E-Commerce Platform Optimization via Cloud Monitoring: A Case Study in Operational Excellence and Digital Transformation

Authors

  • Maneesh Singh

Keywords:

Cloud Monitoring, E-Commerce Optimization, Aws Cloudwatch, Observability, Platform Performance

Abstract

The proliferation of e-commerce has increased the demands for performance management in e-retailing, where reliability‚ scalability and operational efficiency are key competitiveness factors. In this article, we describe how a high-traffic e-retailer implemented a single observability platform for its front-end, inventory management and payment gateway systems, leveraging the Amazon Web Services CloudWatch and New Relic platforms to move from ad hoc, siloed monitoring to a data-based governance of the platform in real time. During a demanding 96-hour trading period, smart dashboards, prevailing automatic scaling, and log analytics helped reduce cart abandonment rates by 30%, improve page load times by 25%, and enable 99.97% uptime availability. The presentation also addresses the technical and organizational issues experienced and resolved during the implementation with its array of disparate third-party vendor data unified via API-driven synthetic monitors. Synthesizing cloud computing theory, recent literature on cloud observability, and empirical case studies, we propose the Instrument-Unify-Automate-Optimize (IUAO) framework as a structured and generalizable strategy for addressing cloud observability in e-commerce firms. We conclude by discussing implications of the findings for platform architects‚ operations teams‚ digital transformation professionals‚ and cloud platform providers․

DOI: https://doi.org/10.17762/ijisae.v14i1s.8240

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Published

07.05.2026

How to Cite

Maneesh Singh. (2026). E-Commerce Platform Optimization via Cloud Monitoring: A Case Study in Operational Excellence and Digital Transformation. International Journal of Intelligent Systems and Applications in Engineering, 14(1s), 744–749. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/8240

Issue

Vol. 14 No. 1s (2026)

Section

Research Article

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