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Performance evaluation of heterogeneous cloud functions
Author(s) -
Figiela Kamil,
Gajek Adam,
Zima Adam,
Obrok Beata,
Malawski Maciej
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4792
Subject(s) - cloud computing , computer science , suite , benchmarking , ibm , function (biology) , operating system , resource (disambiguation) , distributed computing , database , computer network , materials science , archaeology , marketing , evolutionary biology , biology , business , history , nanotechnology
Summary Cloud Functions, often called Function‐as‐a‐Service (FaaS), pioneered by AWS Lambda, are an increasingly popular method of running distributed applications. As in other cloud offerings, cloud functions are heterogeneous due to variations in underlying hardware, runtime systems, as well as resource management and billing models. In this paper, we focus on performance evaluation of cloud functions, taking into account heterogeneity aspects. We developed a cloud function benchmarking framework, consisting of one suite based on Serverless Framework and one based on HyperFlow. We deployed the CPU‐intensive benchmarks: Mersenne Twister and Linpack. We measured the data transfer times between cloud functions and storage, and we measured the lifetime of the runtime environment. We evaluated all the major cloud function providers: AWS Lambda, Azure Functions, Google Cloud Functions, and IBM Cloud Functions. We made our results available online and continuously updated. We report on the results of the performance evaluation, and we discuss the discovered insights into resource allocation policies.