OPTIMIZATION OF INFRASTRUCTURE IN CLOUD-BASED SAAS QUEUE SYSTEM DEVELOPMENT

• Main Author: Rey Shazni Helmi, Muhammad
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/83526
• Institution: Institut Teknologi Bandung

Stability and performance are crucial pillars in supporting the success of an e-commerce website. Instability and crashes can reduce user interest and negatively impact sales. Moreover, page loading speed plays a vital role in determining sales conversion rates. This study aims to identify the optimal cloud infrastructure to support an efficient Software-as- a-Service (SaaS) queuing system, enhance cybersecurity, and evaluate the impact of cloud service provider selection on the system's operational costs. This research employs problem analysis, solution design, implementation, and evaluation methods. We explore various strategies to manage demand surges, reduce crash risks, and assess infrastructure cost efficiency. The proposed solution includes implementing scalable and secure cloud architectures and utilizing four Cloud Service Providers: Google Cloud Platform (GCP), Amazon Web Services (AWS), Microsoft Azure, and Alibaba Cloud. Testing was conducted to evaluate the performance of the implemented system, focusing on cost efficiency, security, and adaptability to workload changes. Test results show that implementing an optimal cloud infrastructure can enhance the stability and performance of the SaaS queuing system. The developed system efficiently handles demand surges and minimizes crash risks. This study provides insights into selecting and implementing appropriate cloud infrastructure to support a SaaS queuing system. Additionally, this research evaluates the impact of cloud service provider selection on system operational costs. Security testing was also conducted to ensure that the implemented system can protect user data from relevant cybersecurity threats.