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AWS Cost and Resource Optimization with Predictive Methods

Author

Listed:
  • Priyanka N. Dukare
  • Shreejay V. Rokde
  • Pradnya R. Sisale
  • Sudesh A. Bachwani

Abstract

The monitoring and analysis of public clouds is gaining momentum due to their widespread exploitation by individual users, researchers, and companies for daily tasks. This paper proposes an algorithm for optimizing the cost and utilization of a set of running Amazon EC2 instances by resizing them appropriately. The algorithm, named Cost and Utilization Optimization (CUO) algorithm, receives information regarding the current set of instances used (their number, type, utilization) and proposes a new set of instances for serving the same load, so as to minimize cost and maximize utilization, or increase performance efficiency. CUO is integrated into Smart cloud Monitoring (SuMo), an open-source tool developed by the authors for collecting and analyzing monitoring data from Amazon Web Services (AWS). A number of experiments are performed using input data that correspond to realistic AWS configuration scenarios, which exhibit the benefits of the CUO algorithm.

Suggested Citation

  • Priyanka N. Dukare & Shreejay V. Rokde & Pradnya R. Sisale & Sudesh A. Bachwani, 2025. "AWS Cost and Resource Optimization with Predictive Methods," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 12(5), pages 285-292, October.
    • Handle: RePEc:etm:ijsrst:v12:y2025:i5:id:1199
    DOI: 10.32628/IJSRST25125132
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