OPTIMIZING CLOUD COMPUTING PERFORMANCE: A COMPREHENSIVE FRAMEWORK OF STRATEGIES AND BEST PRACTICES
Cloud computing has revolutionized the IT landscape, offering unprecedented scalability and flexibility. However, optimizing performance in cloud environments remains a complex challenge. This comprehensive study explores multifaceted strategies for enhancing cloud computing efficiency, encompassing architecture design, resource management, security, and DevOps practices. We present a systematic framework that integrates auto-scaling mechanisms, load balancing techniques, and multi-region deployments to ensure scalability and resilience. Our analysis extends to cost-effective resource allocation, leveraging reserved and spot instances, while emphasizing the critical role of continuous monitoring and optimization. We further examine the interplay between performance and security, proposing best practices for identity management and data protection that do not compromise system efficiency. The article also highlights the significance of automation and Infrastructure as Code (IaC) in maintaining consistent, high-performance cloud environments. Through case studies of large-scale implementations, we demonstrate the practical application of these strategies, revealing significant improvements in system responsiveness, resource utilization, and cost-efficiency. This article contributes to the growing body of knowledge on cloud optimization, offering valuable insights for practitioners and researchers alike in navigating the complexities of modern cloud architectures.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-09-27
- DOI
- https://doi.org/10.5281/zenodo.13851329
- Primary Topic
- Cloud Computing and Resource Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00