Exploring the Efficiency of Docker Containers in Cloud-Based Application Deployment Using AWS

The quick evolution of web apps has revolutionised people’s daily lives and careers. Hybrid clouds are becoming more common as a means of accessing resources on demand via cloud computing. Using Docker as its foundation, this article presents a framework that can automatically grow web applications in a hybrid cloud. Web applications are deployed on hybrid cloud hosts, and their resources may be adjusted by adding or removing docker containers, a technique used in this research. This study explores the efficiency of Docker containers in cloud-based application deployment on Amazon Web Services (AWS) by comparing two primary deployment models, Amazon EC2 and Amazon ECS. Performance testing was conducted using Apache JMeter, and development was supported by Visual Studio Code. Performance metrics, such as throughput, response time and error rate, were measured across varying instance types and configurations. The results also depicted the variation in performances; in the step load condition, EC2 has an ultra-low error percentage of $0.01 \%$ with a mean throughput rate of 35.89 operation/sec, and ECS has a higher throughput rate of 80.95 operation/sec but with a higher error percentage of 2.22 are observed. Even under peak load, their EC2’s rejection rate went to $2.93 \%$ and throughput reduced to 25.41, though ECS achieved a better high throughput of 34.45 per second operations at a slightly higher rejection rate of $8.86 \%$. These results indicate the ideal cost benefits of Docker container stand alone in achieving larger scale and better throughout relative to VM deployments that provide fewer errors and better reliability in large traffic loads. Thus, this work presents real-world experience useful for organisations that seek to enhance IaaS resource performance and elasticity in AWS environments.

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Publication Details

Published
2025-02-21
DOI
https://doi.org/10.1109/mpseciceta64837.2025.11118780
Citations
1
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
3.25
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article

Exploring the Efficiency of Docker Containers in Cloud-Based Application Deployment Using AWS

Sandeep K. Gupta, Vashudhar Sai Thokala
1 citations
Cloud Computing and Resource Management
3.25
article

Exploring the Efficiency of Docker Containers in Cloud-Based Application Deployment Using AWS

Sandeep K. Gupta, Vashudhar Sai Thokala
article en
1 citations

Abstract

The quick evolution of web apps has revolutionised people’s daily lives and careers. Hybrid clouds are becoming more common as a means of accessing resources on demand via cloud computing. Using Docker as its foundation, this article presents a framework that can automatically grow web applications in a hybrid cloud. Web applications are deployed on hybrid cloud hosts, and their resources may be adjusted by adding or removing docker containers, a technique used in this research. This study explores the efficiency of Docker containers in cloud-based application deployment on Amazon Web Services (AWS) by comparing two primary deployment models, Amazon EC2 and Amazon ECS. Performance testing was conducted using Apache JMeter, and development was supported by Visual Studio Code. Performance metrics, such as throughput, response time and error rate, were measured across varying instance types and configurations. The results also depicted the variation in performances; in the step load condition, EC2 has an ultra-low error percentage of $0.01 \%$ with a mean throughput rate of 35.89 operation/sec, and ECS has a higher throughput rate of 80.95 operation/sec but with a higher error percentage of 2.22 are observed. Even under peak load, their EC2’s rejection rate went to $2.93 \%$ and throughput reduced to 25.41, though ECS achieved a better high throughput of 34.45 per second operations at a slightly higher rejection rate of $8.86 \%$. These results indicate the ideal cost benefits of Docker container stand alone in achieving larger scale and better throughout relative to VM deployments that provide fewer errors and better reliability in large traffic loads. Thus, this work presents real-world experience useful for organisations that seek to enhance IaaS resource performance and elasticity in AWS environments.

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Cloud Computing and Resource Management
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