Title
Splice: An Automated Framework for Cost-and Performance-Aware Blending of Cloud Services
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 %.
Year
DOI
Venue
2022
10.1109/CCGrid54584.2022.00021
2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
Keywords
DocType
ISBN
automation,compiler,serverless,blending
Conference
978-1-6654-9957-6
Citations 
PageRank 
References 
0
0.34
7
Authors
7
Name
Order
Citations
PageRank
Myungjun Son171.55
Shruti Mohanty200.34
Jashwant Raj Gunasekaran300.34
Aman Jain400.34
Mahmut Taylan Kandemir501.69
Kesidis, G.643871.79
Bhuvan Urgaonkar72309158.10