2018· International Journal of Artificial Intelligence & Digital Transformation· Vol 1, pp. 01-07· 0 citations
TL;DR
A comprehensive survey of current technologies in cloud infrastructure automation, including Infrastructure as Code (IaC), configuration management, continuous integration/continuous deployment (CI/CD), and containerization is provided.
Abstract
Cloud infrastructure automation has emerged as a pivotal component in modern cloud computing, enabling efficient resource management, rapid deployment, and enhanced scalability. This paper provides a comprehensive survey of current technologies in cloud infrastructure automation, including Infrastructure as Code (IaC), configuration management, continuous integration/continuous deployment (CI/CD), and containerization. It explores the integration of serverless architectures with Function as a Service (FaaS) and Infrastructure as a Service (IaaS), highlighting the challenges and solutions in their hybrid implementation. The study also delves into the role of Artificial Intelligence (AI) and Machine Learning (ML) in fostering predictive and self-healing cloud systems. Furthermore, it addresses the complexities introduced by multi-cloud configurations and the management tools like Kubernetes and Terraform that aid in their orchestration. By analyzing these technologies, the paper offers insights into future directions and research opportunities in cloud infrastructure automation.
Analysis of hybrid cloud architecture, its applicability to the modern enterprise business setting, and its use in facilitating resilience-based scalable and secure business activities indicate that hybrid cloud solutions can be effective with regards to enhanced performance, availability and reduced costs in comparison with earlier single-cloud models.
Noah Wright, Isabella Moore· International Journal of Mod...· 0 citations
The paper addresses the transformation of enterprise application infrastructure out of on-premise legacy resource setting into service-based cloud environments properly configured to scale horizontally, and presents experimental evaluations of the response time, throughput, service resiliency, and infrastructure utilization in both traditional and cloud-native deployments.
Kanya Mohammed, Naree Thongchai· International Journal of Mod...· 0 citations
This review explores the recent approaches of the state of the art focused on service orchestration in IoT edge-cloud environments, concentrating on architectures and methodologies that enable resource allocation and service management.
The rapid adoption of multi-cloud computing has enabled organizations to utilize services from multiple cloud providers to improve scalability, availability, and operational flexibility. However, differences in cloud architectures, proprietary application programming interfaces (APIs), and service management mechanisms continue to impede seamless interoperability across heterogeneous cloud environments. To overcome these challenges, two major approaches have emerged: vendor-neutral Infrastructure-as-Code (IaC) technologies, such as Docker and Terraform, and provider-specific native cloud interoperability services. Despite their growing adoption, a comprehensive comparison of these approaches remains limited. This paper presents a comparative analysis of Infrastructure-as-Code and native cloud services for achieving multi-cloud interoperability. The study evaluates both approaches using key criteria, including vendor independence, deployment portability, infrastructure automation, scalability, deployment complexity, cost efficiency, and vendor lock-in. The analysis shows that Docker and Terraform provide a cloud-agnostic deployment model that enhances application portability and reduces dependency on specific cloud vendors. In contrast, native cloud services offer optimized integration, simplified management, and improved performance within their respective cloud ecosystems but limit portability across heterogeneous platforms. The findings provide practical insights into the strengths and limitations of both approaches and offer guidance for selecting appropriate interoperability strategies for cloud-native applications deployed in multi-cloud environments.
P. Shukla, V. M. Patil· International Journal of Sci...· 0 citations
This paper presents a comprehensive study of edge-cloud orchestration strategies tailored for scalable industrial automation systems, and reveals that intelligent orchestration can significantly enhance operational efficiency, system scalability, and responsiveness in industrial settings.
A. Reza· International Journal of Mac...· 0 citations
A comprehensive review of edge computing as a modern trend in information technology, including the convergence of edge computing with artificial intelligence (Edge AI), 6G networks, digital twins, and serverless edge architectures is presented.
Awiti Gideon Appiah, Dr. Lazarus Kwao, Benjamin Opoku Atuahene· International Journal of Cre...· 0 citations
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