Black-box inter-application traffic monitoring for adaptive container placement

Abstract

A key issue in the performance of modern containerized distributed systems, such as big data storage and processing stacks or micro-service based applications, is the placement of each container, or container pod, in virtual and physical servers. Although it has been shown that inter-application traffic is an important factor in placement decisions, as it directly indicates how components interact, it has not been possible to accurately monitor it in an application independent way, thus putting it out of reach of cloud platforms. In this paper we present an efficient black-box monitoring approach for detecting and building a weighted communication graph of collaborating processes in a distributed system that can be queried for various purposes, including adaptive placement. The key to achieving high detail and low overhead without custom application instrumentation is to use a kernel-aided event driven strategy. We evaluate a prototype implementation with micro-benchmarks and demonstrate its usefulness for container placement in a distributed data storage and processing stack (i.e., Cassandra and Spark).