Research and Analysis of Computing Cluster Configuration Management Systems

Martyshkin, A.I; Biktashev, R. A.

doi:10.1007/978-3-031-22311-2_20

Cited by 3 publications

(4 citation statements)

References 7 publications

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“…Specifically, we observe comparative analyses of container orchestration frameworks in the research works [15,16] and find that Kubernetes wins the race by a fair margin (for this, we do not repeat the same analysis herein, simply inferring their analysis). Specifically, in the studies [15,16], the comparative analysis is shown among Kubernetes, Mesos, Docker Swarm, Nomad, and the fully-managed frameworks except SaltStack, while comparing with SaltStack, we see that Kubernetes is superior to SaltStack [11,43,44]. In particular, we observe that Kubernetes caters better to business needs than SaltStack.…”

Section: Kubernetes Vs Other Container Orchestration Frameworkmentioning

confidence: 80%

“…The first category includes fully-managed, paid, closed-source, easy deployable and manageable frameworks, such as Amazon Elastic Container Service (Amazon ECS) [12,38], Amazon Elastic Container Service for Kubernetes (EKS) [16] Google Kubernetes Engine (GKE) [16], Microsoft Azure Kubernetes Service (AKS) [16], OpenShift [13,14,39], and others. The second category includes self-managed and opensource frameworks, such as Kubernetes [7,17], Mesos [8,40], Docker Swarm [9,10,41,42], Nomad [10], SaltStack [11,43,44], and many others. Although each framework has unique features that others could do not have, their limitations dissuade some potential users.…”

Section: Kubernetes Vs Other Container Orchestration Frameworkmentioning

confidence: 99%

“…In particular, we observe that Kubernetes caters better to business needs than SaltStack. Moreover, Kubernetes is a better choice than SaltStack with quality metrics, feature updates, and other evaluation criteria [11,43,44]. Notably, Kubernetes is easier to use, as stated earlier, while the saving grace of SaltStack is that it is easier to set up, manage, and control.…”

Section: Kubernetes Vs Other Container Orchestration Frameworkmentioning

confidence: 99%

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Toward Optimal Load Prediction and Customizable Autoscaling Scheme for Kubernetes

Mondal

Kabir

et al. 2023

Mathematics

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Most enterprise customers now choose to divide a large monolithic service into large numbers of loosely-coupled, specialized microservices, which can be developed and deployed separately. Docker, as a light-weight virtualization technology, has been widely adopted to support diverse microservices. At the moment, Kubernetes is a portable, extensible, and open-source orchestration platform for managing these containerized microservice applications. To adapt to frequently changing user requests, it offers an automated scaling method, Horizontal Pod Autoscaler (HPA), that can scale itself based on the system’s current workload. The native reactive auto-scaling method, however, is unable to foresee the system workload scenario in the future to complete proactive scaling, leading to QoS (quality of service) violations, long tail latency, and insufficient server resource usage. In this paper, we suggest a new proactive scaling scheme based on deep learning approaches to make up for HPA’s inadequacies as the default autoscaler in Kubernetes. After meticulous experimental evaluation and comparative analysis, we use the Gated Recurrent Unit (GRU) model with higher prediction accuracy and efficiency as the prediction model, supplemented by a stability window mechanism to improve the accuracy and stability of the prediction model. Finally, with the third-party custom autoscaling framework, Custom Pod Autoscaler (CPA), we packaged our custom autoscaling algorithm into a framework and deployed the framework into the real Kubernetes cluster. Comprehensive experiment results prove the feasibility of our autoscaling scheme, which significantly outperforms the existing Horizontal Pod Autoscaler (HPA) approach.

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Section: Kubernetes Vs Other Container Orchestration Frameworkmentioning

confidence: 80%

Section: Kubernetes Vs Other Container Orchestration Frameworkmentioning

confidence: 99%

Section: Kubernetes Vs Other Container Orchestration Frameworkmentioning

confidence: 99%

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Toward Optimal Load Prediction and Customizable Autoscaling Scheme for Kubernetes

Mondal

Kabir

et al. 2023

Mathematics

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“…Table 5 provides a quick reference on the key countermeasures to address privacy and security concerns in fog-to-fog communication. Use automated tools for configuration management [186] 7 Encryption Key Management Establish a robust key management system [187]- [189] Regularly rotate encryption keys Use hardware security modules (HSMs)…”

Section: Dependency On External Networkmentioning

confidence: 99%

Privacy and security issues in fog-to-fog communication: A survey

Timothy Murkomen

2023

World J. Adv. Res. Rev.

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The rapid growth of Fog Computing has brought a paradigm shift in data processing and communication, presenting various benefits such as reduced latency, efficient data processing, enhanced scalability and the ability to operate effectively in resource-constrained environments. However, the technology introduced complex privacy and security issues. This paper conducted a thorough exploration of privacy and security issues associated with fog-to-fog (F2F) communication within the broader framework of fog computing. It initiated by providing a background of fog computing, it’s architecture and the core characteristics of fog computing. This survey aimed to discuss the state-of-the-art of privacy and security concerns in fog-to-fog communication. The survey also proposed the areas of future research to equip researchers, practitioners, policy makers and the decision makers with solid knowledge, offering guidance in navigating the complex landscape of privacy and security issues in fog-to-fog (F2F) communication. The survey also aimed to discuss the existing privacy and security research gaps in fog-to-fog (F2F) communication. The findings of this review underscore privacy and security issues in F2F communication, providing valuable insights into recommended countermeasures to strengthen the overall security framework.

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