70-413 Designing for Automated Server Installation part 1 of 14

August 28, 2016 | 190 views

70-413 Designing and Implementing a Server Infrastructure

Design and plan an automated server installation strategy
- Design considerations including images and bare metal/virtual deployment; design a server implementation using Windows Assessment and Deployment Kit (ADK); design a virtual server deployment
-Plan for deploying servers to Microsoft Azure infrastructure as a service (IaaS); plan for deploying servers to public and private cloud by using AppController and Windows PowerShell; plan for multicast deployment; plan for Windows Deployment Services (WDS)

Spotlight

IT Resources S.A

Somos un equipo de profesionales comprometidos en generar soluciones IT de calidad.

OTHER ARTICLES
IT SYSTEMS MANAGEMENT

Data Center as a Service Is the Way of the Future

Article | July 27, 2022

Data Center as a Service (DCaaS) is a hosting service that gives clients access to actual data center infrastructure and amenities. Through a Wide-Area Network, DCaaS enables clients to remotely access the provider's storage, server, and networking capabilities (WAN). Businesses can tackle their on-site data center's logistical and financial issues by outsourcing to a service provider. Many enterprises rely on DCaaS to overcome the physical constraints of their on-site infrastructure or to offload the hosting and management of non-mission-critical applications. Businesses that require robust data management solutions but lack the necessary internal resources can adopt DCaaS. DCaaS is the perfect answer for companies that are struggling with a lack of IT help or a lack of funding for system maintenance. Added benefits data Center as a Service allows businesses to be independent of their physical infrastructure: A single-provider API Data centers without Staff Effortlessly handle the influx of data Data centers in regions with more stable climates Data Center as a Service helps democratize the data center itself, allowing companies that could never afford the huge investments that have gotten us this far to benefit from these developments. This is perhaps the most important, as Infrastructure-as-a-Service enables smaller companies to get started without a huge investment. Conclusion Data center as a service (DCaaS) enables clients to access a data center remotely and its features, whereas data center services might include complete management of an organization's on-premises infrastructure resources. IT can be outsourced using data center services to manage an organization's network, storage, computing, cloud, and maintenance. The infrastructure of many businesses is outsourced to increase operational effectiveness, size, and cost-effectiveness. It might be challenging to manage your existing infrastructure while keeping up with the pace of innovation, but it's critical to be on the cutting edge of technology. Organizations may stay future-ready by working with a vendor that can supply DCaaS and data center services.

Read More
APPLICATION INFRASTRUCTURE

Enhancing Rack-Level Security to Enable Rapid Innovation

Article | August 3, 2022

IT and data center administrators are under pressure to foster quicker innovation. For workers and customers to have access to digital experiences, more devices must be deployed, and larger enterprise-to-edge networks must be managed. The security of distributed networks has suffered as a result of this rapid growth, though. Some colocation providers can install custom locks for your cabinet if necessary due to the varying compliance standards and security needs for distinct applications. However, physical security measures are still of utmost importance because theft and social engineering can affect hardware as well as data. Risk Companies Face Remote IT work continue on the long run Attacking users is the easiest way into networks IT may be deploying devices with weak controls When determining whether rack-level security is required, there are essentially two critical criteria to take into account. The first is the level of sensitivity of the data stored, and the second is the importance of the equipment in a particular rack to the facility's continuing functioning. Due to the nature of the data being handled and kept, some processes will always have a higher risk profile than others. Conclusion Data centers must rely on a physically secure perimeter that can be trusted. Clients, in particular, require unwavering assurance that security can be put in place to limit user access and guarantee that safety regulations are followed. Rack-level security locks that ensure physical access limitations are crucial to maintaining data center space security. Compared to their mechanical predecessors, electronic rack locks or "smart locks" offer a much more comprehensive range of feature-rich capabilities.

Read More
APPLICATION INFRASTRUCTURE

Infrastructure Lifecycle Management Best Practices

Article | August 8, 2022

As your organization scales, inevitably, so too will its infrastructure needs. From physical spaces to personnel, devices to applications, physical security to cybersecurity – all these resources will continue to grow to meet the changing needs of your business operations. To manage your changing infrastructure throughout its entire lifecycle, your organization needs to implement a robust infrastructure lifecycle management program that’s designed to meet your particular business needs. In particular, IT asset lifecycle management (ITALM) is becoming increasingly important for organizations across industries. As threats to organizations’ cybersecurity become more sophisticated and successful cyberattacks become more common, your business needs (now, more than ever) to implement an infrastructure lifecycle management strategy that emphasizes the security of your IT infrastructure. In this article, we’ll explain why infrastructure management is important. Then we’ll outline steps your organization can take to design and implement a program and provide you with some of the most important infrastructure lifecycle management best practices for your business. What Is the Purpose of Infrastructure Lifecycle Management? No matter the size or industry of your organization, infrastructure lifecycle management is a critical process. The purpose of an infrastructure lifecycle management program is to protect your business and its infrastructure assets against risk. Today, protecting your organization and its customer data from malicious actors means taking a more active approach to cybersecurity. Simply put, recovering from a cyber attack is more difficult and expensive than protecting yourself from one. If 2020 and 2021 have taught us anything about cybersecurity, it’s that cybercrime is on the rise and it’s not slowing down anytime soon. As risks to cybersecurity continue to grow in number and in harm, infrastructure lifecycle management and IT asset management are becoming almost unavoidable. In addition to protecting your organization from potential cyberattacks, infrastructure lifecycle management makes for a more efficient enterprise, delivers a better end user experience for consumers, and identifies where your organization needs to expand its infrastructure. Some of the other benefits that come along with comprehensive infrastructure lifecycle management program include: More accurate planning; Centralized and cost-effective procurement; Streamlined provisioning of technology to users; More efficient maintenance; Secure and timely disposal. A robust infrastructure lifecycle management program helps your organization to keep track of all the assets running on (or attached to) your corporate networks. That allows you to catalog, identify and track these assets wherever they are, physically and digitally. While this might seem simple enough, infrastructure lifecycle management and particularly ITALM has become more complex as the diversity of IT assets has increased. Today organizations and their IT teams are responsible for managing hardware, software, cloud infrastructure, SaaS, and connected device or IoT assets. As the number of IT assets under management has soared for most organizations in the past decade, a comprehensive and holistic approach to infrastructure lifecycle management has never been more important. Generally speaking, there are four major stages of asset lifecycle management. Your organization’s infrastructure lifecycle management program should include specific policies and processes for each of the following steps: Planning. This is arguably the most important step for businesses and should be conducted prior to purchasing any assets. During this stage, you’ll need to identify what asset types are required and in what number; compile and verify the requirements for each asset; and evaluate those assets to make sure they meet your service needs. Acquisition and procurement. Use this stage to identify areas for purchase consolidation with the most cost-effective vendors, negotiate warranties and bulk purchases of SaaS and cloud infrastructure assets. This is where lack of insights into actual asset usage can potentially result in overpaying for assets that aren’t really necessary. For this reason, timely and accurate asset data is crucial for effective acquisition and procurement. Maintenance, upgrades and repair. All assets eventually require maintenance, upgrades and repairs. A holistic approach to infrastructure lifecycle management means tracking these needs and consolidating them into a single platform across all asset types. Disposal. An outdated or broken asset needs to be disposed of properly, especially if it contains sensitive information. For hardware, assets that are older than a few years are often obsolete, and assets that fall out of warranty are typically no longer worth maintaining. Disposal of cloud infrastructure assets is also critical because data stored in the cloud can stay there forever. Now that we’ve outlined the purpose and basic stages of infrastructure lifecycle management, it’s time to look at the steps your organization can take to implement it.

Read More
APPLICATION INFRASTRUCTURE

The Drive with Direction: The Path of Enterprise IT Infrastructure

Article | June 6, 2022

Introduction It is hard to manage a modern firm without a convenient and adaptable IT infrastructure. When properly set up and networked, technology can improve back-office processes, increase efficiency, and simplify communication. IT infrastructure can be utilized to supply services or resources both within and outside of a company, as well as to its customers. IT infrastructure when adequately deployed aids organizations in achieving their objectives and increasing profits. IT infrastructure is made up of numerous components that must be integrated for your company's infrastructure to be coherent and functional. These components work in unison to guarantee that your systems and business as a whole run smoothly. Enterprise IT Infrastructure Trends Consumption-based pricing models are becoming more popular among enterprise purchasers, a trend that began with software and has now spread to hardware. This transition from capital to operational spending lowers risk, frees up capital, and improves flexibility. As a result, infrastructure as a service (IaaS) and platform as a service (PaaS) revenues increased by 53% from 2015 to 2016, making them the fastest-growing cloud and infrastructure services segments. The transition to as-a-service models is significant given that a unit of computing or storage in the cloud can be quite cheaper in terms of the total cost of ownership than a unit on-premises. While businesses have been migrating their workloads to the public cloud for years, there has been a new shift among large corporations. Many companies, including Capital One, GE, Netflix, Time Inc., and others, have downsized or removed their private data centers in favor of shifting their operations to the cloud. Cybersecurity remains a high priority for the C-suite and the board of directors. Attacks are increasing in number and complexity across all industries, with 80% of technology executives indicating that their companies are unable to construct a robust response. Due to lack of cybersecurity experts, many companies can’t get the skills they need on the inside, so they have to use managed security services. Future of Enterprise IT Infrastructure Companies can adopt the 'As-a-Service' model to lower entry barriers and begin testing future innovations on the cloud's basis. Domain specialists in areas like healthcare and manufacturing may harness AI's potential to solve some of their businesses' most pressing problems. Whether in a single cloud or across several clouds, businesses want an architecture that can expand to support the rapid evolution of their apps and industry for decades. For enterprise-class visibility and control across all clouds, the architecture must provide a common control plane that supports native cloud Application Programming Interfaces (APIs) as well as enhanced networking and security features. Conclusion The scale of disruption in the IT infrastructure sector is unparalleled, presenting enormous opportunities and hazards for industry stakeholders and their customers. Technology infrastructure executives must restructure their portfolios and rethink their go-to-market strategies to drive growth. They should also invest in the foundational competencies required for long-term success, such as digitization, analytics, and agile development. Data center companies that can solve the industry's challenges, as well as service providers that can scale quickly without limits and provide intelligent outcome-based models. This helps their clients achieve their business objectives through a portfolio of 'As-a-Service' models, will have a bright future.

Read More

Spotlight

IT Resources S.A

Somos un equipo de profesionales comprometidos en generar soluciones IT de calidad.

Related News

HYPER-CONVERGED INFRASTRUCTURE

Inspur Announces MLPerf v2.0 Results for AI Servers

Inspur | July 04, 2022

The open engineering consortium MLCommons released the latest MLPerf Training v2.0 results, with Inspur AI servers leading in closed division single-node performance. MLPerf is the world’s most influential benchmark for AI performance. It is managed by MLCommons, with members from more than 50 global leading AI companies and top academic institutions, including Inspur Information, Google, Facebook, NVIDIA, Intel, Harvard University, Stanford University, and the University of California, Berkeley. MLPerf AI Training benchmarks are held twice a year to track improvements in computing performance and provide authoritative data guidance for users. The latest MLPerf Training v2.0 attracted 21 global manufacturers and research institutions, including Inspur Information, Google, NVIDIA, Baidu, Intel-Habana, and Graphcore. There were 264 submissions, a 50% increase over the previous round. The eight AI benchmarks cover current mainstream usage AI scenarios, including image classification with ResNet, medical image segmentation with 3D U-Net, light-weight object detection with RetinaNet, heavy-weight object detection with Mask R-CNN, speech recognition with RNN-T, natural language processing with BERT, recommendation with DLRM, and reinforcement learning with MiniGo. Among the closed division benchmarks for single-node systems, Inspur Information with its high-end AI servers was the top performer in natural language processing with BERT, recommendation with DLRM, and speech recognition with RNN-T. It won the most titles among single-node system submitters. For mainstream high-end AI servers equipped with eight NVIDIA A100 Tensor Core GPUs, Inspur Information AI servers were top ranked in five tasks (BERT, DLRM, RNN-T, ResNet and Mask R-CNN). Continuing to lead in AI computing performance Inspur AI servers continue to achieve AI performance breakthroughs through comprehensive software and hardware optimization. Compared to the MLPerf v0.5 results in 2018, Inspur AI servers showed significant performance improvements of up to 789% for typical 8-GPU server models. The leading performance of Inspur AI servers in MLPerf is a result of its outstanding design innovation and full-stack optimization capabilities for AI. Focusing on the bottleneck of intensive I/O transmission in AI training, the PCIe retimer-free design of Inspur AI servers allows for high-speed interconnection between CPUs and GPUs for reduced communication delays. For high-load, multi-GPU collaborative task scheduling, data transmission between NUMA nodes and GPUs is optimized to ensure that data I/O in training tasks is at the highest performance state. In terms of heat dissipation, Inspur Information takes the lead in deploying eight 500W high-end NVIDIA Tensor Core A100 GPUs in a 4U space, and supports air cooling and liquid cooling. Meanwhile, Inspur AI servers continue to optimize pre-training data processing performance, and adopt combined optimization strategies such as hyperparameter and NCCL parameter, as well as the many enhancements provided by the NVIDIA AI software stack, to maximize AI model training performance. Greatly improving Transformer training performance Pre-trained massive models based on the Transformer neural network architecture have led to the development of a new generation of AI algorithms. The BERT model in the MLPerf benchmarks is based on the Transformer architecture. Transformer’s concise and stackable architecture makes the training of massive models with huge parameters possible. This has led to a huge improvement in large model algorithms, but necessitates higher requirements for processing performance, communication interconnection, I/O performance, parallel extensions, topology and heat dissipation for AI systems. In the BERT benchmark, Inspur AI servers further improved BERT training performance by using methods including optimizing data preprocessing, improving dense parameter communication between NVIDIA GPUs and automatic optimization of hyperparameters, etc. Inspur Information AI servers can complete BERT model training of approximately 330 million parameters in just 15.869 minutes using 2,850,176 pieces of data from the Wikipedia data set, a performance improvement of 309% compared to the top performance of 49.01 minutes in Training v0.7. To this point, Inspur AI servers have won the MLPerf Training BERT benchmark for the third consecutive time. Inspur Information’s two AI servers with top scores in MLPerf Training v2.0 are NF5488A5 and NF5688M6. The NF5488A5 is one of the first servers in the world to support eight NVIDIA A100 Tensor Core GPUs with NVIDIA NVLink technology and two AMD Milan CPUs in a 4U space. It supports both liquid cooling and air cooling. It has won a total of 40 MLPerf titles. NF5688M6 is a scalable AI server designed for large-scale data center optimization. It supports eight NVIDIA A100 Tensor Core GPUs and two Intel Ice Lake CPUs, up to 13 PCIe Gen4 IO, and has won a total of 25 MLPerf titles. About Inspur Information Inspur Information is a leading provider of data center infrastructure, cloud computing, and AI solutions. It is the world’s 2nd largest server manufacturer. Through engineering and innovation, Inspur Information delivers cutting-edge computing hardware design and extensive product offerings to address important technology sectors such as open computing, cloud data center, AI, and deep learning. Performance-optimized and purpose-built, our world-class solutions empower customers to tackle specific workloads and real-world challenges.

Read More

HYPER-CONVERGED INFRASTRUCTURE

TYAN showcases optimized HPC platforms at ISC 2022

Tyan Computer | May 31, 2022

TYAN, an industry-leading server platform design manufacturer and MiTAC Computing Technology Corporation subsidiary, will demonstrate its latest server platforms, which are powered by 3rd Gen Intel® Xeon® Scalable processors and optimized for HPC and AI markets, at ISC 2022 in Hamburg, Germany, from May 30th to June 1st, booth#D400. "The HPC market growth is heavily driven by new technologies and the increasing application of big data analytics. This is creating the need for better computing infrastructure to process large volumes of data available in the market. TYAN's HPC server platforms are based on 3rd Gen Intel Xeon Scalable processors which are foundational to help businesses and organizations accelerate the development of the next-generation HPC and AI system architectures." Danny Hsu, Vice President of MiTAC Computing Technology Corporation's Server Infrastructure Business Unit The Thunder HX FT83A-B7129 from TYAN is a 4U dual-socket supercomputer that can accommodate up to 10 high-performance GPU cards. The FT83A-B7129 platform provides great heterogeneous computing capacity for a variety of GPU-based scientific high-performance computing, AI training, inference, and deep learning applications, thanks to dual 3rd Gen Intel Xeon Scalable CPUs and 32 DDR4 DIMM slots. In addition, the system supports up to four U.2 NVMe devices in twelve 3.5-inch tool-less drive bays. The Thunder HX FT65T-B5642 is a 4U single-socket pedestal server designed for small HPC tasks that require a lot of processing power at the desk. A single 3rd Generation Intel Xeon Scalable processor, eight DDR4-3200 DIMM slots, eight 3.5-inch SATA, and two NVMe U.2 hot-swap, tool-less drive bays are included in the system. For GPUs to speed up HPC workloads, the FT65T-B5642 has two double-wide PCIe 4.0 x16 slots. The Thunder SX TS65-B7126 is a software-defined storage 2U dual-socket hybrid storage server. There are 16 DDR4-3200 DIMM slots, twelve 3.5-inch SATA hot-swap, tool-less drive bays with support for up to four NVMe U.2 devices, and two rear 2.5-inch hot-swap, tool-less SATA drive bays for boot drive deployment in this system. The Tempest CX S5560 is a Micro-ATX server motherboard with a single Intel Xeon E-2300 processor, four DDR4-3200 DIMM slots, three PCIe slots, up to eight SATA 6G connections, two NVMe M.2 slots, and dual 10GbE onboard LAN ports from TYAN. In 5G networks, the motherboard is excellent for multi-access edge computing servers and service access servers in a CSP environment.

Read More

Global IT Infrastructure Monitoring Tool Market Will Grow Demand

Reports Observer | June 14, 2019

IT Infrastructure Monitoring Tools (ITIM) capture the availability of the IT infrastructure components that reside in a data center or are hosted in the cloud as infrastructure as a service (IaaS). These tools monitor and collate the availability and resource utilization metrics of servers, networks, database instances, hypervisors and storage. Notably, these tools collect metrics in real time and perform historical data analysis or trending of the elements they monitor. The global IT Infrastructure Monitoring Tool market was xx million US$ in 2018 and is expected to xx million US$ by the end of 2026, growing at a CAGR of xx% between 2019 and 2026. Different leading key players have been profiled to get better insights into the businesses. It offers detailed elaboration on different top-level industries which are functioning in global regions. It includes informative data such as company overview, contact information, and some significant strategies followed by key players.

Read More

HYPER-CONVERGED INFRASTRUCTURE

Inspur Announces MLPerf v2.0 Results for AI Servers

Inspur | July 04, 2022

The open engineering consortium MLCommons released the latest MLPerf Training v2.0 results, with Inspur AI servers leading in closed division single-node performance. MLPerf is the world’s most influential benchmark for AI performance. It is managed by MLCommons, with members from more than 50 global leading AI companies and top academic institutions, including Inspur Information, Google, Facebook, NVIDIA, Intel, Harvard University, Stanford University, and the University of California, Berkeley. MLPerf AI Training benchmarks are held twice a year to track improvements in computing performance and provide authoritative data guidance for users. The latest MLPerf Training v2.0 attracted 21 global manufacturers and research institutions, including Inspur Information, Google, NVIDIA, Baidu, Intel-Habana, and Graphcore. There were 264 submissions, a 50% increase over the previous round. The eight AI benchmarks cover current mainstream usage AI scenarios, including image classification with ResNet, medical image segmentation with 3D U-Net, light-weight object detection with RetinaNet, heavy-weight object detection with Mask R-CNN, speech recognition with RNN-T, natural language processing with BERT, recommendation with DLRM, and reinforcement learning with MiniGo. Among the closed division benchmarks for single-node systems, Inspur Information with its high-end AI servers was the top performer in natural language processing with BERT, recommendation with DLRM, and speech recognition with RNN-T. It won the most titles among single-node system submitters. For mainstream high-end AI servers equipped with eight NVIDIA A100 Tensor Core GPUs, Inspur Information AI servers were top ranked in five tasks (BERT, DLRM, RNN-T, ResNet and Mask R-CNN). Continuing to lead in AI computing performance Inspur AI servers continue to achieve AI performance breakthroughs through comprehensive software and hardware optimization. Compared to the MLPerf v0.5 results in 2018, Inspur AI servers showed significant performance improvements of up to 789% for typical 8-GPU server models. The leading performance of Inspur AI servers in MLPerf is a result of its outstanding design innovation and full-stack optimization capabilities for AI. Focusing on the bottleneck of intensive I/O transmission in AI training, the PCIe retimer-free design of Inspur AI servers allows for high-speed interconnection between CPUs and GPUs for reduced communication delays. For high-load, multi-GPU collaborative task scheduling, data transmission between NUMA nodes and GPUs is optimized to ensure that data I/O in training tasks is at the highest performance state. In terms of heat dissipation, Inspur Information takes the lead in deploying eight 500W high-end NVIDIA Tensor Core A100 GPUs in a 4U space, and supports air cooling and liquid cooling. Meanwhile, Inspur AI servers continue to optimize pre-training data processing performance, and adopt combined optimization strategies such as hyperparameter and NCCL parameter, as well as the many enhancements provided by the NVIDIA AI software stack, to maximize AI model training performance. Greatly improving Transformer training performance Pre-trained massive models based on the Transformer neural network architecture have led to the development of a new generation of AI algorithms. The BERT model in the MLPerf benchmarks is based on the Transformer architecture. Transformer’s concise and stackable architecture makes the training of massive models with huge parameters possible. This has led to a huge improvement in large model algorithms, but necessitates higher requirements for processing performance, communication interconnection, I/O performance, parallel extensions, topology and heat dissipation for AI systems. In the BERT benchmark, Inspur AI servers further improved BERT training performance by using methods including optimizing data preprocessing, improving dense parameter communication between NVIDIA GPUs and automatic optimization of hyperparameters, etc. Inspur Information AI servers can complete BERT model training of approximately 330 million parameters in just 15.869 minutes using 2,850,176 pieces of data from the Wikipedia data set, a performance improvement of 309% compared to the top performance of 49.01 minutes in Training v0.7. To this point, Inspur AI servers have won the MLPerf Training BERT benchmark for the third consecutive time. Inspur Information’s two AI servers with top scores in MLPerf Training v2.0 are NF5488A5 and NF5688M6. The NF5488A5 is one of the first servers in the world to support eight NVIDIA A100 Tensor Core GPUs with NVIDIA NVLink technology and two AMD Milan CPUs in a 4U space. It supports both liquid cooling and air cooling. It has won a total of 40 MLPerf titles. NF5688M6 is a scalable AI server designed for large-scale data center optimization. It supports eight NVIDIA A100 Tensor Core GPUs and two Intel Ice Lake CPUs, up to 13 PCIe Gen4 IO, and has won a total of 25 MLPerf titles. About Inspur Information Inspur Information is a leading provider of data center infrastructure, cloud computing, and AI solutions. It is the world’s 2nd largest server manufacturer. Through engineering and innovation, Inspur Information delivers cutting-edge computing hardware design and extensive product offerings to address important technology sectors such as open computing, cloud data center, AI, and deep learning. Performance-optimized and purpose-built, our world-class solutions empower customers to tackle specific workloads and real-world challenges.

Read More

HYPER-CONVERGED INFRASTRUCTURE

TYAN showcases optimized HPC platforms at ISC 2022

Tyan Computer | May 31, 2022

TYAN, an industry-leading server platform design manufacturer and MiTAC Computing Technology Corporation subsidiary, will demonstrate its latest server platforms, which are powered by 3rd Gen Intel® Xeon® Scalable processors and optimized for HPC and AI markets, at ISC 2022 in Hamburg, Germany, from May 30th to June 1st, booth#D400. "The HPC market growth is heavily driven by new technologies and the increasing application of big data analytics. This is creating the need for better computing infrastructure to process large volumes of data available in the market. TYAN's HPC server platforms are based on 3rd Gen Intel Xeon Scalable processors which are foundational to help businesses and organizations accelerate the development of the next-generation HPC and AI system architectures." Danny Hsu, Vice President of MiTAC Computing Technology Corporation's Server Infrastructure Business Unit The Thunder HX FT83A-B7129 from TYAN is a 4U dual-socket supercomputer that can accommodate up to 10 high-performance GPU cards. The FT83A-B7129 platform provides great heterogeneous computing capacity for a variety of GPU-based scientific high-performance computing, AI training, inference, and deep learning applications, thanks to dual 3rd Gen Intel Xeon Scalable CPUs and 32 DDR4 DIMM slots. In addition, the system supports up to four U.2 NVMe devices in twelve 3.5-inch tool-less drive bays. The Thunder HX FT65T-B5642 is a 4U single-socket pedestal server designed for small HPC tasks that require a lot of processing power at the desk. A single 3rd Generation Intel Xeon Scalable processor, eight DDR4-3200 DIMM slots, eight 3.5-inch SATA, and two NVMe U.2 hot-swap, tool-less drive bays are included in the system. For GPUs to speed up HPC workloads, the FT65T-B5642 has two double-wide PCIe 4.0 x16 slots. The Thunder SX TS65-B7126 is a software-defined storage 2U dual-socket hybrid storage server. There are 16 DDR4-3200 DIMM slots, twelve 3.5-inch SATA hot-swap, tool-less drive bays with support for up to four NVMe U.2 devices, and two rear 2.5-inch hot-swap, tool-less SATA drive bays for boot drive deployment in this system. The Tempest CX S5560 is a Micro-ATX server motherboard with a single Intel Xeon E-2300 processor, four DDR4-3200 DIMM slots, three PCIe slots, up to eight SATA 6G connections, two NVMe M.2 slots, and dual 10GbE onboard LAN ports from TYAN. In 5G networks, the motherboard is excellent for multi-access edge computing servers and service access servers in a CSP environment.

Read More

Global IT Infrastructure Monitoring Tool Market Will Grow Demand

Reports Observer | June 14, 2019

IT Infrastructure Monitoring Tools (ITIM) capture the availability of the IT infrastructure components that reside in a data center or are hosted in the cloud as infrastructure as a service (IaaS). These tools monitor and collate the availability and resource utilization metrics of servers, networks, database instances, hypervisors and storage. Notably, these tools collect metrics in real time and perform historical data analysis or trending of the elements they monitor. The global IT Infrastructure Monitoring Tool market was xx million US$ in 2018 and is expected to xx million US$ by the end of 2026, growing at a CAGR of xx% between 2019 and 2026. Different leading key players have been profiled to get better insights into the businesses. It offers detailed elaboration on different top-level industries which are functioning in global regions. It includes informative data such as company overview, contact information, and some significant strategies followed by key players.

Read More

Events