Cost aware resource sizing and scaling of microservices

Agarwal, P and Lakshmi, J (2019) Cost aware resource sizing and scaling of microservices. In: 4th International Conference on Cloud Computing and Internet of Things, CCIOT 2019, 20 September 2019, Tokyo, pp. 66-74.

PDF CCIOT_2019.pdf - Published Version Restricted to Registered users only Download (721kB) | Request a copy

Abstract

Microservices are small, independent, loosely coupled components which provide flexibility, agility, and scalability to an application. While these are aimed for scalability, achieving it needs judicious trade-offs between size, number and cost of provisioning. In this architecture, sizing in both homogeneous and heterogeneous resources plays a key role to balance application performance and resource requirement, as workload demand varies. This paper provides insights where the importance of considering workload characterization to decide a homogeneous or heterogeneous scaling strategy for a microservice is discussed. The work exploits the correlation of workload characterization, predicted workload demand and selection of right-sized microservice to minimize resource costs. Size of microservice is referred with respect to the amount of resources allocated to the microservice. This work also evaluates trade-offs between considering the entire predicted workload demand for resource cost optimization against algorithmic computational complexity and designs a heuristic to reduce such complexity. Evaluation of results demonstrate two important outcomes. Firstly, workload characterization helps to choose between homogeneous or heterogeneous sizing for different microservices. And secondly, by considering workload demand prediction beyond the current scheduling interval, allows to make scaling decision in the current cycle keeping in view whether the demand is going to increase or decrease. The paper also details on how to use the insights of application characterization and workload trend for choosing an appropriate scaling strategy. © 2019 Association for Computing Machinery.

Item Type:	Conference Paper
Publication:	ACM International Conference Proceeding Series
Publisher:	Association for Computing Machinery
Additional Information:	The copyright for this article belongs to Association for Computing Machinery
Keywords:	Cloud computing; Commerce; Computational complexity; Economic and social effects; Internet of things; Optimization; Parallel processing systems; Scalability, Application performance; Demand prediction; Heterogeneous resources; Microservices; Resource optimization; Resource requirements; Scheduling interval; Workload characterization, Costs
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	05 Jan 2023 12:22
Last Modified:	05 Jan 2023 12:22
URI:	https://eprints.iisc.ac.in/id/eprint/78798

Actions (login required)

View Item