Date of Graduation
Summer 8-15-2023
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Science
Thesis Chair
Dr. Jeong Yang
Abstract
This study analyzed the system features, usability, and performance of three serverless cloud computing platforms: Google Cloud’s Cloud Run, Amazon Web Service’s App Runner, and Microsoft Azure’s Container Apps. The analysis was conducted on a containerized mobile application designed to track real-time bus locations for San Antonio public buses on specific routes and provide estimated arrival times for selected bus stops. The study evaluated various system-related features, including service configuration, pricing, and memory & CPU capacity, along with performance metrics such as container latency, Distance Matrix API response time, and CPU utilization for each service. Easy-to-use usability was also evaluated by assessing the quality of documentation, a learning curve for be- ginner users, and a scale-to-zero factor. The results of the analysis revealed that Google’s Cloud Run demonstrated better performance and usability when com- pared to AWS’s App Runner and Microsoft Azure’s Container Apps. Cloud Run exhibited lower latency and faster response time for distance matrix queries. These findings provide valuable insights for selecting an appropriate serverless cloud ser- vice for similar containerized web applications.
Recommended Citation
Abraham, Anoop, "ANALYZING THE SYSTEM FEATURES, USABILITY, AND PERFORMANCE OF A CONTAINERIZED APPLICATION ON CLOUD COMPUTING SYSTEMS" (2023). Masters Theses. 9.
https://digitalcommons.tamusa.edu/masters_theses/9