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

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Traditional data center infrastructure suffers from a lack of standard and ubiquitous management solutions. Despite the achieved contributions, existing tools lack interoperability and are hardware dependent. Vendors are already actively participating in the specification and design of new standard software and hardware interfaces within different forums. Nevertheless, the complexity and variety of data center infrastructure components that includes servers, cooling, networking, and power hardware, coupled with the introduction of the software defined data center paradigm, led to the parallel development of a myriad of standardization efforts. In an attempt to shed light on recent works, we survey and discuss the main standardization efforts for traditional data center infrastructure management.

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... The [1] traditional data centre is also tightly coupled with management software, creating interoperatabilty issues. To overcome all these problems this chapter provides a broad view on Modern Data centre software-defined solutions to maintain integrated standard management ecosystem or framework [2]. To bring efficiency, agility, energy consumption we are dramatically moving towards Next-Generation Modern data centres for environmental sustainability with recycling efficiency that reduces emissions footprint [3]. ...
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Data centres playing a vital role in expanding the business for enterprises with intelligent solutions. They have prominently improved the usability of data as a whole. The existing traditional data centre is still in use at most of the on-premises organization. It is also called "siloed" data centre which mostly relies on Hardware machines with more manual interventions and configurations sometimes lead to error-prone. The storage drive is of monolithic spinning Magnetic-disk based Networked Attached Storage (NAS) or Storage Area Network (SAN) array. These resources also require more flooring space with cooling may consume more power and incur cost. The proposed Modern data centre which is based on software-defined technology which requires less physical resources with unified user interface, highly virtualized, easy configuration, centralized administration and with high speed network fabrics for faster, lossless data transfer with rapid resource provisioning. The SLI (Software-Led infrastructure) can handle dynamic workloads with intelligent automated resource allocation which is highly scalable. The storage is of solid state or flash storage which requires less power to operate on comparing the spinning disk. In Modern data centres Virtualization, consolidation and fluid resource pooling enables efficient better, accurate utilization of resources and provisioning with High Availability (HA) which saves cost and energy also reduces the carbon footprints to preserve the ecosystem for the next generation and improves digital business agility.
... So procuring the new hardware from various vendors may consume time and cost to replace the failed component [2]. Traditional on-premise data centre infrastructure also suffers from standards, lack of interoperatabilty, more hardware dependency and omnipresent management solutions [3]. In on-premises Traditional DC, Enterprises invests costs in more hardware like servers, storage and network equipment's to meet specific application needs required by their organization employees to process their workloads and keep them secure within their datacenter privately. ...
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In this Modern Era, Datacenters are the backbone of today's enterprise businesses. To expand their business growth, an organization should first identify whether they are going to stay with on-premises or cloud infrastructure. In this paper we are going to explore the evolution towards on-premises Modern Data Centre (DC) from the basic classical, "siloed" traditional infrastructure. The old traditional data centre relies on more hardware and physical servers, needs more individual team to maintain, consumes more electricity, incurs more cost on buying machines for extra workloads when company grows. Maintaining the data securely is also a crucial task in siloed infrastructure because it needs more configuration and administration task which may lead to error-prone. The Next level of converged infrastructure in which the configurations are of pre-defined bundled templates which cannot be scaled further. The one more level-up the existing on-premise hyper-converged infrastructure in which CPU and storage will be coupled in one plane and network is in another plane and here when scalability is needed extra nodes to be created completely again is an additional overhead. In this paper the proposed Composable Infrastructure which supports all kinds of traditional and modern workloads with fluid pool of independent resource provisioning can be done intelligently through predictive unified API with more scalability, High availability and agility by means of the technologies like virtualization and containerization like the power of cloud infrastructure and services. Moreover, the software industry is highly fluid in this present decade to adapt the old software model to fit with evolving containerized Micro-services based applications which requires greater scalability and fast deployment. Hence the evolved on-premises composable modern infrastructure which is more dynamic in provisioning the resources with unlimited scaling is compared with other existing infrastructures with various parameters like Energy efficiency, High Availability, Cost and Agility.
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Large data centers are complex systems that depend on several generations of hardware and software components, ranging from legacy mainframes and rack-based appliances to modular blade servers and modern rack scale design solutions. To cope with this heterogeneity, the data center manager must coordinate a multitude of tools, protocols, and standards. Currently, data center managers, standardization bodies, and hardware/software manufacturers are joining efforts to develop and promote Redfish as the main hardware management standard for data centers, and even beyond the data center. The authors hope that this article can be used as a starting point to understand how Redfish and its extensions are being targeted as the main management standard for next-generation data centers. This article describes Redfish and the recent collaborations to leverage this standard.
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Conference Paper
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Conference Paper
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This article reports experimental and numerical testing performed to characterize the operation and reliability of the open compute (OC) storage system in contained environment from server to aisle levels. The study is comprised of three parts. The first part is an experimental analysis of the high density (HD) 3D array storage unit thermal and utilization responses during airflow imbalances. This is done with the stress test proposed for IT in containment to mimic possible mismatch and cascade failure scenarios. It is found that downstream HDDs are most prone to overheating and loss in utilization during an airflow imbalance. This was proven to undermine the storage capacity of the hard disk drives. An IT level airflow prediction model is discussed for the storage unit and validated for different fan speeds. In the second part, a computational fluid dynamics model is created for a high density open rack based on the active flow curve method. Here, the measured airflow response curves for the open compute IT (storage and compute servers) are used to build compact models and run rack level testing for IT air systems sensitivity and create a rack level AFC (active flow curve) airflow demand prediction model. Finally, the experimental characterization data is used to build an aisle level model (POD) that incorporates IT fan control systems (FCS). This modeling approach yields shorter uptime during chiller failure due to increased recirculation induced by increased IT airflow demand during cases such as chiller failure or high economizer temperatures.
This column provides examples of data access patterns ranging from completely local user-driven methods to cloud-based tools to illustrate concepts related to application programmer interface (API) design, and the use and role of API concepts in cloud computing.
Network Topology Discovery and Inventory Listing are two of the primary features of modern network monitoring systems (NMS). Current NMSs rely heavily on active scanning techniques for discovering and mapping network information. Although this approach works, it introduces some major drawbacks such as the performance impact it can exact, specially in larger network environments. As a consequence, scans are often run less frequently which can result in stale information being presented and used by the network monitoring system. Alternatively, some NMSs rely on their agents being deployed on the hosts they monitor. In this article, we present a new approach to Network Topology Discovery and Network Inventory Listing using only passive monitoring and scanning techniques. The proposed techniques rely solely on the event logs produced by the hosts and network devices present within a network. Finally, we discuss some of the advantages and disadvantages of our approach.
The NOVI Information Model (IM) and the corresponding data models are the glue between the software components in the NOVI Service Layer. The IM enables the communication among the various components of the NOVI Architecture and supports the various functionalities it offers. The NOVI IM consists of three main ontologies: resource, monitoring and policy ontology that have evolved over time to accommodate the emerging requirements of the NOVI architecture. This article presents the NOVI IM and its ontologies, together with an overview of how the NOVI software prototypes have benefited from using the IM.
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The recently emerged Cloud Computing paradigm poses new management challenges because of its complex, heterogeneous infrastructure. A cloud contains infrastructure (Servers, Storage, Networks), applications (web apps, database, backup etc.) from various vendors. Generally, different vendor products are managed (discovery, provisioning, monitoring etc.) by their own proprietary management software. Today, in clouds there is no standard way to manage infrastructure and applications using a single management framework. This will cause cloud management a complex task and creates interoperability issues. The Cloud infrastructure cannot be easily replaced due to dependency on the management software. In this paper we will present various independent CIM (Common Information Model) based Management models available as today, their applicability to cloud infrastructure, advantages etc.
Conference Paper
Virtualized environments today allow managing and migrating workloads more flexibly such that goals of minimizing power usage in data centers can be pursued. Automated closed-loop controllers are often used for exercising control over workload placement and migration in a data center. The combination with power, airflow and temperature control can even more contribute to energy efficiency in a data center crossing the traditionally separated domains of IT management and facility management. These Power/Workload Control Systems (PWCS) are actively managing IT systems and their behaviors - changes that have impact on other IT management systems in the data center. Consequently, PWCS should be carefully integrated into an overall data center IT management architecture such that changes affected by the PWCS are properly propagated to other IT management systems and vice versa, definitions for the PWCS (e.g. about their control domain and their control policies) are obtained from centrally managed repositories such as CMDB. The reality, however, is that autonomous control systems are constructed and operated in isolation from other IT management systems in a data center. This paper describes how an autonomous PWCS can be integrated into an IT management architecture and can be connected with other management systems that are used in a data center.
Conference Paper
Ever increasing data center complexity poses a significant burden on IT administrators. This burden can become unbearable without the help of self-managed systems that monitor themselves and automatically modify their state in order to carry out business processes according to high level objectives set by service level agreements (SLA) and policies. Among the key IT management tasks that must be automated and enhanced to realize the idea of an autonomic and highly dynamic data center, are discovery, configuration, and provisioning of new servers. In this direction, this paper describes pre-boot capabilities endowing the bare metal server with the ability to be discovered, queried, configured, and provisioned at time zero using industry standards like Common Information Model (CIM), CIM-XML, and Service Location Protocol (SLP). The capabilities are implemented as a payload of an Intel® Extensible Firmware Interface (EFI)-compliant BIOS, the Intel® Rapid Boot Toolkit (IRBT), allowing a resource manager to discover a new server during pre-boot, possibly in a bare-metal state, and then perform an asset inventory, configure the server including CPU-specific settings, and provision it with the most appropriate image. All these tasks may be carried out based on decisions taken by the resource manager according to server capabilities, application requirements, SLAs, and high-level policies. Additionally, this system uses reliable protocols, thus minimizing error possibilities.
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