  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.

Distributed, Parallel, and Cluster Computing