research-article

Parrotfish: Parametric Regression for Optimizing Serverless Functions

Authors:

Arshia Moghimi,

Mehdi Ben Chikha,

Mohammad ShahradAuthors Info & Claims

SoCC '23: Proceedings of the 2023 ACM Symposium on Cloud Computing

Pages 177 - 192

https://doi.org/10.1145/3620678.3624654

Published: 31 October 2023 Publication History

Abstract

Serverless computing is a new paradigm that aims to remove the burdens of cloud management from developers. Yet rightsizing serverless functions remains a pain point for developers. Choosing the right memory configuration is necessary to ensure cost and/or performance optimality for serverless workloads. In this work, we identify that using parametric regression can significantly simplify function rightsizing compared to black-box optimization techniques currently available. With this insight, we build a tool, called Parrotfish, which finds optimal configurations through an online learning process. It also allows users to communicate constraints on execution time, or to relax cost optimality to gain performance. Parrotfish achieves substantially lower exploration costs (1.81-9.96×) compared with the state-of-the-art tools, while delivering similar or better recommendations.

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Cited By

Schirmer TScheuner JPfandzelter TBermbach D(2024)FUSIONIZE++: Improving Serverless Application Performance Using Dynamic Task Inlining and Infrastructure OptimizationIEEE Transactions on Cloud Computing10.1109/TCC.2024.345110812:4(1172-1185)Online publication date: Oct-2024
https://doi.org/10.1109/TCC.2024.3451108
Devineni SGorantla BShaik IAnand Kumar V(2024)Optimizing Cloud Resources using Algorithmic Approaches in Serverless Computing2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10724923(1-6)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10724923

Index Terms

Parrotfish: Parametric Regression for Optimizing Serverless Functions
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing

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cover image ACM Conferences

SoCC '23: Proceedings of the 2023 ACM Symposium on Cloud Computing

October 2023

624 pages

ISBN:9798400703874

DOI:10.1145/3620678

Copyright © 2023 ACM.

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Publication History

Published: 31 October 2023

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Natural Sciences and Engineering Research Council of Canada

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SoCC '23

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SoCC '23: ACM Symposium on Cloud Computing

October 30 - November 1, 2023

CA, Santa Cruz, USA

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Overall Acceptance Rate 169 of 722 submissions, 23%

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Cited By

Schirmer TScheuner JPfandzelter TBermbach D(2024)FUSIONIZE++: Improving Serverless Application Performance Using Dynamic Task Inlining and Infrastructure OptimizationIEEE Transactions on Cloud Computing10.1109/TCC.2024.345110812:4(1172-1185)Online publication date: Oct-2024
https://doi.org/10.1109/TCC.2024.3451108
Devineni SGorantla BShaik IAnand Kumar V(2024)Optimizing Cloud Resources using Algorithmic Approaches in Serverless Computing2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10724923(1-6)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10724923

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