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QoS aware FaaS platform

Sheshadri, KR and Lakshmi, J (2021) QoS aware FaaS platform. In: 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2021, 10-13 May 2021, Melbourne, pp. 812-819.

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Official URL: https://doi.org/10.1109/CCGrid51090.2021.00099

Abstract

Function as a Service (FaaS), a form of serverless computing, is one of the recent cloud computing service offerings, which abstracts and automates the management and provisioning of resources, and deployment of applications. It provides powerful abstractions to compose applications as stateless functions and triggers their executions through events. The platform offers autonomous scaling for applications and pay-as-you-go sub-second billing model. However, contemporary FaaS platforms provide limited features in stating resource requirements. They often lack specifications to express application specificities and resource requirements associated with Quality of Service (QoS). Such specifications can effectively guide the resource provisioning and function deployment at the resource provider, leading to efficient resource utilization and cost savings. This research exploration motivates the need for a QoS specification framework for FaaS and proposes ideas for realizing an initial QoS aware FaaS platform. Experimental results based on real-world workload trace show the cost savings and efficient resource utilization that QoS can bring in FaaS platforms. © 2021 IEEE.

Item Type: Conference Paper
Publication: Proceedings - 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords: Cluster computing; Specifications, Cloud computing services; Cost saving; Pay as you go; QoS specifications; Real-world; Resource providers; Resource requirements; Resource utilizations, Quality of service
Department/Centre: Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited: 03 Dec 2021 08:28
Last Modified: 03 Dec 2021 08:28
URI: http://eprints.iisc.ac.in/id/eprint/70206

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