emerged as an alternative isolation technology, offering a lightweight execution model. Because of compatibility limitations, WebAssembly has mainly been applied to Function-as-a-Service (FaaS) and Edge Computing scenarios, where it has attracted growing research interest. However, recent advances in the WebAssembly ecosystem have significantly matured the technology, raising the question of whether it can serve as a viable replacement for containers in cloud-native workloads. In this paper, we present Kirin, an orchestrator for cloud-native WebAssembly services. It supports core orchestration responsibilities, including resource scheduling, lifecycle management, scaling, and request routing. We evaluate Kirin against container-based deployments for several service workloads and demonstrate promising results, particularly in service lifecycle management. Simultaneously, we confirm known limitations in CPU-intensive workloads. However, for typical service workloads, Kirin demonstrates competitive performance, suggesting that WebAssembly is a viable candidate for broader adoption as a cloud-native deployment technology.
发表机构
- Technische Universität Berlin（柏林工业大学）
机构由 AI 辅助整理，请以论文原文为准。
