We utilized Digital Ocean's cloud service, setting up three Linux virtual machines, each with 1vCPU, 1GB of memory, and a 10GB disk. The architecture included an API gateway for routing requests to a stateless application service backed by a database for storing application data. The application operates the service under a fluctuating workload generated by a load-testing script to simulate real-world usage scenarios. The target source or the application service is integrated with Prometheus, a monitoring tool for gathering system metrics.

DOI Link: 
10.21227/8wf2-2y40
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[1] Nutt Chairatana, Rathachai Chawuthai, "Cloud Stateless System Performance Metrics and Status", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/8wf2-2y40. Accessed: Dec. 12, 2024.
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Nutt Chairatana, Rathachai Chawuthai. (2024). Cloud Stateless System Performance Metrics and Status. IEEE Dataport. http://dx.doi.org/10.21227/8wf2-2y40
Nutt Chairatana, Rathachai Chawuthai, 2024. Cloud Stateless System Performance Metrics and Status. Available at: http://dx.doi.org/10.21227/8wf2-2y40.
Nutt Chairatana, Rathachai Chawuthai. (2024). "Cloud Stateless System Performance Metrics and Status." Web.
1. Nutt Chairatana, Rathachai Chawuthai. Cloud Stateless System Performance Metrics and Status [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/8wf2-2y40
Nutt Chairatana, Rathachai Chawuthai. "Cloud Stateless System Performance Metrics and Status." doi: 10.21227/8wf2-2y40