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Journal articles on the topic 'Hybrid cloud orchestration'

Author: Grafiati

Published: 7 June 2025

Last updated: 17 July 2025

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1

Voruganti, Kiran Kumar. "Orchestrating Multi-Cloud Environments for Enhanced Flexibility and Resilience." Journal of Technology and Systems 6, no. 2 (2024): 9–25. http://dx.doi.org/10.47941/jts.1810.

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Purpose: This paper examines the essential role of multi-cloud orchestration in navigating the complexities of the contemporary cloud computing landscape, aimed at optimizing the deployment and management of cloud resources across diverse environments. Methodology: Utilizing a systematic review of scholarly articles, industry reports, and case studies, including the Flexera 2021 State of the Cloud Report and insights from Gartner, alongside academic contributions from researchers like Jamshidi et al. and Garg et al., this study delves into the strategies and tools facilitating effective

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Natta, Prasanna Kumar. "AI-Powered Cloud Orchestration: Automating Multi-Cloud & Hybrid Cloud Workloads." European Journal of Computer Science and Information Technology 13, no. 8 (2025): 138–47. https://doi.org/10.37745/ejcsit.2013/vol13n8138147.

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AI-powered cloud orchestration revolutionizes how enterprises manage and optimize their multi-cloud and hybrid cloud environments. Integrating artificial intelligence into cloud management addresses complexity, manual intervention, and reactive problem-solving challenges that plague traditional orchestration methods. By implementing intelligent algorithms for resource allocation, workload balancing, predictive scaling, security enhancement, and self-healing capabilities, organizations can transform their cloud operations from manually-defined workflows to autonomous systems capable of continuo

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Bhanuprakash, Madupati. "Kubernetes for Multi-Cloud and Hybrid Cloud: Orchestration, Scaling, and Security Challenges." Journal of Scientific and Engineering Research 10, no. 6 (2023): 290–97. https://doi.org/10.5281/zenodo.14050147.

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Kubernetes enables organizations to manage applications globally, from multi-cloud to hybrid clouds. This paper presents challenges and solutions for workload orchestration, scaling, and security in such infrastructures. Running workloads across different cloud providers enables one to escape vendor lock-in and improve service availability. However, it leads to more complexity in terms of management and security. This paper will analyze the tendency of Kubernetes to orchestrate across multiple clouds in which it operates in a Multi-Cloud environment. It covers important solutions for scaling &

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Dmitry, Vasilenko and Mahesh Kurapati. "DYNAMIC TENANT PROVISIONING AND SERVICE ORCHESTRATION IN HYBRID CLOUD." International Journal on Cloud Computing: Services and Architecture (IJCCSA) 9, no. 2/3 (2022): 1. https://doi.org/10.5281/zenodo.7476019.

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The advent of container orchestration and cloud computing, as well as associated security and compliance complexities, make it challenging for the enterprises to develop robust, secure, manageable and extendable architectures which would be applicable to the public and private cloud. The main challenges stem from the fact that on-premises, private cloud and third-party, public cloud services often have seemingly different and sometimes conflicting requirements to tenant provisioning, service deployment, security and compliance and that can lead to rather different architectures which still hav

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Dmitry, Vasilenko, and Kurapati Mahesh. "Dynamic Tenant Provisioning and Service Orchestration in Hybrid Cloud." International Journal on Cloud Computing: Services and Architecture (IJCCSA) 9, no. 2/3 (2019): 1–10. https://doi.org/10.5281/zenodo.3483491.

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The advent of container orchestration and cloud computing, as well as associated security and compliance complexities, make it challenging for the enterprises to develop robust, secure, manageable and extendable architectures which would be applicable to the public and private cloud. The main challenges stem from the fact that on-premises, private cloud and third-party, public cloud services often have seemingly different and sometimes conflicting requirements to tenant provisioning, service deployment, security and compliance and that can lead to rather different architectures which still hav

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Dathwal, Prashant. "Frameworks for implementing AI-driven cloud orchestration." American Journal of Engineering and Technology 07, no. 06 (2025): 81–87. https://doi.org/10.37547/tajet/volume07issue06-08.

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This article presents an analysis of frameworks designed for AI-driven orchestration of cloud resources, focusing on contemporary methods and architectural models aimed at improving the efficiency, adaptability, and energy performance of cloud computing environments. The study includes a comprehensive review of applied machine learning techniques, deep learning, reinforcement learning algorithms, evolutionary algorithms, and hybrid approaches used for workload prediction, resource allocation optimization, and autonomous decision-making. The paper identifies key integration challenges, computat

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Pasupuleti, Murali Krishna. "Container Orchestration in Multi-Cloud Environments: A Performance Evaluation." International Journal of Academic and Industrial Research Innovations(IJAIRI) 05, no. 06 (2025): 327–40. https://doi.org/10.62311/nesx/rphcrcscrcec2.

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The emergence of multi-cloud strategies has significantly transformed how enterprises deploy and manage applications, particularly through the use of container orchestration platforms like Kubernetes. This study investigates the performance efficiency of container orchestration in multi-cloud environments by evaluating key parameters such as deployment time, resource utilization, latency, scalability, and fault tolerance. A comparative analysis is conducted using Google Kubernetes Engine (GKE), Amazon Elastic Kubernetes Service (EKS), and Azure Kubernetes Service (AKS), supported by statistica

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Srikanth Gurram. "Cross-domain integration for hybrid cloud management: Innovations and future directions." World Journal of Advanced Engineering Technology and Sciences 15, no. 1 (2025): 1755–61. https://doi.org/10.30574/wjaets.2025.15.1.0405.

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Cross-domain integration for hybrid cloud management presents a significant paradigm shift in how organizations orchestrate resources, secure data, and maintain governance across heterogeneous environments. This article explores the transformative impact of emerging technologies that enable seamless integration across public cloud providers, private clouds, and on-premise infrastructure. Integrating artificial intelligence into orchestration platforms has revolutionized workload placement optimization and resource allocation in hybrid environments. At the same time, Zero Trust security framewo

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Nikhil, Bhagat. "Optimizing Performance, Cost-Efficiency, and Flexibility through Hybrid Multi-Cloud Architectures." Journal of Scientific and Engineering Research 11, no. 4 (2024): 372–79. https://doi.org/10.5281/zenodo.14273093.

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Cloud Computing is the foundation of every modern company that is scalable, adaptable and economical. Hybrid multi-cloud environments, which combine private clouds, public clouds, and multiple cloud providers, represent the next generation for scaling cloud infrastructures. Hybrid cloud architecture lets organizations reap the security and control benefits of a private cloud while also taking advantage of the scalability and cost efficiency of a public cloud. Meanwhile, multi-cloud models avoid vendor lock-in, provide risk mitigation, and enable organizations to choose the best options from mu

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Katta, Tejaswi Bharadwaj. "AI-Enhanced Orchestration in Hybrid Cloud Enterprise Integration: Transforming Enterprise Data Flows." European Journal of Computer Science and Information Technology 13, no. 9 (2025): 92–103. https://doi.org/10.37745/ejcsit.2013/vol13n992103.

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Hybrid cloud enterprise integration presents a formidable challenge as organizations strive to harmonize legacy systems with modern, cloud-native applications. This article investigates the potential of AI-enhanced orchestration to dynamically manage integration workflows across such heterogeneous environments. By embedding artificial intelligence within orchestration platforms, enterprises can achieve real-time optimization of data flows, resource allocation, and security compliance, transforming static integration approaches into adaptive, self-healing systems. The article focuses on three k

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Sai, Sneha. "The Power of Orchestration: Centralized Management for Effective RPA Operations." Journal of Advances in Developmental Research 14, no. 1 (2023): 1–7. https://doi.org/10.5281/zenodo.14916885.

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Robotic Process Automation (RPA) has revolutionized business operations by automating repetitive tasks and enhancing efficiency. However, as RPA ecosystems scale, managing multiple bots, ensuring seamless execution, and maintaining reliability become critical challenges. This white paper, The Power of Orchestration: Centralized Management for Effective RPA Operations, explores the pivotal role of orchestration in enabling organizations to maximize the value of their RPA investments.We delve into how centralized orchestration platforms like UiPath Orchestrator empower businesses to streamline b

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Sanjay Dahibhate, Makarand. "Enhancing Enterprise Data Orchestration Using Azure Data Factory." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–9. https://doi.org/10.55041/isjem03578.

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ABSTRACT This paper explores the principles and practices of data orchestration in the context of modern enterprise needs, emphasizing scalability, automation, and reliability. It provides a detailed overview of Azure Data Factory (ADF), Microsoft’s cloud-native orchestration tool, covering its architecture, key components, and operational workflows. Through a case study involving an e-commerce platform processing 50 GB of data daily, the study demonstrates ADF’s effectiveness in reducing execution time, minimizing errors, and enhancing developer productivity. Quantitative analysis highlights

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Gudelli, Venkata Ramana. "The Role of AI in Managing Multi-Cloud Strategies and Hybrid Architectures." Newark Journal of Human-Centric AI and Robotics Interaction 4 (October 16, 2024): 146–60. https://doi.org/10.5281/zenodo.15306069.

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The proliferation of multi-cloud strategies and hybrid cloud architectures has introduced unprecedented complexity in enterprise IT environments, necessitating advanced orchestration, optimization, and governance mechanisms. Artificial Intelligence (AI) is increasingly pivotal in addressing these challenges by enabling intelligent workload placement, predictive resource allocation, autonomous performance tuning, and enhanced compliance monitoring. This paper examines the state-of-the-art applications of AI in managing heterogeneous cloud infrastructures, focusing on AI-driven decision-making a

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Vasilenko, Dmitry, and Mahesh Kurapati. "Dynamic Tenant Provisioning and Service Orchestration in Hybrid Cloud." International Journal on Cloud Computing: Services and Architecture 09, no. 03 (2019): 01–10. http://dx.doi.org/10.5121/ijccsa.2019.9301.

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Ogbuefi, Ejielo, Jeffrey Chidera Ogeawuchi, Bright Chibunna Ubamadu, Oluwademilade Aderemi Agboola, and Oyinomomo-emi Emmanuel Akpe. "Systematic Review of Integration Techniques in Hybrid Cloud Infrastructure Projects." International Journal of Advanced Multidisciplinary Research and Studies 3, no. 6 (2023): 1634–43. https://doi.org/10.62225/2583049x.2023.3.6.4323.

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The growing adoption of hybrid cloud infrastructures combining public and private cloud environments has introduced complex integration challenges for organizations striving to optimize performance, scalability, and data security. This systematic review aims to evaluate and synthesize the current landscape of integration techniques used in hybrid cloud infrastructure projects, with a focus on interoperability, orchestration, data synchronization, and security compliance. This examines peer-reviewed literature, technical white papers, and industry reports published between 2015 and 2024 to iden

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Chelliah, Pethuru Raj, and Chellammal Surianarayanan. "Multi-Cloud Adoption Challenges for the Cloud-Native Era." International Journal of Cloud Applications and Computing 11, no. 2 (2021): 67–96. http://dx.doi.org/10.4018/ijcac.2021040105.

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With the ready availability of appropriate technologies and tools for crafting hybrid clouds, the move towards employing multiple clouds for hosting and running various business workloads is garnering subtle attention. The concept of cloud-native computing is gaining prominence with the faster proliferation of microservices and containers. The faster stability and maturity of container orchestration platforms also greatly contribute towards the cloud-native era. This paper guarantees the following contributions: 1) It describes the key motivations for multi-cloud concept and implementations. 2

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Nagaraju, Islavath. "Optimizing Hybrid Cloud Environments: A DevOps Approach to Managing Multi-Cloud Infrastructure." European Journal of Advances in Engineering and Technology 8, no. 3 (2021): 87–91. https://doi.org/10.5281/zenodo.13837443.

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Organizations face a challenging task as hybrid cloud setups become more widely used: managing and optimizing resources across several cloud platforms. Hybrid and multi-cloud systems provide flexibility, scalability, and cost-effectiveness but also deal with security, monitoring, and operational consistency. A DevOps approach can greatly simplify the management of hybrid cloud infrastructures by combining automation, continuous delivery (CD), infrastructure as code (IaC), and reliable monitoring tools. This article investigates how multi-cloud infrastructures can be optimized through DevOps, g

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Anil, Kumar Anusuru. "The Evolution of Middleware in Enterprise Architectures: A Future Outlook." Applied Science and Engineering Journal for Advanced Research 4, no. 1 (2025): 1–6. https://doi.org/10.5281/zenodo.14753098.

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Middleware technologies serve as critical enablers for seamless integration, communication, and management of distributed systems across diverse enterprise environments. As technological paradigms evolve, the future of middleware is set to be transformed by innovations in artificial intelligence (AI), hybrid and multi-cloud orchestration, zero-trust security frameworks, data-centric architectures, and low-code development platforms. AI-powered middleware will revolutionize system management by automating complex tasks such as anomaly detection, predictive maintenance, and dynamic traffic routi

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Asolo, Emmanuel, Jeremiah Henry Chijioke, Neibo Augustine Olobo, Isaac Adeolu Oluwagbemi, and Chukwuemeka Chukwuma Osaro. "Enhancing Urban Surveillance with Fog Computing, Mobile Cloud, and Big Data Analytics in 5G Networks." International Journal of Education, Management, and Technology 2, no. 3 (2024): 327–39. http://dx.doi.org/10.58578/ijemt.v2i3.4056.

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The new emerging applications in 5G network, in the context of the Internet of Everything (IoE), will introduce high mobility, high scalability, real-time, and low latency requirements that raise new challenges on the services being provided to the users. Fortunately, Fog Computing and Cloud Computing, with their service orchestration mechanisms offer virtually unlimited dynamic resources for computation, storage and service provision, that will effectively cope with the requirements of the forthcoming services. 5G will use the benefits of centralized high performance computing cloud centers,

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Ganore, Pramod. "Federated Learning in Cloud-Native Architectures: A Secure Approach to Decentralized AI." International Journal of Computing and Engineering 6, no. 8 (2024): 1–10. https://doi.org/10.47941/ijce.2762.

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Purpose: The paper aims to analyze the technical and security challenges of deploying FL at scale and explores how modern cloud-native technologies such as container orchestration, hybrid cloud infrastructure, and privacy-preserving techniques can be leveraged to mitigate these challenges. The study also seeks to provide a comprehensive understanding of how FL is being applied in critical domains such as healthcare, IoT, and cybersecurity, while identifying future trends that could shape the evolution of decentralized AI systems. Methodology: This research adopts a qualitative and architectura

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Researcher. "ADVANCED DISASTER RECOVERY STRATEGIES FOR HYBRID CLOUD ENVIRONMENTS: A COMPREHENSIVE TECHNICAL GUIDE." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 1147–59. https://doi.org/10.5281/zenodo.14329902.

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This comprehensive technical article analysis explores advanced disaster recovery strategies specifically designed for hybrid cloud environments, addressing the evolving challenges organizations face in maintaining business continuity. The article examines the fundamental components of hybrid cloud DR solutions, including infrastructure requirements, orchestration tools, and data replication technologies. Through detailed case studies across financial services, healthcare, and manufacturing sectors, the article demonstrates the critical importance of integrated DR approaches in modern enterpri

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Baladari, Venkata. "ENHANCING PERFORMANCE AND SECURITY IN MULTI-CLOUD AND HYBRID-CLOUD ENVIRONMENTS." International Journal of Core Engineering and Management 7, no. 11 (2024): 253–65. https://doi.org/10.5281/zenodo.15020436.

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Cloud computing is becoming more sophisticated, with companies increasingly adopting multi-cloud and hybrid cloud systems to improve flexibility, scalability, and disaster recovery capabilities. The shift in this direction poses new security, interoperability, and management challenges that need to be resolved to guarantee a secure and efficient functioning of cloud environments. This study delves into the future of cloud computing by investigating significant trends, obstacles, and resolutions connected to multi-cloud and hybrid cloud implementations. Key areas of focus examine effective meth

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Adusumilli, Lakshmi Vara Prasad. "Serverless Kubernetes: The Evolution of Container Orchestration." European Journal of Computer Science and Information Technology 13, no. 30 (2025): 20–36. https://doi.org/10.37745/ejcsit.2013/vol13n302036.

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This article examines the convergence of serverless computing and Kubernetes orchestration, representing a significant advancement in cloud-native architecture. Serverless Kubernetes implementations address fundamental operational challenges of traditional container orchestration while preserving its powerful capabilities. It explores the technical foundations enabling this evolution, including Virtual Kubelet for node abstraction, KEDA for event-driven scaling, and Knative for serverless abstractions. It analyzes implementations from major cloud providers—AWS EKS on Fargate, Azure Container I

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Gokul Chandra Purnachandra Reddy. "Architecting Hybrid Edge-Cloud Solutions: Integration Patterns for Public Cloud Platforms." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 2145–54. https://doi.org/10.32628/cseit23112562.

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This article examines the integration of edge computing with major public cloud platforms, presenting a structured analysis of architectural patterns, implementation challenges, and optimization strategies in this rapidly evolving technological domain. The article explores three fundamental integration models—hub-and-spoke, mesh, and hybrid patterns—evaluating their suitability for various use cases and operational environments. It explores critical implementation challenges related to connectivity management, data synchronization, security architecture, and resource orchestration, offering pr

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Sreerangapuri, Ashok. "Designing Resilient Hybrid Data Centers: Multi-Cloud Integration with Edge Computing for Improved Redundancy." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 9, no. 2 (2018): 801–10. http://dx.doi.org/10.61841/turcomat.v9i2.14932.

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As organizations adopt multi-cloud strategies to enhance operational agility, the integration of edge computing is emerging as a critical solution to address latency and redundancy challenges. This paper explores the architecture and design principles of hybrid data centers that seamlessly integrate cloud resources with edge nodes. It highlights the key considerations for ensuring redundancy, performance, and data sovereignty while managing distributed workloads. The study provides real-world case examples of hybrid data center deployments across different sectors, focusing on the role of soft

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Ajay Kumar Panchalingala. "Recent advances in AWS cloud services." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 259–67. https://doi.org/10.30574/wjaets.2025.15.3.0918.

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The rapid evolution of Amazon Web Services (AWS) cloud technologies continues to reshape enterprise computing environments across global industries. This technical review examines recent innovations in AWS services that are transforming organizational capabilities and competitive positioning. Beginning with computational performance advancements through AWS Graviton processors and specialized High-Performance Computing offerings, the article explores how these ARM-based architectures deliver enhanced efficiency across diverse workloads. The expanding AI and Machine Learning ecosystem, particul

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Venkatachala Nivas Chainuru. "Hybrid Storage Integration: Bridging On-Premises and Cloud through APIs." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 642–57. https://doi.org/10.32628/cseit25112394.

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This comprehensive article explores the evolution, implementation, and benefits of API-driven hybrid storage architectures in modern enterprise environments. The article examines how organizations increasingly adopt hybrid approaches that blend on-premises infrastructure with cloud capabilities to address complex storage challenges. It investigates market trends driving this transition, including cloud-first strategies, performance requirements, and regulatory considerations. The article details key components of successful API-driven hybrid storage implementations, including unified API frame

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Clement Praveen Xavier Pakkam Isaac. "Quantum cloud computing: Enterprise strategies for hybrid quantum-classical workloads." World Journal of Advanced Research and Reviews 26, no. 1 (2025): 2245–62. https://doi.org/10.30574/wjarr.2025.26.1.1248.

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Quantum Cloud Computing (QCC) represents a paradigm shift in enterprise computing strategy, merging quantum processing capabilities with traditional cloud infrastructure. This article explores the Quantum-Cloud Hybrid Adoption Model (QCHAM), a comprehensive framework consisting of three critical layers: Quantum Computing-as-a-Service (QCaaS) for scalable access to quantum hardware, Hybrid Quantum-Classical Orchestration (HQCO) for optimized workload distribution, and Quantum-Resilient Security (QRS) for cryptographic resilience. Through detailed case studies in financial services, pharmaceutic

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Bocchi, Enrico, Luca Canali, Diogo Castro, et al. "ScienceBox Converging to Kubernetes containers in production for on-premise and hybrid clouds for CERNBox, SWAN, and EOS." EPJ Web of Conferences 245 (2020): 07047. http://dx.doi.org/10.1051/epjconf/202024507047.

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Docker containers are the de-facto standard to package, distribute, and run applications on cloud-based infrastructures. Commercial providers and private clouds expand their offer with container orchestration engines, making the management of resources and containerized applications tightly integrated. The Storage Group of CERN IT leverages on container technologies to provide ScienceBox: An integrated software bundle with storage and computing services for general purposes and scientific use. ScienceBox features distributed scalable storage, sync&share functionalities, and a web-based dat

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Satya Sai Ram Alla. "Demystifying AI-driven cloud resiliency: How machine learning enhances fault tolerance in hybrid cloud infrastructure." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 1203–15. https://doi.org/10.30574/wjaets.2025.15.2.0591.

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The evolution of cloud infrastructure resilience has transitioned from traditional redundancy-based approaches to sophisticated AI-driven frameworks that enhance fault tolerance in hybrid and multi-cloud environments. This article examines how machine learning models improve cloud-native resiliency through predictive analytics, automated remediation, and intelligent resource allocation. Through systematic literature review and case studies across streaming media, container orchestration, and retail platforms, the effectiveness of various AI techniques is evaluated against traditional methods.

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Bhanuprakash, Madupati. "Kubernetes: Advanced Deployment Strategies- Technical Perspective." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 9, no. 2 (2021): 1–10. https://doi.org/10.5281/zenodo.14005206.

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Container orchestration is a foundational element of Kubernetes, the pre-eminent container orchestration platform responsible for automating the deployment, number of processes, and scaling up and down containers. Advanced Deployment Strategies official Kubernetes Concepts Doc at Kubernetes.org This paper covers some advanced deployment strategies in Kubernetes like Blue-Green Deployment Rolling updates Auto-scaling mechanisms. It is necessary to keep high availability and spare resources in cloud environments. Besides, it comes with continuous service-delivering functionality, particularly in

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Bhanuprakash, Madupati. "Kubernetes: Advanced Deployment Strategies - *Technical Perspective." International Journal of Leading Research Publication 2, no. 4 (2021): 1–12. https://doi.org/10.5281/zenodo.15109750.

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Container orchestration is a foundational element of Kubernetes, the pre-eminent container orchestration platform responsible for automating the deployment, number of processes, and scaling up and down containers. Advanced Deployment Strategies official Kubernetes Concepts Doc at Kubernetes.org This paper covers some advanced deployment strategies in Kubernetes like Blue-Green Deployment Rolling updates Auto-scaling mechanisms. It is necessary to keep high availability and spare resources in cloud environments. Besides, it comes with continuous service-delivering functionality, particularly in

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Ku, DongHwan, Hannie Zang, Anvarjon Yusupov, Sun Park, and JongWon Kim. "Vehicle-to-Everything-Car Edge Cloud Management with Development, Security, and Operations Automation Framework." Electronics 14, no. 3 (2025): 478. https://doi.org/10.3390/electronics14030478.

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Modern autonomous driving and intelligent transportation systems face critical challenges in managing real-time data processing, network latency, and security threats across distributed vehicular environments. Conventional cloud-centric architectures typically struggle to meet the low-latency and high-reliability requirements of vehicle-to-everything (V2X) applications, particularly in dynamic and resource-constrained edge environments. To address these challenges, this study introduces the V2X-Car Edge Cloud system, which is a cloud-native architecture driven by DevSecOps principles to ensure

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Bhaskara Srinivas Beeraka. "Modernizing enterprise architecture: A guide to microservices migration and hybrid cloud integration." International Journal of Science and Research Archive 14, no. 1 (2025): 440–47. https://doi.org/10.30574/ijsra.2025.14.1.0052.

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The migration from monolithic to microservices architecture represents a transformative journey in enterprise software development, complemented by the adoption of hybrid cloud technologies. This comprehensive article explores the strategic approaches, implementation patterns, and best practices for successful architectural transformation. The article examines key aspects, including preliminary analysis requirements, domain-driven design implementation, technical considerations for database and API management, and the integration of hybrid cloud technologies. Through a detailed examination of

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Sunday Adeola Oladosu, Christian Chukwuemeka Ike, Peter Adeyemo Adepoju, Adeoye Idowu Afolabi, Adebimpe Bolatito Ige, and Olukunle Oladipupo Amoo. "Advancing cloud networking security models: Conceptualizing a unified framework for hybrid cloud and on-premise integrations." Magna Scientia Advanced Research and Reviews 3, no. 1 (2021): 079–90. https://doi.org/10.30574/msarr.2021.3.1.0076.

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As organizations increasingly adopt hybrid cloud environments, the complexity of managing and securing these infrastructures has grown. Hybrid cloud and on-premise integrations present unique challenges in terms of data security, access control, and compliance, requiring a more advanced and unified approach to cloud networking security. This review conceptualizes a unified security framework aimed at addressing the specific security needs of hybrid cloud and on-premise integrations. The framework is designed to balance the flexibility and scalability of cloud environments with the robustness o

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. Kumar, M. "Smartflux: A Dual-Phase Resource Orchestration Model for IOT-Fog-Cloud Ecosystems." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49930.

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Abstract - The rapid expansion of Internet of Things (IoT) ecosystems has triggered an immense surge in data generation, demanding computational models that can efficiently manage and process this influx. Although cloud computing provides scalable resources for such tasks, its inherent latency and lack of contextual responsiveness limit its effectiveness for time-sensitive IoT applications. Fog computing, introduced to bridge this gap by enabling localized processing closer to data sources, offers reduced latency but is constrained by limited computational capacity. To overcome these limitatio

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Pothen, Vivek Aby. "Strategic Azure Cloud Migration for Telecom: Best Practices and Emerging Trends." European Journal of Computer Science and Information Technology 13, no. 19 (2025): 79–92. https://doi.org/10.37745/ejcsit.2013/vol13n197992.

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The migration of telecommunications infrastructure to cloud platforms, particularly Microsoft Azure, represents a transformative shift in how telecommunications providers manage and optimize their networks. This comprehensive article explores the imperatives driving cloud adoption in telecommunications, examining the substantial improvements in operational efficiency, cost reduction, and service reliability achieved through strategic migration initiatives. The article investigates hybrid cloud adoption strategies, the implementation of advanced Azure technologies including AI-powered analytics

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Researcher. "LEVERAGING KUBERNETES AND AI FOR IMPROVED DISASTER RECOVERY IN CLOUD COMPUTING." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 1160–67. https://doi.org/10.5281/zenodo.14330367.

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This article presents a groundbreaking approach to disaster recovery in cloud computing by integrating Artificial Intelligence (AI) capabilities with Kubernetes container orchestration. The article introduces a novel multi-layered architecture that combines deep learning-based predictive analytics, automated recovery mechanisms, and intelligent resource optimization algorithms to enhance system resilience and minimize downtime. Our framework demonstrated remarkable improvements in key performance metrics through extensive testing across geographically distributed clusters, achieving a 73% redu

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Jung, JiYoung, and Yongtae Shin. "Cloud Computing Transformation Considering Operational Efficiency." International Journal of Software Innovation 10, no. 2 (2022): 1–18. http://dx.doi.org/10.4018/ijsi.289599.

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Companies that have their own IT Center built and operated an on-premise system. But recently, cloud computing is considered to secure system reliability and reduce management costs. IT resources can be efficiently utilized and paid for used. Therefore, companies were deploying and migrating their intranet services to cloud servers. However, it is also true that cloud migration makes system complexity increase, and system reliability is compromised by the increase of management points. Cloud computing for each service unit was considered as a way to meet an efficient utilization of IT resource

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Sumanth Kadulla. "The evolution of cloud automation: From DevOps to autonomous infrastructure." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 496–503. https://doi.org/10.30574/wjaets.2025.15.2.0626.

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The evolution of cloud automation represents a transformative journey from manual operations to autonomous systems capable of self-configuration and self-healing. This technical article explores the progression from early DevOps practices through infrastructure as code, container orchestration, and toward AI-driven autonomous operations. The DevOps revolution established the foundation through cultural transformation and basic automation, breaking down traditional silos between development and operations teams while introducing standardized processes. Infrastructure as Code further advanced th

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Ankita, Sharma. "Network Automation and Orchestration: AI-Driven Self-Healing Networks and Zero-Touch Provisioning." European Journal of Advances in Engineering and Technology 10, no. 3 (2023): 98–104. https://doi.org/10.5281/zenodo.14168741.

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This study analyzes the changing dynamics of network automation and orchestration, highlighting the contributions of Artificial Intelligence (AI) and Machine Learning (ML) in improving network stability, scalability, and efficiency. We examine the development of self-healing networks for autonomous fault identification and rectification, SD-WAN automation for hybrid cloud settings, and zero-touch provisioning for efficient network administration. This investigation underscores the role of AI and ML in advancing the next generation of network automation, paving the way for progressively autonom

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Srinivasa, Rao Karanam. "The Evolution of Data Warehousing: From On-Premise to Cloud-Native Solutions." Journal of Advances in Developmental Research 15, no. 2 (2024): 1–9. https://doi.org/10.5281/zenodo.15206387.

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Throughout the broader timeline of enterprise computing, data warehousing has become an integral approach for consolidating disparate data sets into the centralized, structured repository. Initial on-premise models emphasized intricately planned schema designs and hardware provisioning, but with the advent of highly scalable Cloud infrastructures, the complexities of deployment and management began to shift drastically. This paper evaluates the transitions from historical on-premises architecture, which demanded massive capital outlays, into more flexible cloud-based data warehouse topologies

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Spiga, Daniele, Enol Fernandez, Vincenzo Spinoso, et al. "The DODAS Experience on the EGI Federated Cloud." EPJ Web of Conferences 245 (2020): 07033. http://dx.doi.org/10.1051/epjconf/202024507033.

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The EGI Cloud Compute service offers a multi-cloud IaaS federation that brings together research clouds as a scalable computing platform for research accessible with OpenID Connect Federated Identity. The federation is not limited to single sign-on, it also introduces features to facilitate the portability of applications across providers: i) a common VM image catalogue VM image replication to ensure these images will be available at providers whenever needed; ii) a GraphQL information discovery API to understand the capacities and capabilities available at each provider; and iii) integration

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Satish Manchana. "Advancing Hybrid Cloud Automation: AI-driven Policy Engines and Compliance-Aware Orchestration in Financial Enterprises." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 1106–21. https://doi.org/10.30574/wjaets.2025.15.3.1003.

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The convergence of artificial intelligence and cloud computing is revolutionizing how financial enterprises manage infrastructure, particularly in hybrid environments where regulatory compliance remains paramount. Financial institutions implementing AI-driven governance solutions report reducing compliance incident response time by 78% and decreasing manual audit efforts by 65%. This article explores the evolution of cloud automation in financial services, highlighting the shift from traditional governance approaches to AI-driven policy engines that dynamically enforce regulatory requirements

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Sultana, Rebeka, and Farhana Zaman Rozony. "A META-ANALYSIS OF ARTIFICIAL INTELLIGENCE-DRIVEN DATA ENGINEERING: EVALUATING THE EFFECTIVENESS OF CLOUD-BASED INTEGRATION MODELS." ASRC Procedia: Global Perspectives in Science and Scholarship 01, no. 01 (2025): 193–214. https://doi.org/10.63125/8a5k2j16.

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This study conducts a comprehensive meta-analysis to evaluate the effectiveness of artificial intelligence (AI)-driven data engineering approaches within cloud-based integration models. Drawing from 122 peer-reviewed studies published between 2015 and 2025—with a combined citation count exceeding 25,000—this research synthesizes empirical findings on how AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing are transforming core data engineering functions. The analysis focuses on performance outcomes related to data ingestion, transforma

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Somaning Turwale. "System Center Virtual Machine Manager 2022: Enhanced Cloud Integration and Management Capabilities." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 1306–14. https://doi.org/10.32628/cseit241061176.

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System Center Virtual Machine Manager (SCVMM) 2022 represents a transformative advancement in private cloud management, offering enhanced capabilities across virtualization, deployment, and cloud integration domains. This comprehensive platform introduces sophisticated hardware-level security protocols, dynamic resource allocation mechanisms, and intelligent orchestration capabilities that significantly improve operational efficiency. The integration with Azure Arc and support for Azure Kubernetes Service demonstrates SCVMM's evolution in hybrid cloud management, while enhanced data protection

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Kanthed, Surbhi. "Automation Tools for DevOps: Leveraging Ansible, Terraform, and Beyond." International Scientific Journal of Engineering and Management 04, no. 04 (2025): 1–7. https://doi.org/10.55041/isjem01286.

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DevOps has rapidly become a cornerstone for modern software development, providing faster release cycles and improved collaboration between development and operations teams. Central to DevOps practices is automation, which addresses the complexity of provisioning and configuring diverse computing environments. This white paper explores state-of-the-art automation tools, with a focus on Ansible for configuration management and Terraform for infrastructure as code (IaC). An extensive review of recent scholarly articles, conference papers, and real-world case studies reveals the unique strengths

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Ramadevi Sannapureddy. "Cloud-Native Enterprise Integration: Architectures, Challenges, and Best Practices." Journal of Computer Science and Technology Studies 7, no. 5 (2025): 167–73. https://doi.org/10.32996/jcsts.2025.7.5.22.

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Cloud-native enterprise integration represents a transformative shift from monolithic middleware to distributed, loosely-coupled architectures that enable organizations to achieve greater business agility and operational efficiency. This article examines the architectural patterns, challenges, and best practices for successful cloud-native integration implementations. By leveraging event-driven architectures, API-first approaches, service meshes, and hybrid integration models, enterprises can create flexible, resilient integration solutions that support modern business requirements. However, t

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Srikanth, Jonnakuti. "INTELLIGENT EDGE ARCHITECTURES: AI AT THE BOUNDARY OF CLOUD AND DEVICE." International Journal of Engineering Technology Research & Management (IJETRM) 06, no. 08 (2022): 95–99. https://doi.org/10.5281/zenodo.15455791.

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Edge computing shifts intelligence closer to data sources, reducing latency and bandwidth by distributing MLinference between devices and cloud. This paper presents a concise study of hybrid edge–cloud architecturestailored for latency-sensitive retail and IoT applications. Building on paradigms such as fog computing,cloudlets, and MEC, we outline three architectural patterns—hierarchical edge–cloud, collaborative (split)inference, and on‑device inference with cloud backup—and discuss orchestration strategies. Use cases in smartretail, industrial IoT, and smart cities i

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Sahil Yadav. "Adaptive AI-Driven Network Orchestration for Self-Evolving Enterprise Data Platforms." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 1580–89. https://doi.org/10.30574/wjaets.2025.15.3.1087.

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This article presents a comprehensive theoretical framework for adaptive AI-driven network orchestration in enterprise data platforms, addressing the growing complexity and dynamic nature of modern data environments. The article introduces a self-evolving architectural construct that leverages advanced machine learning methodologies, specifically multi-agent reinforcement learning with proximal policy optimization, transformer-based anomaly detection, and temporal graph attention networks, to continuously monitor, predict, and optimize system resources without human intervention. The theoretic

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