Standardization Efforts for Traditional Data Center Infrastructure Management: The Big Picture

Ferreira, Leylane; Endo, Patrícia Takako; Rosendo, Daniel; Santos, Guto Leoni; Gomes, Demis; Moreira, Andre; Gonçalves, Glauco Estácio; Kelner, Judith; Sadok, Djamel; Mehta, Amardeep; Wildeman, Mattias

doi:10.1109/emr.2020.2969864

Cited by 6 publications

(2 citation statements)

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“…However, our work differs from these as our focus is on the availability evaluation of next‐generation cloud data centers. Moreover, we also propose chassis design configurations based on Redfish Schema, adopted since it is an important open industry standard, in fact, one that is seen as a meta‐standard. This way, to provide an availability evaluation regarding the emerging vPOD‐based data centers, this article: proposes four chassis design configurations based on the Redfish industry standard to compose a vPOD system: (a) fully shared design, (b) partially shared homogeneous design, (c) partially shared heterogeneous design, and (d) not shared design; and proposes a set of stochastic models that combine reliability block diagram (RBD) and stochastic Petri nets (SPNs) to represent how failures on pools of hardware resources affect vPODs availability ; and analyzes how these different design configurations impact the vPOD availability . …”

Section: Introductionmentioning

confidence: 99%

Availability analysis of design configurations to compose virtual performance‐optimized data center systems in next‐generation cloud data centers

et al. 2020

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Next-generation cloud data centers are based on software-defined data center infrastructures that promote flexibility, automation, optimization, and scalability. The Redfish standard and the Intel Rack Scale Design technology enable software-defined infrastructure and disaggregate bare-metal compute, storage, and networking resources into virtual pools to dynamically compose resources and create virtual performance-optimized data centers (vPODs) tailored to workload-specific demands. This article proposes four chassis design configurations based on Distributed Management Task Force's Redfish industry standard applied to compose vPOD systems, namely, a fully shared design, partially shared homogeneous design, partially shared heterogeneous design, and not shared design; their main difference is based on the used hardware disaggregation level. Furthermore, we propose models that combine reliability block diagram and stochastic Petri net modeling approaches to represent the complexity of the relationship between the pool of disaggregated hardware resources and their power and cooling sources in a vPOD. These four proposed design configurations were analyzed and compared in terms of availability and component's sensitivity indexes by scaling their configurations considering different data center infrastructure. From the obtained results, we can state that, in general, when one increases the hardware disaggregation, availability is improved. However, after a given point, the availability level of the fully shared, partially shared homogeneous, and partially shared heterogeneous configurations remain almost equal, while the not shared configuration is still able to improve its availability. K E Y W O R D Savailability, composable systems, next-generation cloud data center, Redfish standard, stochastic models Softw: Pract Exper. 2020;50:805-826.wileyonlinelibrary.com/journal/spe

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Section: Introductionmentioning

confidence: 99%

Availability analysis of design configurations to compose virtual performance‐optimized data center systems in next‐generation cloud data centers

et al. 2020

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“…Nowadays, many strategies to monitor data center resources are utilized by operators such as standards, protocols, and purpose built software. According to Reference 4, standards are essential in data center management in order to simplify management of the large diversity of data center components (servers, appliances, storage, network devices, etc.) .…”

Section: Introductionmentioning

confidence: 99%

Aggregating data center measurements for availability analysis

et al. 2020

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Summary A data center infrastructure is composed of heterogeneous resources divided into three main subsystems: IT (processor, memory, disk, network, etc.), power (generators, power transformers, uninterruptible power supplies, distribution units, among others), and cooling (water chillers, pipes, and cooling tower). This heterogeneity brings challenges for collecting and gathering data from several devices in the infrastructure. In addition, extracting relevant information is another challenge for data center managers. While seeking to improve the cloud availability, monitoring the entire infrastructure using a variety of (open source and/or commercial) advanced monitoring tools, such as Zabbix, Nagios, Prometheus, CloudWatch, AzureWatch, and others is required. It is often common to use many monitoring systems to collect real‐time data for data center components from different subsystems. Such an environment brings an inherent challenge stemming from the need to aggregate and organize the whole collected infrastructure data and measurements. This first step is necessary prior to obtaining any valuable insights for decision‐making. In this paper, we present the Data Center Availability (DCA) System, a software system that is able to aggregate and analyze data center measurements aimed toward the study of DCA. We also discuss the DCA implementation and illustrate its operation, monitoring a small University research laboratory data center. The DCA System is able to monitor different types of devices using the Zabbix tool, such as servers, switches, and power devices. The DCA System is able to automatically identify the failure time seasonality and trend present in the collected data from different devices of the data center.

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Research on Renewable Energy Supplement in DC Data Center

Jin

2023

Applied Economics and Policy Studies

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Standardization Efforts for Traditional Data Center Infrastructure Management: The Big Picture

Cited by 6 publications

References 25 publications

Availability analysis of design configurations to compose virtual performance‐optimized data center systems in next‐generation cloud data centers

Availability analysis of design configurations to compose virtual performance‐optimized data center systems in next‐generation cloud data centers

Aggregating data center measurements for availability analysis

Research on Renewable Energy Supplement in DC Data Center

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