research-article

How Does It Function? Characterizing Long-term Trends in Production Serverless Workloads

Authors:

Adam BarkerAuthors Info & Claims

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

Pages 443 - 458

https://doi.org/10.1145/3620678.3624783

Published: 31 October 2023 Publication History

Abstract

This paper releases and analyzes two new Huawei cloud serverless traces. The traces span a period of over 7 months with over 1.4 trillion function invocations combined. The first trace is derived from Huawei's internal workloads and contains detailed per-second statistics for 200 functions running across multiple Huawei cloud data centers. The second trace is a representative workload from Huawei's public FaaS platform. This trace contains per-minute arrival rates for over 5000 functions running in a single Huawei data center. We present the internals of a production FaaS platform by characterizing resource consumption, cold-start times, programming languages used, periodicity, per-second versus per-minute burstiness, correlations, and popularity. Our findings show that there is considerable diversity in how serverless functions behave: requests vary by up to 9 orders of magnitude across functions, with some functions executed over 1 billion times per day; scheduling time, execution time and cold-start distributions vary across 2 to 4 orders of magnitude and have very long tails; and function invocation counts demonstrate strong periodicity for many individual functions and on an aggregate level. Our analysis also highlights the need for further research in estimating resource reservations and time-series prediction to account for the huge diversity in how serverless functions behave.

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Cited By

Chen QQian JChe YLin ZWang JZhou JSong LLiang YWu JZheng WLiu WLi LLiu FTan KSekar VYu MSeneviratne AVeitch D(2024)YuanRong: A Production General-purpose Serverless System for Distributed Applications in the CloudProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672216(843-859)Online publication date: 4-Aug-2024
https://dl.acm.org/doi/10.1145/3651890.3672216
Segarra CFeldman-Fitzthum TBuono DPietzuch P(2024)Serverless Confidential Containers: Challenges and OpportunitiesProceedings of the 2nd Workshop on SErverless Systems, Applications and MEthodologies10.1145/3642977.3652097(32-40)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3642977.3652097
Starc RKuchler TGiardino MKlimovic A(2024)Serverless? RISC more!Proceedings of the 2nd Workshop on SErverless Systems, Applications and MEthodologies10.1145/3642977.3652095(15-24)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3642977.3652095
Show More Cited By

Index Terms

How Does It Function? Characterizing Long-term Trends in Production Serverless Workloads
1. Computer systems organization
  1. Architectures
    1. Distributed architectures
      1. Cloud computing
2. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks

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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.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 31 October 2023

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October 30 - November 1, 2023

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Overall Acceptance Rate 169 of 722 submissions, 23%

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Cited By

Chen QQian JChe YLin ZWang JZhou JSong LLiang YWu JZheng WLiu WLi LLiu FTan KSekar VYu MSeneviratne AVeitch D(2024)YuanRong: A Production General-purpose Serverless System for Distributed Applications in the CloudProceedings of the ACM SIGCOMM 2024 Conference10.1145/3651890.3672216(843-859)Online publication date: 4-Aug-2024
https://dl.acm.org/doi/10.1145/3651890.3672216
Segarra CFeldman-Fitzthum TBuono DPietzuch P(2024)Serverless Confidential Containers: Challenges and OpportunitiesProceedings of the 2nd Workshop on SErverless Systems, Applications and MEthodologies10.1145/3642977.3652097(32-40)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3642977.3652097
Starc RKuchler TGiardino MKlimovic A(2024)Serverless? RISC more!Proceedings of the 2nd Workshop on SErverless Systems, Applications and MEthodologies10.1145/3642977.3652095(15-24)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3642977.3652095
Christofidi GDoudali T(2024)Do Predictors for Resource Overcommitment Even Predict?Proceedings of the 4th Workshop on Machine Learning and Systems10.1145/3642970.3655838(153-160)Online publication date: 22-Apr-2024
https://dl.acm.org/doi/10.1145/3642970.3655838
Katsakioris CAlverti CNikas KSiakavaras DPsomadakis SKoziris NMencagli GDazzi PLowenthal DBadia R(2024)FaaSRail: Employing Real Workloads to Generate Representative Load for Serverless ResearchProceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing10.1145/3625549.3658684(214-226)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3625549.3658684
Cai XSang QHu CGong YSuo KZhou XCheng D(2024)Incendio: Priority-Based Scheduling for Alleviating Cold Start in Serverless ComputingIEEE Transactions on Computers10.1109/TC.2024.338606373:7(1780-1794)Online publication date: Jul-2024
https://doi.org/10.1109/TC.2024.3386063
Chen JXu FGu YChen LLiu FZhou Z(2024)HarmonyBatch: Batching multi-SLO DNN Inference with Heterogeneous Serverless Functions2024 IEEE/ACM 32nd International Symposium on Quality of Service (IWQoS)10.1109/IWQoS61813.2024.10682915(1-10)Online publication date: 19-Jun-2024
https://doi.org/10.1109/IWQoS61813.2024.10682915

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