Splice: An Automated Framework for Cost-and Performance-Aware Blending of Cloud Services

Myungjun Son, Shruti Mohanty, Jashwant Raj Gunasekaran, Aman Jain, Mahmut Taylan Kandemir, George Kesidis, Bhuvan Urgaonkar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

With the rapid growth of users adopting public clouds to run their applications, the types of resources procured from the different public cloud resource offerings are critical in simultaneously achieving satisfactory performance and reducing deployment costs. Typically, no one resource type can meet all application requirements, and thus combining different resource offerings is known to considerably reduce the performance-cost problem. However, it is non-trivial to use blended resources, due to the manual overhead of designing and implementing such blended approaches. Specifically, it necessitates rewriting the application code to suit a given resource and scaling it on demand. In order to overcome this manual hurdle, we take the first step by proposing Splice, an automated framework for cost-and performance-aware blending of IaaS and FaaS services. The three major goals of Splice are: (1) while cost-saving opportunities exist from blending resources, we aim to largely automate the blending process for public cloud services through a compiler-driven approach; (2) more specifically, we focus on automated blending of VMs and serverless functions; and (3) for serverless applications which contain multiple chained functions, we unearth the potential choices in determining a portion of the services to be blended cost-efficiently. We implement Splice on Amazon Web Services (AWS) using an Abstract Syntax Tree (AST), and extensively evaluate its effectiveness using several ap-plications with real-world traces. Our experiments demonstrate that, through automated blending, Splice is able to reduce SLO violations by 31 % compared to VM-based resource procurement schemes, while simultaneously minimizing costs by up to 32 %.

Original languageEnglish (US)
Title of host publicationProceedings - 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2022
EditorsMaria Fazio, Dhabaleswar K. Panda, Radu Prodan, Valeria Cardellini, Burak Kantarci, Omer Rana, Massimo Villari
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages119-128
Number of pages10
ISBN (Electronic)9781665499569
DOIs
StatePublished - 2022
Event22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2022 - Taormina, Italy
Duration: May 16 2022May 19 2022

Publication series

NameProceedings - 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2022

Conference

Conference22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2022
Country/TerritoryItaly
CityTaormina
Period5/16/225/19/22

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Software
  • Information Systems and Management
  • Computer Networks and Communications

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