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Serverless Architectures: A Comparative Study of Performance, Scalability, and Cost in Cloud-native Applications
Subject area: Science,Engineering and Technology · Area of research: Cloud-native Applications
Abstract
Serverless architecture has emerged as a revolutionary paradigm in cloud computing, offering a cost-efficient, scalable, and performance-driven solution for modern cloud-native applications. This paper provides a comprehensive comparative analysis of serverless computing across three critical dimensions: performance, scalability, and cost. By examining the offerings of major cloud providers?AWS Lambda, Azure Functions, and Google Cloud Functions?this study highlights key differences in their operational characteristics, pricing models, and real-world applicability. The paper begins with an overview of serverless computing, emphasizing its core principles, benefits, and limitations. Subsequently, a detailed comparison of performance metrics, including latency, cold start behavior, and concurrency handling, is presented to showcase the suitability of serverless solutions for diverse workloads. Scalability is analyzed by evaluating the auto-scaling mechanisms of these platforms under varying traffic intensities, demonstrating their ability to meet dynamic demand patterns effectively. Additionally, a cost analysis reveals insights into pricing structures, highlighting hidden costs and the economic implications of serverless adoption for small-scale and large-scale applications. Real-world case studies are incorporated to illustrate the practical applications of serverless architectures in domains such as e-commerce, IoT, artificial intelligence (AI), and media processing. Visual aids, including tables and graphs, provide a clear and concise representation of the comparative data, offering actionable insights for decision-makers. This study concludes by discussing best practices for adopting serverless architectures, strategies for optimizing performance and cost, and emerging trends such as cold start optimization and the integration of serverless with edge computing. The findings aim to guide organizations in leveraging serverless architectures effectively to achieve operational excellence in cloud-native ecosystems.
References
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How to cite this paper
@article{1702888,
author = {Naveen Kodakandla},
title = {Serverless Architectures: A Comparative Study of Performance, Scalability, and Cost in Cloud-native Applications},
journal = {Iconic Research And Engineering Journals},
year = {2021},
volume = {5},
number = {2},
pages = {136-150},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1702888.pdf},
abstract = {Serverless architecture has emerged as a revolutionary paradigm in cloud computing, offering a cost-efficient, scalable, and performance-driven solution for modern cloud-native applications. This paper provides a comprehensive comparative analysis of serverless computing across three critical dimensions: performance, scalability, and cost. By examining the offerings of major cloud providers?AWS Lambda, Azure Functions, and Google Cloud Functions?this study highlights key differences in their operational characteristics, pricing models, and real-world applicability.
The paper begins with an overview of serverless computing, emphasizing its core principles, benefits, and limitations. Subsequently, a detailed comparison of performance metrics, including latency, cold start behavior, and concurrency handling, is presented to showcase the suitability of serverless solutions for diverse workloads. Scalability is analyzed by evaluating the auto-scaling mechanisms of these platforms under varying traffic intensities, demonstrating their ability to meet dynamic demand patterns effectively. Additionally, a cost analysis reveals insights into pricing structures, highlighting hidden costs and the economic implications of serverless adoption for small-scale and large-scale applications.
Real-world case studies are incorporated to illustrate the practical applications of serverless architectures in domains such as e-commerce, IoT, artificial intelligence (AI), and media processing. Visual aids, including tables and graphs, provide a clear and concise representation of the comparative data, offering actionable insights for decision-makers.
This study concludes by discussing best practices for adopting serverless architectures, strategies for optimizing performance and cost, and emerging trends such as cold start optimization and the integration of serverless with edge computing. The findings aim to guide organizations in leveraging serverless architectures effectively to achieve operational excellence in cloud-native ecosystems.},
month = {August},
}