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Littérature scientifique sur le sujet « Auto-Scaling policies »

Auteur : Grafiati

Publié le 1 juin 2024

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Auto-Scaling policies"

Vemasani, Preetham, Sai Mahesh Vuppalapati, Suraj Modi, and Sivakumar Ponnusamy. "Achieving Agility through Auto-Scaling: Strategies for Dynamic Resource Allocation in Cloud Computing." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 3169–77. http://dx.doi.org/10.22214/ijraset.2024.60566.

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Abstract: Auto-scaling is a crucial aspect of cloud computing, allowing for the efficient allocation of computational resources in response to immediate demand. This article delves into the concept of auto-scaling, its key components, and the strategies used to effectively manage resources in cloud environments. This study emphasizes the importance of auto-scaling in the cloud computing landscape by exploring its benefits, including cost efficiency, performance optimization, high availability, and scalability [1]. The article explores the various factors to consider when implementing scaling p

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Guo, Yuan Yuan, Jing Li, Xin Chun Liu, and Wei Wei Wang. "Batch Job Based Auto-Scaling System on Cloud Computing Platform." Advanced Materials Research 756-759 (September 2013): 2386–90. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.2386.

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With the quick development of information science, it becomes much harder to deal with a large scale of data. In this case, cloud computing begins to become a hot topic as a new computing model because of its good scalability. It enables customers to acquire and release computing resources from and to the cloud computing service providers according to current workload. The scaling ability is achieved by system automatically according to auto scaling policies reserved by customers in advance, and it can greatly decrease users operating burden. In this paper, we proposed a new architecture of au

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viatoire, Dr T. Amalraj. "Dynamic Auto-Scaling and Load-Balanced Web Application Deployment in AWS." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49936.

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ABSTRACT Web applications must be fast, dependable, and able to manage evolving user needs without collapsing or becoming overly costly to maintain in the digital environment of today. Manual server management or traffic spike handling in traditional approaches of application deployment sometimes result in downtime, inadequate performance, or expensive costs. This project, "Dynamic Auto-Scaling and Load-Balanced Wed Application Deployment In AWS," thus emphasizes on creating a cloud-based infrastructure capable of automatically adjusting to demand, remain available, and operate effectively wit

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Rajput, R. S., Dinesh Goyal, Rashid Hussain, and Pratham Singh. "Provisioning of Virtual Machines in the Context of an Auto-Scaling Cloud Computing Environment." Journal of Computational and Theoretical Nanoscience 17, no. 6 (2020): 2430–34. http://dx.doi.org/10.1166/jctn.2020.8912.

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The cloud computing environment is accomplishing cloud workload by distributing between several nodes or shift to the higher resource so that no computing resource will be overloaded. However, several techniques are used for the management of computing workload in the cloud environment, but still, it is an exciting domain of investigation and research. Control of the workload and scaling of cloud resources are some essential aspects of the cloud computing environment. A well-organized load balancing plan ensures adequate resource utilization. The auto-scaling is a technique to include or termi

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Evangelidis, Alexandros, David Parker, and Rami Bahsoon. "Performance modelling and verification of cloud-based auto-scaling policies." Future Generation Computer Systems 87 (October 2018): 629–38. http://dx.doi.org/10.1016/j.future.2017.12.047.

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Researcher. "SCALING: THE BACKBONE OF EFFICIENT CLOUD PLATFORMS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 5 (2024): 1–13. https://doi.org/10.5281/zenodo.13644708.

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This comprehensive article explores the concept of elastic scaling in cloud computing, detailing its significance, key components, applications, benefits, and challenges. It examines how elastic scaling enables dynamic resource allocation in response to fluctuating demands, optimizing performance and cost-efficiency. The article discusses various auto-scaling techniques, scaling policies, and the importance of monitoring and observability in implementing effective elastic scaling strategies. It highlights the wide-ranging applications of elastic scaling across different industries and use case

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A. Karunamurthy, Dr. "Scalable Web Application Deployment Using Auto Scaling, Load Balancer, And RDS." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49702.

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Abstract The rapid growth of web applications and the increasing demand for high availability, scalability, and performance have made traditional deployment methods inadequate. This project, titled "Scalable Web Application Deployment Using Auto Scaling, Load Balancer, and RDS," focuses on creating a robust and efficient infrastructure for deploying web applications on the cloud. The main goal is to ensure that the application can automatically adapt to changing workloads while maintaining optimal performance and availability. The proposed system utilizes Amazon Web Services (AWS) as the cloud

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Gudelli, Venkata Ramana. "Optimizing Elastic Kubernetes Services for High Availability Applications." Journal of Computational Intelligence and Robotics 1, no. 2 (2021): 64–88. https://doi.org/10.5281/zenodo.15102526.

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Cloud native architectures are adapted rapidly which makes the deployment highly available, resilient, and scalable applications on Kubernetes. Elastic Kubernetes Services (EKS) provides an automated managed environment that facilitates dynamic resource allocation and workload distribution. But optimization of EKS for high availability requires precise tuning of cluster configurations, node auto-scaling policies, and fault tolerance mechanisms. The purpose of this paper is to examine the key architectural components which influences the EKS performance which includes pod disruption budgets, ho

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A. Karunamurthy, Dr. "SECURE AND SCALABLE WORDPRES DEPLOYMENT ON AWS WITH RDS." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04077.

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Abstract This paper digital landscape, ensuring high availability, scalability, and security for web applications is crucial. This project focuses on deploying a secure and scalable WordPress website on Amazon Web Services (AWS) using industry best practices. By leveraging AWS services such as EC2, Auto Scaling, RDS, S3, VPC, IAM, and Security Groups, this deployment achieves high performance, reliability, and security. The architecture includes Amazon EC2 instances running WordPress in an Auto Scaling Group, ensuring seamless horizontal scalability. Amazon RDS is used for the MySQL database,

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Owoade, Samuel, Abraham Ayodeji Abayomi, Abel Chukwuemeke Uzoka, Oyejide Timothy Odofin, Oluwasanmi Segun Adanigbo, and Jeffrey Chidera Ogeawuchi. "Predictive Infrastructure Scaling in Fintech Systems Using AI-Driven Load Balancing Models." International Journal of Advanced Multidisciplinary Research and Studies 4, no. 6 (2024): 2393–401. https://doi.org/10.62225/2583049x.2024.4.6.4356.

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As the fintech industry continues to experience exponential growth, the ability to scale infrastructure dynamically and efficiently has become a critical concern. Traditional methods of load balancing and resource scaling often fail to meet the demands of real-time fintech applications, resulting in performance bottlenecks, high operational costs, and system inefficiencies. This paper explores the integration of artificial intelligence (AI) in predictive infrastructure scaling to address these challenges. Specifically, it investigates AI-driven models, including machine learning algorithms suc

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Thèses sur le sujet "Auto-Scaling policies"

Adolfsson, Henrik. "Comparison of Auto-Scaling Policies Using Docker Swarm." Thesis, Linköpings universitet, Databas och informationsteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-154160.

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When deploying software engineering applications in the cloud there are two similar software components used. These are Virtual Machines and Containers. In recent years containers have seen an increase in popularity and usage, in part because of tools such as Docker and Kubernetes. Virtual Machines (VM) have also seen an increase in usage as more companies move to solutions in the cloud with services like Amazon Web Services, Google Compute Engine, Microsoft Azure and DigitalOcean. There are also some solutions using auto-scaling, a technique where VMs are commisioned and deployed to as load i

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Tournaire, Thomas. "Model-based reinforcement learning for dynamic resource allocation in cloud environments." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS004.

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L'émergence de nouvelles technologies nécessite une allocation efficace des ressources pour satisfaire la demande. Cependant, ces nouveaux besoins nécessitent une puissance de calcul élevée impliquant une plus grande consommation d'énergie notamment dans les infrastructures cloud et data centers. Il est donc essentiel de trouver de nouvelles solutions qui peuvent satisfaire ces besoins tout en réduisant la consommation d'énergie des ressources. Dans cette thèse, nous proposons et comparons de nouvelles solutions d'IA (apprentissage par renforcement RL) pour orchestrer les ressources virtuelles

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Chapitres de livres sur le sujet "Auto-Scaling policies"

Kumari, Anisha, and Bibhudatta Sahoo. "Serverless Architecture for Healthcare Management Systems." In Advances in Healthcare Information Systems and Administration. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-4580-8.ch011.

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Serverless computing is an emerging cloud service architecture for executing distributed applications, where services are provided based on a pay-as-you-go basis. It allows the developers to deploy and run their applications without worrying about the underlying architecture. Serverless architecture has been popular due to its cost-effective policies, auto-scaling, independent, and simplified code deployment. The healthcare service can be made available as a serverless application that consists of distributed cloud services achieving the various requirements in the healthcare industry. The ser

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Actes de conférences sur le sujet "Auto-Scaling policies"

Eshwar, S. R., Lucas Lopes Felipe, Alexandre Reiffers-Masson, Daniel Sadoc Menasché, and Gugan Thoppe. "Online Learning of Weakly Coupled MDP Policies for Load Balancing and Auto Scaling." In 2024 IFIP Networking Conference (IFIP Networking). IEEE, 2024. http://dx.doi.org/10.23919/ifipnetworking62109.2024.10619773.

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Evangelidis, Alexandros, David Parker, and Rami Bahsoon. "Performance Modelling and Verification of Cloud-Based Auto-Scaling Policies." In 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID). IEEE, 2017. http://dx.doi.org/10.1109/ccgrid.2017.39.

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Gandhi, Anshul, Mor Harchol-Balter, Ram Raghunathan, and Michael A. Kozuch. "Distributed, Robust Auto-Scaling Policies for Power Management in Compute Intensive Server Farms." In 2011 6th Open Cirrus Summit (OCS). IEEE, 2011. http://dx.doi.org/10.1109/ocs.2011.6.

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