Interference Analysis of Co-Located Container Workloads: A Perspective from Hardware Performance Counters

Abstract

Workload characterization is critical for resource management and scheduling. Recently, with the fast development of container technique, more and more cloud service providers like Google and Alibaba adopt containers to provide cloud services, due to the low overheads. However, the characteristics of co-located diverse services (e.g., interactive on-line services, off-line computing services) running in containers are still not clear. In this paper, we present a comprehensive analysis of the characteristics of co-located workloads running in containers on the same server from the perspective of hardware events. Our study quantifies and reveals the system behavior from the micro-architecture level when workloads are running in different co-location patterns. Through the analysis of typical hardware events, we provide recommended/unrecommended co-location workload patterns which provide valuable deployment suggestions for datacenter administrators.