论文标题
QoS保证实用的有效微服务自动化
Practical Efficient Microservice Autoscaling with QoS Assurance
论文作者
论文摘要
云应用程序越来越多地从整体服务转向基于敏捷微服务的部署。但是，由于宽松的耦合和相互作用的组件数量，微量服务的有效资源管理构成了重大障碍。各种微服务之间的相互依赖性使现有的云资源自动化技术无效。同时，试图捕获微服务中复杂关系的基于机器学习（ML）的方法需要广泛的培训数据并导致故意违规。此外，这些重量重的方法适应动态变化的微服务操作环境的缓慢。在本文中，我们提出了PEMA（实用有效的微服务自动化），这是一家轻量级的微服务资源管理器，通过减少机会性资源来找到有效的资源分配。 PEMA的轻量级设计可以实现新颖的工作负载和自适应资源管理。使用三个原型微服务实现，我们表明PEMA可以找到有效的资源分配，并且与基于商业规则的资源分配相比，最多可节省33％的资源。
Cloud applications are increasingly moving away from monolithic services to agile microservices-based deployments. However, efficient resource management for microservices poses a significant hurdle due to the sheer number of loosely coupled and interacting components. The interdependencies between various microservices make existing cloud resource autoscaling techniques ineffective. Meanwhile, machine learning (ML) based approaches that try to capture the complex relationships in microservices require extensive training data and cause intentional SLO violations. Moreover, these ML-heavy approaches are slow in adapting to dynamically changing microservice operating environments. In this paper, we propose PEMA (Practical Efficient Microservice Autoscaling), a lightweight microservice resource manager that finds efficient resource allocation through opportunistic resource reduction. PEMA's lightweight design enables novel workload-aware and adaptive resource management. Using three prototype microservice implementations, we show that PEMA can find efficient resource allocation and save up to 33% resource compared to the commercial rule-based resource allocations.
