Cloud applications are increasingly shifting to interactive and loosely-coupled microservices. Despite their advantages, microservices complicate resource management, due to inter-tier dependencies. We present Sinan, a cluster manager for interactive microservices that leverages easily-obtainable tracing data instead of empirical decisions, to infer the impact of a resource allocation on on end-to-end performance, and allocate appropriate resources to each tier. In a preliminary evaluation of Sinan with an end-to-end social network built with microservices, we show that Sinan's data-driven approach, allows the service to always meet its QoS without sacrificing resource efficiency.

翻译：云层应用正日益转向互动和松散的微观服务。尽管微观服务有其优势,但由于不同层次的相互依存关系,使资源管理复杂化。 我们介绍Sinan,一个互动微观服务的集群经理,利用易于获取的追踪数据而不是经验决定,来推断资源分配对端到端业绩的影响,并向各级分配适当的资源。在对Sinan进行初步评估时,我们展示Sinan的数据驱动方法,使服务在不牺牲资源效率的情况下能够满足其质保要求。