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A case for performance-aware deployment of containers

Abstract:

Cloud-native applications are increasingly adopting microservices architectures that support the development agility required by modern software. These applications deploy their components in containers that enable microservices to be deployed across different platforms, supporting the independent scaling of the different components. However, the operational complexity of microservices presents significant challenges in maintaining the performance of such applications, especially in clouds with performance variability and unpbkp_redictability. While virtual machine based deployment of applications has been well studied—with sophisticated orchestrators in the literature and practice—there has been little such studies on the opportunity in improving application performance using performance-aware deployment strategies for containers. In this paper, we consider both the run-time and initialization time performance of containerized applications and show that default placement strategies provided by orchestrators are often insufficient. Our experiments on multiple services show that a performance-aware approach is able to outperform the default placement strategy by up to factor of 2x and 2.21x for the 50th and 99th percentiles.