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Harnessing Serverless Computing for Agile Cloud Application Development

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Serverless computing revolutionises cloud application development with elastic, cost-effective, scalable infrastructure management solutions. This research explores the adoption of serverless computing in agile cloud application development and its impacts on software delivery speed, scalability, and efficiency of operations. Serverless user authentication, data processing, and real-time analytics functions are supported in the experimental dataset and deployed on AWS Lambda, Google Cloud Functions, and Azure Functions. The experiments measure execution time, cost, latency, and concurrency. Python and Matplotlib are used to analyze the performance and plots. Graphviz was employed to generate a sequence diagram of the architecture. The findings show that serverless computing not only simplifies the development process but also maximizes the utilization of resources as it charges customers for utilized resources only. Two performance improvement graphs and two data tables are included to identify performance improvement and reduce costs when implementing the best serverless architectures. The results indicate serverless computing as a viable option for modern organizations that need flexible development approaches to suit the needs of agile digital environments. The paper ends by analysing the limitations and possible horizons of serverless computing in cloud app development.
Fernando Martins De Bulhão Publishing Company
Title: Harnessing Serverless Computing for Agile Cloud Application Development
Description:
Serverless computing revolutionises cloud application development with elastic, cost-effective, scalable infrastructure management solutions.
This research explores the adoption of serverless computing in agile cloud application development and its impacts on software delivery speed, scalability, and efficiency of operations.
Serverless user authentication, data processing, and real-time analytics functions are supported in the experimental dataset and deployed on AWS Lambda, Google Cloud Functions, and Azure Functions.
The experiments measure execution time, cost, latency, and concurrency.
Python and Matplotlib are used to analyze the performance and plots.
Graphviz was employed to generate a sequence diagram of the architecture.
The findings show that serverless computing not only simplifies the development process but also maximizes the utilization of resources as it charges customers for utilized resources only.
Two performance improvement graphs and two data tables are included to identify performance improvement and reduce costs when implementing the best serverless architectures.
The results indicate serverless computing as a viable option for modern organizations that need flexible development approaches to suit the needs of agile digital environments.
The paper ends by analysing the limitations and possible horizons of serverless computing in cloud app development.

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