Increasing Scalability and Resource Utilization in Cloud Computing with Load Management via Docker
Keywords:
Docker, Load management, Cloud Computing, Scalability
Abstract
This research aims to study and develop an approach to increase scalability and resource utilization within cloud computing systems by implementing Docker for load management. The study will focus on analyzing the efficacy of Containerization techniques for application isolation and the utilization of robust load balancing mechanisms to ensure optimal consumption of cloud resources . The methodology includes practical testing in a simulated environment to compare the performance of Docker-based load management against traditional approaches. The expected outcome is the derivation of a concrete framework and best practices guidelines that enable cloud service providers and users to significantly enhance operational efficiency and reduce costs. The findings reveal that the Containerization management techniques developed in this study significantly reduce system vulnerabilities, enhance data security, and improve the efficiency of server administration. These outcomes contribute positively to supporting digital learning initiatives within the university. The research involved a diverse group of respondents who completed a satisfaction assessment questionnaire. This group included 1,600 university students from Rajabhat University Suan Sunandha during the first semester of the academic year 2023, along with 25 staff members from the General Education Office. Most participants were students, constituting 98.46% of the total respondents, while staff members comprised 1.54%. Satisfaction Assessment: The study assessed user satisfaction with various aspects of the cloud-based question and answer repository technology. The evaluation criteria covered essential factors related to system performance, usability, and service provision. The results, as presented in Table 2, demonstrated consistently high levels of satisfaction across all evaluated criteria. The average scores ranged from 4.44 to 4.68, with standard deviations of 0.47 to 0.50. Overall, the users expressed "Very Satisfied" levels of satisfaction, with an impressive overall satisfaction score of 4.52.
Published
2026-04-01
Section
Articles