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Cost optimization strategies for micro services in AWS: Managing resource consumption and scaling efficiently
Independent Researcher, Sterling, Virginia, USA.
Research Article
International Journal of Science and Research Archive, 2023, 10(02), 1255-1266.
Article DOI: 10.30574/ijsra.2023.10.2.0921
Publication history:
Received on 01 October 2023; revised on 13 November 2023; accepted on 16 November 2023
Abstract:
Microservices architecture has become the new standard for cloud computing since it provides scalability tools and flexibility options and enhanced resilience features. The deployment of Microservices in Amazon Web Services encounters substantial difficulties with cost management mainly because of its elastic resource distribution and scaling requirements. Research investigates cost reduction approaches for AWS microservices which includes automatic scaling mechanisms with serverless technology and extracting the right balance and organizing containers and distributing workloads based on expense considerations. A detailed review of literature explores present methods for reducing cloud expenses together with performance impact evaluation and identification of optimal cost-reduction approaches. The study follows real deployments which confirm that implementing hybrid cost optimization through multiple approaches delivers the best results for managing performance along with cost expenditures. Organizations that establish automation together with predictive scaling and workload distribution strategies succeed in attaining lasting cost reductions while preserving operational effectiveness. The analysis demonstrates how organizations must maintain persistent cost evaluation together with scalable infrastructure decisions using artificial intelligence systems to achieve balance between system availability and operational efficiency and financial cost management. Businesses can achieve optimal microservices performance in AWS through simultaneous implementation of multi-dimensional cost management strategies along with serverless solutions and correct selection of compute resources and workload management through container orchestration systems. Research into AI-based cost prediction technologies and automation processes should be conducted to enhance cloud environment cost reduction capabilities. The research delivers essential knowledge that helps organizations enhance microservices performance in AWS platforms.
Keywords:
AWS; Microservices; Cost Optimization; Auto-Scaling; Serverless Computing; Container Orchestration; Predictive Scaling; Cloud Cost Management
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
