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Abstrakty
AWS Lambda is a widely used serverless computing service that executes code in response to events and automatically manages the underlying hardware resources. Lambda integrates with many AWS services and offers two processor architecture options for running functions: x86_64 (CISC) and arm64 (RISC). Determining the optimal settings for the lowest cost or execution time is not straightforward due to performance variations between processor architectures, the wide range of configuration options, and the workload-dependent nature of function execution efficiency. We developed a tool which we used in experiments examining different configurations and processors architectures for several algorithms. In this paper two of such experiments are presented in detail.
Słowa kluczowe
Rocznik
Tom
Strony
11
Opis fizyczny
Bibliogr. 27 poz., rys.
Twórcy
autor
- Institute of Computer Science, Warsaw University of Technology, Poland
autor
- Institute of Computer Science, Warsaw University of Technology, Poland
Bibliografia
- [1] P. Mell and T. Grance, “The NIST Definition of Cloud Computing,” National Institute of Standards and Technology (NIST), NIST Special Publication 800-145, Sep. 2011. https://doi.org/10.6028/NIST.SP.800-145
- [2] M. Armbrust et al., “A view of cloud computing,” Commun. ACM, vol. 53, no. 4, pp. 50-58, Apr. 2010. https://doi.org/10.1145/1721654.1721672.
- [3] “What is AWS Lambda? - AWS Lambda.” Accessed: Jan., 2025. https://docs.aws.amazon.com/lambda/latest/dg/welcome.html
- [4] A. Zdanowski, ”LambdaLab: a tool for performance evaluation and configuration optimization of AWS Lambda functions, Bachelor’s Thesis, March 2025, Inst. of Computer Science Warsaw Univ. of Technology
- [5] “Comparing AWS Lambda Arm vs. x86 Performance, Cost, and Analysis AWS Partner Network (APN) Blog.” Jan., 2025. https://aws.amazon.com/blogs/apn/comparing-aws-lambda-arm-vs-x86-performance-cost-and-analysis-2
- [6] A. Marinos and G. Briscoe, “Community Cloud Computing,” vol. 5931, 2009. pp. 472-484. https://doi.org/10.1007/978-3-642-10665-1_43
- [7] Z. Li et al., “The Serverless Computing Survey: A Technical Primer for Design Architecture,” ACM Comput. Surv., vol. 54, no. 10s, pp. 1-34, Sep. 2022. https://doi.org/10.1145/3508360.
- [8] E. Jonas et al., “Cloud Programming Simplified: A Berkeley View on Serverless Computing,” Feb. 09, 2019, arXiv: arXiv:1902.03383. https://doi.org/10.48550/arXiv.1902.03383.
- [9] J. Scheuner and P. Leitner, “Function-as-a-Service Performance Evaluation: A Multivocal Literature Review,” J. Syst. Softw., vol. 170, p. 110708, Dec. 2020. https://doi.org/10.1016/j.jss.2020.110708.
- [10] “Intel 8086,” Wikipedia. Jan. 27, 2025. https://en.wikipedia.org/wiki/Intel_8086
- [11] “ARM architecture family,” Wikipedia. Feb. 01, 2025. https://en.wikipedia.org/wiki/ARM_architecture_family
- [12] “ARM Processor - AWS Graviton Processor - AWS,” Amazon Web Services, Inc. Feb. 03, 2025. https://aws.amazon.com/ec2/graviton/
- [13] “Selecting and configuring an instruction set architecture for your Lambda function - AWS Lambda.” Feb. 03, 2025. https://docs.aws.amazon.com/lambda/latest/dg/foundation-arch.html
- [14] “Serverless Computing - AWS Lambda Pricing - Amazon Web Services.” Feb. 03, 2025. https://aws.amazon.com/lambda/pricing/.
- [15] B. Ayala, Bryan-0/aws-lambda-benchmark-tool. (Jul. 25, 2024). Python. Accessed: Feb. 04, 2025. https://github.com/Bryan-0/aws-lambda-benchmark-tool
- [16] theam/aws-lambda-benchmark. (Dec. 27, 2024). The Agile Monkeys. Accessed: Feb. 04, 2025. https://github.com/theam/aws-lambda-benchmark
- [17] T. Yu et al., “Characterizing serverless platforms with serverless bench,” in Proceedings of the 11th ACM Symposium on Cloud Computing, Virtual Event USA: ACM, Oct. 2020, pp. 30-44. https://doi.org/10.1145/3419111.3421280
- [18] P. Maissen, P. Felber, P. Kropf, and V. Schiavoni, “FaaSdom: a benchmark suite for serverless computing,” in Proc. of the 14th ACM Int. Conf. on Distributed and Event-based Systems, Montreal Quebec Canada: ACM, Jul. 2020, pp. 73-84. https://doi.org/10.1145/3401025.3401738
- [19] hjmart93, hjmart93/ServerlessBenchmark. (Nov. 20, 2023). Python. Feb. 04, 2025. https://github.com/hjmart93/ServerlessBenchmark
- [20] A. Casalboni, alexcasalboni/aws-lambda-power-tuning. Feb. 04, 2025. JavaScript. https://github.com/alexcasalboni/aws-lambda-power-tuning.
- [21] H. Martins, F. Araujo, and P. R. Da Cunha, “Benchmarking Serverless Computing Platforms,” J. Grid Computing, vol. 18, no. 4, pp. 691-709, Dec. 2020. https://doi.org/10.1007/s10723-020-09523-1
- [22] M. Sadaqat, M. Sánchez-Gordón, and R. Colomo-Palacios, “Benchmarking Serverless Computing: Performance and Usability,” J. Inf. Technol. Res. JITR, vol. 15, no. 1, pp. 1-17, 2022. https://doi.org/10.4018/JITR.299374
- [23] “AWS Lambda Benchmarking: Rust, Scala, Python, TypeScript - Xebia.” Feb., 2025. https://xebia.com/blog/aws-lambda-benchmarking/
- [24] J. Wen, Z. Chen, F. Sarro, and X. Liu, “SuperFlow: Performance Testing for Serverless Computing,” Jun. 2023, arXiv:2306.01620. Oct. 2024. http://arxiv.org/abs/2306.01620
- [25] X. Chen, L.-H. Hung, R. Cordingly, and W. Lloyd, “X86 vs. ARM64: An Investigation of Factors Influencing Serverless Performance,” in Proc. of the 9th Int. Workshop on Serverless Computing, Bologna Italy: ACM, Dec. 2023, pp. 7-12. https://doi.org/10.1145/3631295.3631394
- [26] I. Bluemke, A. Zdanowski “Experiment evaluating configurations of AWS Lambda functions” submitted to “Practical Aspects of Software Engineering”, 51st Euromicro Conf. Series on Soft. Eng. and Advanced Applications, September 2025
- [27] “hashlib — Secure hashes and message digests,” Python documentation. Feb. 08, 2025. https://docs.python.org/3/library/hashlib.html
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
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