Performance Analysis and Optimization of Amazon Web Service Lambda Functions in Serverless Systems
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Science | India | Volume 13 Issue 11, November 2024 | Popularity: 5 / 10


     

Performance Analysis and Optimization of Amazon Web Service Lambda Functions in Serverless Systems

Dr. Ima Hussain


Abstract: This article explores the working model of AWS Lambda functions and provides a step-by-step guide on creating Lambda functions for different use cases. AWS Lambda is a serverless computing service offered by Amazon Web Services (AWS), allowing developers to run code without the need for provisioning or managing servers. This research paper explores the potential of serverless computing, with a focus on building a robust working model utilizing AWS Lambda, a leading serverless computing platform. The paper delves into the key concepts of serverless architecture, highlighting its benefits, challenges, and practical applications. Through a comprehensive examination of AWS Lambda, the research aims to provide insights into designing and implementing efficient serverless solutions. The study includes real-world use cases, best practices, and performance considerations, offering a practical guide for developers and organizations seeking to harness the power of serverless computing in their applications. The study demonstrates that a modified formula for calculating non-zero demand averages significantly improves forecasting accuracy for intermittent demand data in serverless environments.


Keywords: AWS Lambda function, Serverless function, Amazon EC2


Edition: Volume 13 Issue 11, November 2024


Pages: 277 - 282


DOI: https://www.doi.org/10.21275/SR241101122450



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Dr. Ima Hussain, "Performance Analysis and Optimization of Amazon Web Service Lambda Functions in Serverless Systems", International Journal of Science and Research (IJSR), Volume 13 Issue 11, November 2024, pp. 277-282, https://www.ijsr.net/getabstract.php?paperid=SR241101122450, DOI: https://www.doi.org/10.21275/SR241101122450