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Measuring Baseline Overheads in Different Orchestration Mechanisms for Large FaaS Workflows

Published: 19 July 2022 Publication History

Abstract

Serverless environments have attracted significant attention in recent years as a result of their agility in execution as well as inherent scaling capabilities as a cloud-native execution model. While extensive analysis has been performed in various critical performance aspects of these environments, such as cold start times, the aspect of workflow orchestration delays has been neglected. Given that this paradigm has become more mature in recent years and application complexity has started to rise from a few functions to more complex application structures, the issue of delays in orchestrating these functions may become severe. In this work, one of the main open source FaaS platforms, Openwhisk, is utilized in order to measure and investigate its orchestration delays for the main sequence operator of the platform. These are compared to delays included in orchestration of functions through two alternative means, including the execution of orchestrator logic functions in supporting runtimes based on Node-RED. The delays inserted by each different orchestration mode are measured and modeled, while boundary points of selection between each mode are presented, based on the number and expected delay of the functions that constitute the workflow. It is indicative that in certain cases, the orchestration overheads might range from 0.29% to 235% compared to the beneficial computational time needed for the workflow functions. The results can extend simulation and estimation mechanisms with information on the orchestration overheads.

References

[1]
T. Lynn, P. Rosati, A. Lejeune, and V. Emeakaroha, "A preliminaryreview of enterprise serverless cloud computing (function-as-a-service)platforms," in2017 IEEE International Conference on Cloud ComputingTechnology and Science (CloudCom), pp. 162--169, IEEE, 2017
[2]
Eismann, S., Scheuner, J., Van Eyk, E., Schwinger, M., Grohmann, J., Herbst, N., Abad, C. and Iosup, A., 2021. The State of Serverless Applications: Collection, Characterization, and Community Consensus. IEEE Transactions on Software Engineering.
[3]
Kousiouris, G. and Kyriazis, D., 2021. Functionalities, Challenges and Enablers for a Generalized FaaS based Architecture as the Realizer of Cloud/Edge Continuum Interplay. In CLOSER (pp. 199--206).
[4]
C. Abad, I. T. Foster, N. Herbst, and A. Iosup, "Serverless computing (dagstuhl seminar 21201)," inDagstuhl Reports, vol. 11, SchlossDagstuhl-Leibniz-Zentrum fur Informatik, 2021.
[5]
P. Leitner, E. Wittern, J. Spillner, and W. Hummer, "A mixed-methodempirical study of function-as-a-service software development in indus-trial practice,"Journal of Systems and Software, vol. 149, pp. 340--359,2019.
[6]
F. Amato and F. Moscato, "Exploiting cloud and workflow patterns forthe analysis of composite cloud services,"Future Generation ComputerSystems, vol. 67, pp. 255--265, 2017.
[7]
I. Baldini, P. Castro, P. Cheng, S. Fink, V. Ishakian, N. Mitchell, V. Muthusamy, R. Rabbah and P. Suter, "Cloud-native, event-based programming for mobile applications," in Proc. of the International Conference on Mobile Software Engineering and Systems, pp. 287--288,2016.
[8]
Barcelona-Pons, P. Garcia-Lopez, "A. Ruiz, A. Gomez-Gomez,G. Pars, and M. Sanchez-Artigas, "Faas orchestration of parallel workloads," in Proc. of the 5th International Workshop on Serverless Computing, pp. 25--30, 2019.
[9]
E. Bisong, "Kubeflow and kubeflow pipelines," in Building Machine Learning and Deep Learning Models on Google Cloud Platform, pp. 671--685, Springer, 2019.
[10]
A. Arjona, P. G. Lopez, J. Sampe, A. Slominski, and L. Villard, "Trig-gerflow: Trigger-based orchestration of serverless workflows,"Future Generation Computer Systems, 2021.
[11]
Erwin van Eyk, Alexandru Iosup, Cristina L. Abad, Johannes Grohmann, and Simon Eismann. 2018. A SPEC RG Cloud Group's Vision on the Performance Challenges of FaaS Cloud Architectures. In Companion of the 2018 ACM/SPEC International Conference on Performance Engineering (ICPE '18). Association for Computing Machinery, New York, NY, USA, 21--24.
[12]
López, P.G., Sánchez-Artigas, M., París, G., Pons, D.B., Ollobarren, Á.R. and Pinto, D.A., 2018, December. Comparison of faas orchestration systems. In 2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion) (pp. 148--153). IEEE.
[13]
Nilanjan Daw, Umesh Bellur, and Purushottam Kulkarni. 2021. Speedo: Fast dispatch and orchestration of serverless workflows. Proceedings of the ACM Symposium on Cloud Computing. Association for Computing Machinery, New York, NY, USA, 585--599.
[14]
Malawski, Maciej, et al. "Serverless execution of scientific workflows: Experiments with hyperflow, aws lambda and google cloud functions." Future Generation Computer Systems 110 (2020): 502--514.
[15]
Ristov, Sasko, Stefan Pedratscher, and Thomas Fahringer. "AFCL: An abstract function choreography language for serverless workflow specification." Future Generation Computer Systems 114 (2021): 368--382.
[16]
John, Aji, et al. "SWEEP: accelerating scientific research through scalable serverless workflows." Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing Companion. 2019.
[17]
Zhang, Haoran, et al. "Fault-tolerant and transactional stateful serverless workflows." 14th USENIX Symposium on Operating Systems Design and Implementation (OSDI20), 2020.
[18]
Burckhardt, Sebastian, et al. "Serverless workflows with durable functions and netherite." arXiv preprint arXiv:2103.00033 (2021
[19]
Kousiouris, G., Ambroziak, S., Costantino, D., Tsarsitalidis, S., Boutas, E., Mamelli, A. and Stamati, T., 2022. Combining Node-RED and Openwhisk for Pattern-based Development and Execution of Complex FaaS Workflows. arXiv preprint arXiv:2202.09683.

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cover image ACM Conferences
ICPE '22: Companion of the 2022 ACM/SPEC International Conference on Performance Engineering
July 2022
166 pages
ISBN:9781450391597
DOI:10.1145/3491204
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Published: 19 July 2022

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Author Tags

  1. faas
  2. openwhisk
  3. orchestration
  4. overhead
  5. performance
  6. serverless

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  • Research-article

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  • European Commission H2020 PHYSICS

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ICPE '22

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ICPE '22 Paper Acceptance Rate 14 of 58 submissions, 24%;
Overall Acceptance Rate 252 of 851 submissions, 30%

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