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All Journal Bulletin of Social Informatics Theory and Application
Arifin, Muh Awal
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Computer Science & IT Social Sciences

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Optimizing AWS lambda code execution time in amazon web services Arifin, Muh Awal; Satra, Ramdan; Syafie, Lukman; Nidhom , Ahmad Mursyidun
Bulletin of Social Informatics Theory and Application Vol. 7 No. 1 (2023)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v7i1.609

Abstract

One of the problems in providing infrastructure is the lack of interest in managing infrastructure. AWS Lambda is a FaaS (Function as a Service) service that allows users to run code automatically in an environment managed by Amazon Web Services. In this study, the method used is to collect data on code execution time at various input sizes, then perform an analysis of the factors that affect execution time. Furthermore, optimization is carried out by selecting the appropriate memory size and proper coding techniques to improve performance. The results show that optimizing memory size and coding can improve code execution time performance by up to 30%, depending on the type of service used. This can help AWS Lambda users improve code performance and save on operational costs.
Co-Authors Nidhom, Ahmad Mursyidun Ramdan Satra Syafie, Lukman