ATOM: Model-driven autoscaling for microservices

Gias, A.U., Casale, G. and Woodside, M. 2019. ATOM: Model-driven autoscaling for microservices. 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS). Dallas, TX, USA 07 - 10 Jul 2019 IEEE . https://doi.org/10.1109/icdcs.2019.00197

TitleATOM: Model-driven autoscaling for microservices
AuthorsGias, A.U., Casale, G. and Woodside, M.
TypeConference paper
Abstract

Microservices based architectures are increasingly widespread in the cloud software industry. Still, there is a shortage of auto-scaling methods designed to leverage the unique features of these architectures, such as the ability to independently scale a subset of microservices, as well as the ease of monitoring their state and reciprocal calls. We propose to address this shortage with ATOM, a model-driven autoscaling controller for microservices. ATOM instantiates and solves at run-time a layered queueing network model of the application. Computational optimization is used to dynamically control the number of replicas for each microservice and its associated container CPU share, overall achieving a fine-grained control of the application capacity at run-time. Experimental results indicate that for heavy workloads ATOM offers around 30%-37% higher throughput than baseline model-agnostic controllers based on simple static rules. We also find that model-driven reasoning reduces the number of actions needed to scale the system as it reduces the number of bottleneck shifts that we observe with model-agnostic controllers.

Year2019
Conference2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS)
PublisherIEEE
Publication dates
Published2019
ISBN9781728125190
Digital Object Identifier (DOI)https://doi.org/10.1109/icdcs.2019.00197
Web address (URL)http://www.scopus.com/inward/record.url?eid=2-s2.0-85074821654&partnerID=MN8TOARS

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