A Comprehensive Framework for Enhancing Operations Development in Cloud Computing Through Scalable Architectures, Intelligent Automation, and Adaptive Resource Management
Keywords:
Cloud computing, operations development, scalable architectures, intelligent automation, adaptive resource management, AI-driven optimization, cloud efficiencyAbstract
Cloud computing has revolutionized operations development by enabling scalable architectures, intelligent automation, and adaptive resource management. However, challenges such as inefficient resource allocation, security vulnerabilities, and high operational costs persist. This paper presents a comprehensive framework that integrates scalable architectures, AI-driven automation, and adaptive resource management techniques to enhance operational efficiency in cloud computing. The proposed framework aims to improve scalability, optimize cloud performance, and minimize infrastructure costs. A systematic literature review is conducted to analyze past advancements and identify research gaps. Furthermore, experimental results and graphical analyses demonstrate the effectiveness of the proposed model in improving cloud operations. This study contributes to the ongoing evolution of cloud computing by presenting a practical and optimized approach to operations development.
References
Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., et al. (2010). A view of cloud computing. Communications of the ACM, 53(4), 50–58.
Omkar Reddy Polu. (2024). AI-Based Fake News Detection Using NLP. International Journal of Artificial Intelligence & Machine Learning, 3(2), 231–239. doi: https://doi.org/10.34218/IJAIML_03_02_019
Buyya, R., Yeo, C. S., & Venugopal, S. (2015). Market-oriented cloud computing: Vision, hype, and reality for delivering IT services. Future Generation Computer Systems, 25(6), 599–616.
Omkar Reddy Polu. (2024). AI-Driven Prognostic Failure Analysis for Autonomous Resilience in Cloud Data Centers. International Journal of Cloud Computing (IJCC), 2(2), 27–37. doi: https://doi.org/10.34218/IJCC_02_02_003
Ghobaei-Arani, M., et al. (2018). Resource management approaches in cloud computing. Computing Surveys, 51(6), 1-36.
Omkar Reddy Polu, Cognitive Cloud-Orchestrated AI Chatbots For Real-Time Customer Support Optimization, International Journal of Computer Applications (IJCA), 5(2), 2024, pp. 20–29 doi: https://doi.org/10.34218/IJCA_05_02_003
Sharma, S., Kumar, R., & Varma, S. (2020). Elasticity in cloud computing. Journal of Cloud Computing, 9(1), 12-24.
Vinay, S. B. (2024). A comprehensive analysis of artificial intelligence applications in legal research and drafting. International Journal of Artificial Intelligence in Law (IJAIL), 2(1), 1–7.
Omkar Reddy Polu, AI Optimized Multi-Cloud Resource Allocation for Cost-Efficient Computing, International Journal of Information Technology (IJIT), 5(2), 2024, pp. 26-33 doi: https://doi.org/10.34218/IJIT_05_02_004
Vinay, S. B. (2024). Identifying research trends using text mining techniques: A systematic review. International Journal of Data Mining and Knowledge Discovery (IJDMKD), 1(1), 1–11.
Abdelaziz, A., et al. (2022). Intelligent cloud automation using AI. IEEE Transactions on Cloud Computing, 10(3), 45-57.
Omkar Reddy Polu, Machine Learning for Predicting Software Project Failure Risks, International Journal of Computer Engineering and Technology (IJCET), 15(4), 2024, pp. 950-959.
Vasudevan, K. (2024). The influence of AI-produced content on improving accessibility in consumer electronics. Indian Journal of Artificial Intelligence and Machine Learning (INDJAIML), 2(1), 1–11.
Wang, J., et al. (2023). AI-driven workload balancing for cloud environments. Elsevier Future Technologies Journal, 15(4), 67-89.
Omkar Reddy Polu, Reinforcement Learning for Autonomous UAV Navigation: Intelligent Decision-Making and Adaptive Flight Strategies, International Journal of Graphics and Multimedia (IJGM) 11(2), 2024, pp. 17-27 doi: https://doi.org/10.34218/IJGM_11_02_002
Ramachandran, K. K. (2024). The role of artificial intelligence in enhancing financial data security. International Journal of Artificial Intelligence & Applications (IJAIAP), 3(1), 1–11.
Hannah Jacob. (2023). Exploring Blockchain and Data Science for Next-Generation Data Security. International Journal of Computer Science and Information Technology Research , 4(2), 1-9.
Gupta, P.P. (2023). Applications of AI-driven data analytics for early diagnosis in complex medical conditions. International Journal of Engineering Applications of Artificial Intelligence, 1(2), 1–9.
Ramachandran, K. K. (2024). Data science in the 21st century: Evolution, challenges, and future directions. International Journal of Business and Data Analytics (IJBDA), 1(1), 1–13.
Jain, D.S. (2023). Computational Methods for Real-Time Epidemic Tracking and Public Health Management. International Journal of Computer Applications in Technology (IJCAT), 1(1), 1–6.
S. Krishnakumar. (2023). Scalability and Performance Optimization in Next-Generation Payment Gateways. International Journal of Computer Science and Engineering Research and Development (IJCSERD), 6(1), 9-16.
S.Sankara Narayanan and M.Ramakrishnan, Software As A Service: MRI Cloud Automated Brain MRI Segmentation And Quantification Web Services, International Journal of Computer Engineering & Technology, 8(2), 2017, pp. 38–48.
Nivedhaa, N. (2024). Software architecture evolution: Patterns, trends, and best practices. International Journal of Computer Sciences and Engineering (IJCSE), 1(2), 1–14.
Sankar Narayanan .S System Analyst, Anna University Coimbatore , 2010. PATTERN BASED SOFTWARE PATENT.International Journal of Computer Engineering and Technology (IJCET) -Volume:1,Issue:1,Pages:8-17.
Akshayapatra Lakshmi Harshini. (2021). A Comparative Study of UPI and Traditional Payment Methods: Efficiency, Accessibility, and User Adoption. International Journal of Computer Science and Engineering Research and Development (IJCSERD), 1(1), 10-16.
Sally Abba. (2022). AI in Fintech: Personalized Payment Recommendations for Enhanced User Engagement. INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY (IJRCAIT), 5(1), 13-20.
Nivedhaa, N. (2024). Towards efficient data migration in cloud computing: A comparative analysis of methods and tools. International Journal of Artificial Intelligence and Cloud Computing (IJAICC), 2(1), 1–16.
Sankar Narayanan .S, System Analyst, Anna University Coimbatore , 2010. INTELLECTUAL PROPERY RIGHTS: ECONOMY Vs SCIENCE &TECHNOLOGY. International Journal of Intellectual Property Rights (IJIPR) .Volume:1,Issue:1,Pages:6-10.
Rahmatullah Ahmed Aamir. (2023). Enhancing Security in Payment Processing through AI-Based Anomaly Detection. International Journal of Information Technology and Electrical Engineering (IJITEE), 12(6), 11-19.
Mukesh, V. (2024). A Comprehensive Review of Advanced Machine Learning Techniques for Enhancing Cybersecurity in Blockchain Networks. ISCSITR-International Journal of Artificial Intelligence, 5(1), 1–6.
Arano Prince. (2021). Developing Resilient Health Financing Models in Response to Emerging Global Health Threats. International Journal of Computer Science and Engineering Research and Development (IJCSERD), 11(1), 29-38.
Geoffrey Ellenberg. (2021). A Framework for Implementing Effective Security Controls in Cloud Computing Environments. International Journal of Computer Science and Information Technology Research , 2(1), 9-18.
Mukesh, V. (2022). Cloud Computing Cybersecurity Enhanced by Machine Learning Techniques. Frontiers in Computer Science and Information Technology (FCSIT), 3(1), 1-19
Mohammed Jassim, A Multi-Layered Approach to Addressing Security Vulnerabilities in Internet of Things Architectures, International Journal ofArtificial Intelligence and Applications (IJAIAP), 2020, 1(1), pp. 21-27.
Das, A.M. (2022). Using Genetic Algorithms to Optimize Cyber Security Protocols for Healthcare Data Management Systems. International Journal of Computer Science and Applications, 1(1), 1–5.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Sakthi velan M (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
