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Closing in on the Intelligent Network

Enterprise networking is quickly shifting from a hardware/software construct to all-software. This means configuration management, system relationships and other architectural elements will transition from today’s admin/management approach to software development processes in short order.

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Faststream Technologies

Faststream technologies, a vanguard of technology solutions specializing in Product & System Engineering, Digital Transformation, IoT, Big Data, Security and Application Development with the global footprint across North America, EMEA and APAC.

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Hyper-Converged Infrastructure, Application Infrastructure

5 TIPS TO ENSURE NETWORK SECURITY OF INTERNAL IT INFRASTRUCTURE

Article | July 19, 2023

What Is IT Infrastructure Security? If you are reading this blog, we would like to assume that you are either an aspiring cybersecurity professional or a business owner looking for ways to improve their network security. A business IT infrastructure includes networks, software, hardware, equipment, and other facilities that make up an IT network. These networks are applied to establish, monitor, test, manage, deliver, and support IT services. So, IT infrastructure security describes the process of safeguarding the core networking infrastructure, and it is typically applied to enterprise IT environments. You can improve IT infrastructure security by installing protective solutions to block unauthorized access, theft, deletion, and data modification.

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Hyper-Converged Infrastructure, Windows Systems and Network

How to backup hyperconverged infrastructure

Article | July 11, 2023

Enterprises running hypervisors on hyper-converged infrastructure (HCI) systems typically have backup options available to them that are not available to those running on generic hardware. Such customers may also have additional backup challenges depending on the HCI vendor and hypervisor they have chosen. Let’s take a look.

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Hyper-Converged Infrastructure

Ensuring Long-Term Reliability of Technology Partners using HCI

Article | October 10, 2023

Building trust through HCI by unveiling strategies to ensure the long-term reliability of technology partnerships, cementing lasting collaborations in a dynamic business landscape through vendor stability. Contents 1. Introduction 2. How HCI Overcomes Infrastructural Challenges 3. Evaluation Criteria for Enterprise HCI 3.1. Distributed Storage Layer 3.2. Data Security 3.3. Data Reduction 4. Assessing Vendor Stability: Ensuring Long-Term Reliability of Partners 4.1. Vendor Track Record 4.2. Financial Stability 4.3. Customer Base and References 4.4. Product Roadmap and Innovation 4.5. Support and Maintenance 4.6. Partnerships and Ecosystem 4.7. Industry Recognition and Analyst Reports 4.8. Contracts and SLAs 5. Final Takeaway 1. Introduction When collaborating with a vendor, it is essential to evaluate their financial stability. This ensures that they are able to fulfil their obligations and deliver the promised services or goods. Prior to making contractual commitments, it is necessary to conduct due diligence to determine a vendor's financial health. This article examines when a vendor's financial viability must be evaluated, why to do so, and how vendor and contract management software can assist businesses. IT organizations of all sizes face numerous infrastructure difficulties. On one hand, they frequently receive urgent demands from the business to keep their organization agile and proactive while implementing new digital transformation initiatives. They also struggle to keep their budget under control, provide new resources swiftly, and manage the increasing complexity while maintaining a reasonable level of efficiency. For many organizations, a cloud-only IT strategy is not a viable option; as a result, there is a growing interest in hybrid scenarios that offer the best of both realms. By combining cloud and traditional IT infrastructures, there is a real danger of creating silos, going in the incorrect direction, and further complicating the overall infrastructure, thereby introducing inefficiencies. 2. How HCI Overcomes Infrastructural Challenges Hyper-converged infrastructures (HCI) surpass conventional infrastructures in terms of simplicity and adaptability. HCI enables organizations to conceal the complexity of their IT infrastructure while reaping the benefits of a cloud-like environment. HCI simplifies operations and facilitates the migration of on-premises data and applications to the cloud. HCI is a software-defined solution that abstracts and organizes CPU, memory, networking, and storage devices as resource pools, typically utilizing commodity x86-based hardware and virtualization software. It enables the administrator to rapidly combine and provision these resources as virtual machines and, more recently, as independent storage resources such as network-attached storage (NAS) filers and object stores. Management operations are also simplified, allowing for an increase in infrastructure productivity while reducing the number of operators and system administrators per virtual machine managed. HCI market and itssolutions can be categorized into three groups: Enterprise Solutions They have an extensive feature set, high scalability, core-to-cloud integrations, and tools that extend beyond traditional virtualization platform management and up the application stack. Small/Medium Enterprise Solutions Comparable to the previous category, but simplified and more affordable. The emphasis remains on simplifying the IT infrastructure for virtualized environments, with limited core-to-cloud integrations and a limited ecosystem of solutions. Vertical Solutions Designed for particular use cases or vertical markets, they are highly competitive in edge-cloud or edge-core deployments, but typically have a limited ecosystem of solutions. These solutions incorporate open-source hypervisors, such as KVM, to provide end-to-end support at lower costs. They are typically not very scalable, but they are efficient from a resource consumption standpoint. 3. Evaluation Criteria for Enterprise HCI 3.1 Distributed Storage Layer The distributed storage layer provides primary data storage service for virtual machines and is a crucial component of every HCI solution. Depending on the exposed protocol, they are typically presented as a virtual network-attached storage (NAS) or storage area network (SAN) and contain all of the data. There are three distributed storage layer approaches for HCI: Virtual storage appliance (VSA): A virtual machine administered by the same hypervisor as the other virtual machines in the node. A VSA is more flexible and can typically support multiple hypervisors, but this method may result in increased latency. Integrated within the hypervisor or the Operating System (OS): The storage layer is an extension of the hypervisor and does not require the preceding approach's components (VM and guest OS). The tight integration boosts overall performance, enhances workload telemetry, and fully exploits hypervisor characteristics, but the storage layer is not portable. Specialized storage nodes: The distributed storage layer is comprised of specialized nodes in order to achieve optimal performance consistency and scalability for both internal and external storage consumption. This strategy, which is typically more expensive than the alternatives for lesser configurations, is utilized. 3.2 Data Security Currently, all vendors offer sophisticated data protection against multiple failures, such as full node, single, and multiple-component issues. Distributed erasure coding safeguards information by balancing performance and data footprint efficiency. This equilibrium is made possible by modern CPUs with sophisticated instruction sets, new hardware such as NVMe and storage-class memory (SCM) devices, and data path optimizations. In addition, the evolution of storage technologies has played a pivotal role in enhancing data protection strategies. The introduction of high-capacity SSDs (Solid-State Drives) and advancements in storage virtualization have further strengthened the ability to withstand failures and ensure uninterrupted data availability. These technological innovations, combined with the relentless pursuit of redundancy and fault tolerance, have elevated the resilience of modern data storage systems. Furthermore, for data protection and security, compliance with rules, regulations, and laws is paramount. Governments and regulatory bodies across the globe have established stringent frameworks to safeguard sensitive information and ensure privacy. Adherence to laws such as the General Data Protection Regulation (GDPR) in Europe, the Health Insurance Portability and Accountability Act (HIPAA) in the United States, and various industry-specific regulations is non-negotiable. Organizations must fortify their data against technical vulnerabilities and align their practices with legal requirements to prevent costly fines, legal repercussions, and reputational damage. 3.3 Data Reduction Optimization of the data footprint is a crucial aspect of hyper-converged infrastructures. Deduplication, compression, and other techniques, such as thin provisioning, can significantly improve capacity utilization in virtualized environments, particularly for Virtual desktop infrastructure (VDI) use cases. Moreover, in order to optimize rack space utilization and achieve server balance, the number of storage devices that can be deployed on a single HCI node is restricted. 4. Assessing Vendor Stability: Ensuring Long-Term Reliability of Partners Here are some key factors that contribute to ensuring long-term reliability: 4.1 Vendor Track Record Assessing the vendor's track record and reputation in the industry is crucial. Look for established vendors with a history of delivering reliable products and services. A vendor that has been operating in the market for a significant period of time and has a strong customer base indicates stability. 4.2 Financial Stability Consider factors such as the vendor's profitability, revenue growth, and ability to invest in research and development. Financial stability ensures the vendor's ability to support their products and services over the long term. 4.3 Customer Base and References Look at the size and diversity of the vendor's customer base. A large and satisfied customer base indicates that the vendor's solutions have been adopted successfully by organizations. Request references from existing customers to get insights into their experience with the vendor's stability and support. 4.4 Product Roadmap and Innovation Assess the vendor's product roadmap and commitment to ongoing innovation. A vendor that actively invests in research and development, regularly updates their products, and introduces new features and enhancements demonstrates a long-term commitment to their solution's reliability and advancement. 4.5 Support and Maintenance Evaluate the vendor's support and maintenance services. Look for comprehensive support offerings, including timely bug fixes, security patches, and firmware updates. Understand the vendor's service-level agreements (SLAs), response times, and availability of technical support to ensure they can address any issues that may arise. 4.6 Partnerships and Ecosystem Consider the vendor's partnerships and ecosystem. A strong network of partners, including technology alliances and integrations with other industry-leading vendors, can contribute to long-term reliability. Partnerships demonstrate collaboration, interoperability, and a wider ecosystem that enhances the vendor's solution. 4.7 Industry Recognition and Analyst Reports Assess the vendor's industry recognition and performance in analyst reports. Look for accolades, awards, and positive evaluations from reputable industry analysts. These assessments provide independent validation of the vendor's stability and the reliability of their HCI solution. 4.8 Contracts and SLAs Review the vendor's contracts, service-level agreements, and warranties carefully. Ensure they provide appropriate guarantees for support, maintenance, and ongoing product updates throughout the expected lifecycle of the HCI solution. 5. Final Takeaway Evaluating a vendor's financial stability is crucial before entering into contractual commitments to ensure their ability to fulfill obligations. Hyper-converged infrastructure overcomes infrastructural challenges by simplifying operations, enabling cloud-like environments, and facilitating data and application migration. The HCI market offers enterprise, small/medium enterprise, and vertical solutions, each catering to different needs and requirements. Analysing enterprise HCI solutions requires careful consideration of various criteria. Each approach has its own advantages and considerations related to flexibility, performance, and cost. The mentioned techniques can significantly reduce the data footprint, particularly in use cases like VDI, while maintaining performance and efficiency. Organizations take decisions that align with their specific storage, security, and efficiency requirements by considering the evaluation criteria for enterprise HCI solutions. By considering these factors, organizations can make informed decisions and choose a vendor with a strong foundation of reliability, stability, and long-term commitment, ensuring the durability of their HCI infrastructure and minimizing risks associated with vendor instability.

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Verizon launches 5G fixed wireless in parts of 21 more cities

Article | April 20, 2021

Communications giant Verizon last week launched 5G for Business Internet in 20 new markets, targeting SMBs and enterprises alike. The fixed-wireless plans provide download speeds of 100Mbps ($69/month), 200Mbps ($99/month), and 400Mbps ($199/month) with no data limits. Upload speeds are slower. Verizon is also offering a 10-year price lock for new customers with no long-term contract required. “As 5G Business Internet scales into new cities, businesses of all sizes can gain access to the superfast speeds, low latency and next-gen applications enabled by 5G Ultra-Wideband, with no throttling or data limits,” Tami Erwin, CEO of Verizon Business, said in a statement. “We’ll continue to expand the 5G Business Internet footprint and bring the competitive pricing, capability, and flexibility of our full suite of products and services to more and more businesses all over the country.” The service was previously launched in parts of Chicago, Houston and Los Angeles. Verizon started rolling out 5G services last year using lower spectrum bands. According to a study by IHS Markit’s RootMetrics, Verizon offers speeds similar to those of T-Mobile but behind AT&T.

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Hyper-Converged Infrastructure, Application Infrastructure

Designing an Advanced Data Center for Hyper-Converged Infrastructure

Article | July 19, 2023

What Is IT Infrastructure Security? If you are reading this blog, we would like to assume that you are either an aspiring cybersecurity professional or a business owner looking for ways to improve their network security. A business IT infrastructure includes networks, software, hardware, equipment, and other facilities that make up an IT network. These networks are applied to establish, monitor, test, manage, deliver, and support IT services. So, IT infrastructure security describes the process of safeguarding the core networking infrastructure, and it is typically applied to enterprise IT environments. You can improve IT infrastructure security by installing protective solutions to block unauthorized access, theft, deletion, and data modification.

Read More
Hyper-Converged Infrastructure, Windows Systems and Network

Choosing the Right Tools for Hyper-Converged Management and Orchestration

Article | July 11, 2023

Enterprises running hypervisors on hyper-converged infrastructure (HCI) systems typically have backup options available to them that are not available to those running on generic hardware. Such customers may also have additional backup challenges depending on the HCI vendor and hypervisor they have chosen. Let’s take a look.

Read More
Hyper-Converged Infrastructure

Ensuring Long-Term Reliability of Technology Partners using HCI

Article | October 10, 2023

Building trust through HCI by unveiling strategies to ensure the long-term reliability of technology partnerships, cementing lasting collaborations in a dynamic business landscape through vendor stability. Contents 1. Introduction 2. How HCI Overcomes Infrastructural Challenges 3. Evaluation Criteria for Enterprise HCI 3.1. Distributed Storage Layer 3.2. Data Security 3.3. Data Reduction 4. Assessing Vendor Stability: Ensuring Long-Term Reliability of Partners 4.1. Vendor Track Record 4.2. Financial Stability 4.3. Customer Base and References 4.4. Product Roadmap and Innovation 4.5. Support and Maintenance 4.6. Partnerships and Ecosystem 4.7. Industry Recognition and Analyst Reports 4.8. Contracts and SLAs 5. Final Takeaway 1. Introduction When collaborating with a vendor, it is essential to evaluate their financial stability. This ensures that they are able to fulfil their obligations and deliver the promised services or goods. Prior to making contractual commitments, it is necessary to conduct due diligence to determine a vendor's financial health. This article examines when a vendor's financial viability must be evaluated, why to do so, and how vendor and contract management software can assist businesses. IT organizations of all sizes face numerous infrastructure difficulties. On one hand, they frequently receive urgent demands from the business to keep their organization agile and proactive while implementing new digital transformation initiatives. They also struggle to keep their budget under control, provide new resources swiftly, and manage the increasing complexity while maintaining a reasonable level of efficiency. For many organizations, a cloud-only IT strategy is not a viable option; as a result, there is a growing interest in hybrid scenarios that offer the best of both realms. By combining cloud and traditional IT infrastructures, there is a real danger of creating silos, going in the incorrect direction, and further complicating the overall infrastructure, thereby introducing inefficiencies. 2. How HCI Overcomes Infrastructural Challenges Hyper-converged infrastructures (HCI) surpass conventional infrastructures in terms of simplicity and adaptability. HCI enables organizations to conceal the complexity of their IT infrastructure while reaping the benefits of a cloud-like environment. HCI simplifies operations and facilitates the migration of on-premises data and applications to the cloud. HCI is a software-defined solution that abstracts and organizes CPU, memory, networking, and storage devices as resource pools, typically utilizing commodity x86-based hardware and virtualization software. It enables the administrator to rapidly combine and provision these resources as virtual machines and, more recently, as independent storage resources such as network-attached storage (NAS) filers and object stores. Management operations are also simplified, allowing for an increase in infrastructure productivity while reducing the number of operators and system administrators per virtual machine managed. HCI market and itssolutions can be categorized into three groups: Enterprise Solutions They have an extensive feature set, high scalability, core-to-cloud integrations, and tools that extend beyond traditional virtualization platform management and up the application stack. Small/Medium Enterprise Solutions Comparable to the previous category, but simplified and more affordable. The emphasis remains on simplifying the IT infrastructure for virtualized environments, with limited core-to-cloud integrations and a limited ecosystem of solutions. Vertical Solutions Designed for particular use cases or vertical markets, they are highly competitive in edge-cloud or edge-core deployments, but typically have a limited ecosystem of solutions. These solutions incorporate open-source hypervisors, such as KVM, to provide end-to-end support at lower costs. They are typically not very scalable, but they are efficient from a resource consumption standpoint. 3. Evaluation Criteria for Enterprise HCI 3.1 Distributed Storage Layer The distributed storage layer provides primary data storage service for virtual machines and is a crucial component of every HCI solution. Depending on the exposed protocol, they are typically presented as a virtual network-attached storage (NAS) or storage area network (SAN) and contain all of the data. There are three distributed storage layer approaches for HCI: Virtual storage appliance (VSA): A virtual machine administered by the same hypervisor as the other virtual machines in the node. A VSA is more flexible and can typically support multiple hypervisors, but this method may result in increased latency. Integrated within the hypervisor or the Operating System (OS): The storage layer is an extension of the hypervisor and does not require the preceding approach's components (VM and guest OS). The tight integration boosts overall performance, enhances workload telemetry, and fully exploits hypervisor characteristics, but the storage layer is not portable. Specialized storage nodes: The distributed storage layer is comprised of specialized nodes in order to achieve optimal performance consistency and scalability for both internal and external storage consumption. This strategy, which is typically more expensive than the alternatives for lesser configurations, is utilized. 3.2 Data Security Currently, all vendors offer sophisticated data protection against multiple failures, such as full node, single, and multiple-component issues. Distributed erasure coding safeguards information by balancing performance and data footprint efficiency. This equilibrium is made possible by modern CPUs with sophisticated instruction sets, new hardware such as NVMe and storage-class memory (SCM) devices, and data path optimizations. In addition, the evolution of storage technologies has played a pivotal role in enhancing data protection strategies. The introduction of high-capacity SSDs (Solid-State Drives) and advancements in storage virtualization have further strengthened the ability to withstand failures and ensure uninterrupted data availability. These technological innovations, combined with the relentless pursuit of redundancy and fault tolerance, have elevated the resilience of modern data storage systems. Furthermore, for data protection and security, compliance with rules, regulations, and laws is paramount. Governments and regulatory bodies across the globe have established stringent frameworks to safeguard sensitive information and ensure privacy. Adherence to laws such as the General Data Protection Regulation (GDPR) in Europe, the Health Insurance Portability and Accountability Act (HIPAA) in the United States, and various industry-specific regulations is non-negotiable. Organizations must fortify their data against technical vulnerabilities and align their practices with legal requirements to prevent costly fines, legal repercussions, and reputational damage. 3.3 Data Reduction Optimization of the data footprint is a crucial aspect of hyper-converged infrastructures. Deduplication, compression, and other techniques, such as thin provisioning, can significantly improve capacity utilization in virtualized environments, particularly for Virtual desktop infrastructure (VDI) use cases. Moreover, in order to optimize rack space utilization and achieve server balance, the number of storage devices that can be deployed on a single HCI node is restricted. 4. Assessing Vendor Stability: Ensuring Long-Term Reliability of Partners Here are some key factors that contribute to ensuring long-term reliability: 4.1 Vendor Track Record Assessing the vendor's track record and reputation in the industry is crucial. Look for established vendors with a history of delivering reliable products and services. A vendor that has been operating in the market for a significant period of time and has a strong customer base indicates stability. 4.2 Financial Stability Consider factors such as the vendor's profitability, revenue growth, and ability to invest in research and development. Financial stability ensures the vendor's ability to support their products and services over the long term. 4.3 Customer Base and References Look at the size and diversity of the vendor's customer base. A large and satisfied customer base indicates that the vendor's solutions have been adopted successfully by organizations. Request references from existing customers to get insights into their experience with the vendor's stability and support. 4.4 Product Roadmap and Innovation Assess the vendor's product roadmap and commitment to ongoing innovation. A vendor that actively invests in research and development, regularly updates their products, and introduces new features and enhancements demonstrates a long-term commitment to their solution's reliability and advancement. 4.5 Support and Maintenance Evaluate the vendor's support and maintenance services. Look for comprehensive support offerings, including timely bug fixes, security patches, and firmware updates. Understand the vendor's service-level agreements (SLAs), response times, and availability of technical support to ensure they can address any issues that may arise. 4.6 Partnerships and Ecosystem Consider the vendor's partnerships and ecosystem. A strong network of partners, including technology alliances and integrations with other industry-leading vendors, can contribute to long-term reliability. Partnerships demonstrate collaboration, interoperability, and a wider ecosystem that enhances the vendor's solution. 4.7 Industry Recognition and Analyst Reports Assess the vendor's industry recognition and performance in analyst reports. Look for accolades, awards, and positive evaluations from reputable industry analysts. These assessments provide independent validation of the vendor's stability and the reliability of their HCI solution. 4.8 Contracts and SLAs Review the vendor's contracts, service-level agreements, and warranties carefully. Ensure they provide appropriate guarantees for support, maintenance, and ongoing product updates throughout the expected lifecycle of the HCI solution. 5. Final Takeaway Evaluating a vendor's financial stability is crucial before entering into contractual commitments to ensure their ability to fulfill obligations. Hyper-converged infrastructure overcomes infrastructural challenges by simplifying operations, enabling cloud-like environments, and facilitating data and application migration. The HCI market offers enterprise, small/medium enterprise, and vertical solutions, each catering to different needs and requirements. Analysing enterprise HCI solutions requires careful consideration of various criteria. Each approach has its own advantages and considerations related to flexibility, performance, and cost. The mentioned techniques can significantly reduce the data footprint, particularly in use cases like VDI, while maintaining performance and efficiency. Organizations take decisions that align with their specific storage, security, and efficiency requirements by considering the evaluation criteria for enterprise HCI solutions. By considering these factors, organizations can make informed decisions and choose a vendor with a strong foundation of reliability, stability, and long-term commitment, ensuring the durability of their HCI infrastructure and minimizing risks associated with vendor instability.

Read More

Verizon launches 5G fixed wireless in parts of 21 more cities

Article | April 20, 2021

Communications giant Verizon last week launched 5G for Business Internet in 20 new markets, targeting SMBs and enterprises alike. The fixed-wireless plans provide download speeds of 100Mbps ($69/month), 200Mbps ($99/month), and 400Mbps ($199/month) with no data limits. Upload speeds are slower. Verizon is also offering a 10-year price lock for new customers with no long-term contract required. “As 5G Business Internet scales into new cities, businesses of all sizes can gain access to the superfast speeds, low latency and next-gen applications enabled by 5G Ultra-Wideband, with no throttling or data limits,” Tami Erwin, CEO of Verizon Business, said in a statement. “We’ll continue to expand the 5G Business Internet footprint and bring the competitive pricing, capability, and flexibility of our full suite of products and services to more and more businesses all over the country.” The service was previously launched in parts of Chicago, Houston and Los Angeles. Verizon started rolling out 5G services last year using lower spectrum bands. According to a study by IHS Markit’s RootMetrics, Verizon offers speeds similar to those of T-Mobile but behind AT&T.

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Spotlight

Faststream Technologies

Faststream technologies, a vanguard of technology solutions specializing in Product & System Engineering, Digital Transformation, IoT, Big Data, Security and Application Development with the global footprint across North America, EMEA and APAC.

Related News

Hyper-Converged Infrastructure

Alluxio Unveils New Data Platform for AI: Accelerating AI Products’ Time-to-Value and Maximizing Infrastructure ROI

GlobeNewswire | October 19, 2023

Alluxio, the data platform company for all data-driven workloads, today introduced Alluxio Enterprise AI, a new high-performance data platform designed to meet the rising demands of Artificial Intelligence (AI) and machine learning (ML) workloads on an enterprise’s data infrastructure. Alluxio Enterprise AI brings together performance, data accessibility, scalability and cost-efficiency to enterprise AI and analytics infrastructure to fuel next-generation data-intensive applications like generative AI, computer vision, natural language processing, large language models and high-performance data analytics. To stay competitive and achieve stronger business outcomes, enterprises are in a race to modernize their data and AI infrastructure. On this journey, they find that legacy data infrastructure cannot keep pace with next-generation data-intensive AI workloads. Challenges around low performance, data accessibility, GPU scarcity, complex data engineering, and underutilized resources frequently hinder enterprises' ability to extract value from their AI initiatives. According to Gartner®, “the value of operationalized AI lies in the ability to rapidly develop, deploy, adapt and maintain AI across different environments in the enterprise. Given the engineering complexity and the demand for faster time to market, it is critical to develop less rigid AI engineering pipelines or build AI models that can self-adapt in production.” “By 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the operationalizing AI models by at least 25%.” Alluxio empowers the world’s leading organizations with the most modern Data & AI platforms, and today we take another significant leap forward, said Haoyuan Li, Founder and CEO, Alluxio. Alluxio Enterprise AI provides customers with streamlined solutions for AI and more by enabling enterprises to accelerate AI workloads and maximize value from their data. The leaders of tomorrow will know how to harness transformative AI and become increasingly data-driven with the newest technology for building and maintaining AI infrastructure for performance, seamless access and ease of management. With this announcement, Alluxio expands from a one-product portfolio to two product offerings - Alluxio Enterprise AI and Alluxio Enterprise Data - catering to the diverse needs of analytics and AI. Alluxio Enterprise AI is a new product that builds on the years of distributed systems experience accumulated from the previous Alluxio Enterprise Editions, combined with a new architecture that is optimized for AI/ML workloads. Alluxio Enterprise Data is the next-gen version of Alluxio Enterprise Edition, and will continue to be the ideal choice for businesses focused primarily on analytic workloads. Accelerating End-to-End Machine Learning Pipeline Alluxio Enterprise AI enables enterprise AI infrastructure to be performant, seamless, scalable and cost-effective on existing data lakes. Alluxio Enterprise AI helps data and AI leaders and practitioners achieve four key objectives in their AI initiatives: high-performance model training and deployment to yield quick business results; seamless data access for workloads across regions and clouds; infinite scale that has been battle-tested at internet giant’s scale; and maximized return on investments by working with existing tech stack instead of costly specialized storage. With Alluxio Enterprise AI, enterprises can expect up to 20x faster training speed compared to commodity storage, up to 10x accelerated model serving, over 90% GPU utilization, and up to 90% lower costs for AI infrastructure. Alluxio Enterprise AI has a distributed system architecture with decentralized metadata to eliminate bottlenecks when accessing massive numbers of small files, typical of AI workloads. This provides unlimited scalability beyond legacy architectures, regardless of file size or quantity. The distributed cache is tailored to AI workload I/O patterns, unlike traditional analytics. Finally, it supports analytics and full machine learning pipelines - from ingestion to ETL, pre-processing, training and serving. Alluxio Enterprise AI includes the following key features: Epic Performance for Model Training and Model Serving - Alluxio Enterprise AI offers significant performance improvements to model training and serving on an enterprise’s existing data lakes. The enhanced set of APIs for model training can deliver up to 20x performance over commodity storage. For model serving, Alluxio provides extreme concurrency and up to 10x acceleration for serving models from offline training clusters for online inference. Intelligent Distributed Caching Tailored to I/O Patterns of AI Workloads - Alluxio Enterprise AI’s distributed caching feature enables AI engines to read and write data through the high performance Alluxio cache instead of slow data lake storage. Alluxio’s intelligent caching strategies are tailored to the I/O patterns of AI engines – large file sequential access, large file random access, and massive small file access. This optimization delivers high throughput and low latency for data-hungry GPUs. Training clusters are continuously fed data from the high-performance distributed cache, achieving over 90% GPU utilization. Seamless Data Access for AI Workloads Across On-prem and Cloud Environments - Alluxio Enterprise AI provides a single pane of glass for enterprises to manage AI workloads across diverse infrastructure environments easily. Providing a source of truth of data for the machine learning pipeline, the product fundamentally removes the bottleneck of data lake silos in large enterprises. Sharing data between different business units and geographical locations becomes seamless with a standard data access layer via the Alluxio Enterprise AI platform. New Distributed System Architecture, Battle-tested At Scale - Alluxio Enterprise AI builds on a new innovative decentralized architecture, DORA (Decentralized Object Repository Architecture). This architecture sets the foundation to provide infinite scale for AI workloads. It allows an AI platform to handle up to 100 billion objects with commodity storage like Amazon S3. Leveraging Alluxio’s proven expertise in distributed systems, this new architecture has addressed the ever-increasing challenges of system scalability, metadata management, high availability, and performance. “Performance, cost optimization and GPU utilization are critical for optimizing next-generation workloads as organizations seek to scale AI throughout their businesses,” said Mike Leone, Analyst, Enterprise Strategy Group. “Alluxio has a compelling offering that can truly help data and AI teams achieve higher performance, seamless data access, and ease of management for model training and model serving.” “We've collaborated closely with Alluxio and consider their platform essential to our data infrastructure,” said Rob Collins, Analytics Cloud Engineering Director, Aunalytics. “Aunalytics is enthusiastic about Alluxio's new distributed system for Enterprise AI, recognizing its immense potential in the ever-evolving AI industry.” “Our in-house-trained large language model powers our Q&A application and recommendation engines, greatly enhancing user experience and engagement,” said Mengyu Hu, Software Engineer in the data platform team, Zhihu. “In our AI infrastructure, Alluxio is at the core and center. Using Alluxio as the data access layer, we’ve significantly enhanced model training performance by 3x and deployment by 10x with GPU utilization doubled. We are excited about Alluxio’s Enterprise AI and its new DORA architecture supporting access to massive small files. This offering gives us confidence in supporting AI applications facing the upcoming artificial intelligence wave.” Deploying Alluxio in Machine Learning Pipelines According to Gartner, data accessibility and data volume/complexity is one the top three barriers to the implementation of AI techniques within an organization. Alluxio Enterprise AI can be added to the existing AI infrastructure consisting of AI compute engines and data lake storage. Sitting in the middle of compute and storage, Alluxio can work across model training and model serving in the machine learning pipeline to achieve optimal speed and cost. For example, using PyTorch as the engine for training and serving, and Amazon S3 as the existing data lake: Model Training: When a user is training models, the PyTorch data loader loads datasets from a virtual local path /mnt/alluxio_fuse/training_datasets. Instead of loading directly from S3, the data loader will load from the Alluxio cache instead. During training, the cached datasets will be used in multiple epochs, so the entire training speed is no longer bottlenecked by retrieving from S3. In this way, Alluxio speeds up training by shortening data loading and eliminates GPU idle time, increasing GPU utilization. After the models are trained, PyTorch writes the model files to S3 through Alluxio. Model Serving: The latest trained models need to be deployed to the inference cluster. Multiple TorchServe instances read the model files concurrently from S3. Alluxio caches these latest model files from S3 and serves them to inference clusters with low latency. As a result, downstream AI applications can start inferencing using the most up-to-date models as soon as they are available. Platform Integration with Existing Systems To integrate Alluxio with the existing platform, users can deploy an Alluxio cluster between compute engines and storage systems. On the compute engine side, Alluxio integrates seamlessly with popular machine learning frameworks like PyTorch, Apache Spark, TensorFlow and Ray. Enterprises can integrate Alluxio with these compute frameworks via REST API, POSIX API or S3 API. On the storage side, Alluxio connects with all types of filesystems or object storage in any location, whether on-premises, in the cloud, or both. Supported storage systems include Amazon S3, Google GCS, Azure Blob Storage, MinIO, Ceph, HDFS, and more. Alluxio works on both on-premise and cloud, either bare-metal or containerized environments. Supported cloud platforms include AWS, GCP and Azure Cloud.

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Data Storage

AMI to Drive Intel DCM's Future and Broaden Manageability Solutions for Sustainable Data Centers

Cision Canada | October 17, 2023

AMI, the leader in foundational technology for sustainable, scalable, and secure global computing, is set to drive the future of Intel Data Center Manager (DCM) as it takes over the development, sales, and support of DCM under an agreement with Intel. This strategic transition empowers AMI to lead further the innovation and expansion of the Intel DCM product. With a unique position in the industry, AMI plays a pivotal role in enabling the cloud and data center ecosystem for all compute platforms. Intel DCM empowers data centers with the capability to manage and fine-tune server performance, energy consumption, and cooling efficiency. This operational optimization reduces the total cost of ownership, improves sustainability, and elevates performance benchmarks. We thank Intel for trusting AMI to lead Intel DCM into the future. This solution for efficient data center management will play a crucial role in enhancing the operational eco-efficiency of the data centers. It empowers data center managers with real-time insights into energy usage, thermal status, device health, and asset management, says Sanjoy Maity, CEO at AMI. AMI remains steadfast in aiding data center operators in achieving their manageability and sustainability objectives. About AMI AMI is Firmware Reimagined for modern computing. As a global leader in Dynamic Firmware for security, orchestration, and manageability solutions, AMI enables the world's compute platforms from on-premises to the cloud to the edge. AMI's industry-leading foundational technology and unwavering customer support have generated lasting partnerships and spurred innovation for some of the most prominent brands in the high-tech industry. For more information, visit ami.com.

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Data Storage

CoolIT Systems Partners with Switch Datacenters to Launch Advanced Energy-Efficient Data Centers

PRWeb | October 12, 2023

CoolIT Systems, a global leader in advanced cooling technology, and Switch Datacenters, a leading sustainable data center operator and developer, are thrilled to unveil a strategic partnership that will benefit an industry seeking to improve the sustainability of data centers. Following the recent release of the World Economic Forum's Top 10 Emerging Technologies featuring "Sustainable Computing" as the 9th-ranked emerging technology, the collaboration between Switch Datacenters and CoolIT facilitates data center space and the necessary technology to significantly curtail energy and water consumption inherent in modern data centers. With a history spanning more than a decade, Switch Datacenters has consistently demonstrated a commitment to environmental responsibility and sustainability. Their latest 45MW AMS6 data center near the Schiphol airport area features an HPC/AI-ready design that uses data center heat to warm adjacent greenhouses. Currently under development, their AMS5s is designed to make a significant contribution to the Amsterdam municipal heat grid with green, CO2-neutral heat. For both data centers, there's a marked preference for liquid cooling because it allows heat extraction at temperatures higher than traditional air cooling, offering enhanced economic value. CoolIT Systems is the industry-leading provider of efficient Direct Liquid Cooling (DLC) and Rear Door Heat Exchangers (RDHx) that enable heat reuse and help customers meet key Environmental, Social, and Governance (ESG) targets. CoolIT DLC technology is featured as a factory-installed, warranty-approved feature from most major servers OEMs. "CoolIT's DLC and RDHx technologies have been instrumental in various data center heat reuse projects for years, with customers reporting at minimum a savings of 10% on energy bills (OPEX), more than 50% on CAPEX spends, and examples of PUE lowered from 1.30 to 1.02," expressed Peggy Burroughs, Director of CoolIT Next. "Our collaborations with most major server OEMs have cultivated an expansive ecosystem for clients aspiring to achieve both business and ESG goals." CoolIT is the right company to help make our vision a reality at an industrial scale. Both CoolIT and Switch Datacenters have shared the same passion for sustainable innovation for years and truly want to elevate the industry's adoption of liquid cooling. We believe liquid cooling will be the game-changer in the next wave of sustainable data center designs, and CoolIT is one of the very few companies that can lead this upcoming demand, thanks to their long history of innovation, reliability, breadth of portfolio, and capabilities to scale with their numerous IT partners worldwide, says Gregor Snip, CEO of Switch Datacenters. Data centers are projected to account for 8% of the global electricity consumption by 20301. Technologies such as Direct Liquid Cooling can significantly reduce data center energy consumption by 25-40% and deliver water savings of 70-97%, depending on local climate and specific implementations2. Switch Datacenters is leading the charge in embracing sustainable alternatives for heating by reusing data center-generated heat. With their latest project, Switch Datacenters AMS6, they will revolutionize the way nearby greenhouses are heated by providing high-temperature heat from their data center. This innovative solution will replace traditional fossil fuel-based heating and contribute to a greener future. By harnessing the power of IT servers to generate green heat for large-scale crop cultivation, Switch Datacenters is driving the transition away from fossil fuels. They strongly advocate for the integration of heat-recapture-enabled data centers in areas with high demand for heat, making it a standard design principle. With the world calling for sustainable IT and data centers, the time is ripe for this much-needed change. With the combined expertise of CoolIT and Switch Datacenters, customers can now harness technologically advanced solutions that not only result in considerable energy and water savings but also contribute significantly to the global drive for reduced environmental impact, aligning with the United Nations Sustainable Development Goals of Affordable and Clean Energy (SDG 7), Industry, Innovation, and Infrastructure (SDG 9), and Climate Action (SDG 13). About CoolIT Systems CoolIT Systems is renowned for its scalable liquid cooling solutions tailored for the world's most challenging computing contexts. In both enterprise data centers and high-performance computing domains, CoolIT collaborates with global OEM server design leaders, formulating efficient and trustworthy liquid cooling solutions. In the desktop enthusiast arena, CoolIT delivers unmatched performance for a diverse range of gaming setups. Their modular Direct Liquid Cooling technology, Rack DLC™, empowers dramatic spikes in rack densities, component efficacy, and power savings. Jointly, CoolIT and its allies are pioneering the large-scale adoption of sophisticated cooling techniques. About Switch Datacenters Switch Datacenters is a Dutch privately-owned data center operator and developer founded in 2010 by Gregor Snip and his brother. Initially established as a private data center for their successful hosting company, the Amsterdam-based company later expanded into a fully-fledged commercial data center operator. It added several highly efficient and environmentally-friendly data center sites to its portfolio, with a current focus on constructing and managing wholesale data centers for large global customers while also providing tailor-made data center services. Switch Datacenters is an ambitious, 100% Dutch player in the Amsterdam data center sector, experiencing rapid growth by continually partnering with leading and globally recognized industry players and customers. The company maintains a steadfast commitment to innovative and sustainable site development. Currently, Switch Datacenters has over 200MW of new sustainable data center capacity in development. This year, it will launch its flagship sustainable data center, AMS4, with major customers having already pre-leased the 15-18MW facility.

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Hyper-Converged Infrastructure

Alluxio Unveils New Data Platform for AI: Accelerating AI Products’ Time-to-Value and Maximizing Infrastructure ROI

GlobeNewswire | October 19, 2023

Alluxio, the data platform company for all data-driven workloads, today introduced Alluxio Enterprise AI, a new high-performance data platform designed to meet the rising demands of Artificial Intelligence (AI) and machine learning (ML) workloads on an enterprise’s data infrastructure. Alluxio Enterprise AI brings together performance, data accessibility, scalability and cost-efficiency to enterprise AI and analytics infrastructure to fuel next-generation data-intensive applications like generative AI, computer vision, natural language processing, large language models and high-performance data analytics. To stay competitive and achieve stronger business outcomes, enterprises are in a race to modernize their data and AI infrastructure. On this journey, they find that legacy data infrastructure cannot keep pace with next-generation data-intensive AI workloads. Challenges around low performance, data accessibility, GPU scarcity, complex data engineering, and underutilized resources frequently hinder enterprises' ability to extract value from their AI initiatives. According to Gartner®, “the value of operationalized AI lies in the ability to rapidly develop, deploy, adapt and maintain AI across different environments in the enterprise. Given the engineering complexity and the demand for faster time to market, it is critical to develop less rigid AI engineering pipelines or build AI models that can self-adapt in production.” “By 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the operationalizing AI models by at least 25%.” Alluxio empowers the world’s leading organizations with the most modern Data & AI platforms, and today we take another significant leap forward, said Haoyuan Li, Founder and CEO, Alluxio. Alluxio Enterprise AI provides customers with streamlined solutions for AI and more by enabling enterprises to accelerate AI workloads and maximize value from their data. The leaders of tomorrow will know how to harness transformative AI and become increasingly data-driven with the newest technology for building and maintaining AI infrastructure for performance, seamless access and ease of management. With this announcement, Alluxio expands from a one-product portfolio to two product offerings - Alluxio Enterprise AI and Alluxio Enterprise Data - catering to the diverse needs of analytics and AI. Alluxio Enterprise AI is a new product that builds on the years of distributed systems experience accumulated from the previous Alluxio Enterprise Editions, combined with a new architecture that is optimized for AI/ML workloads. Alluxio Enterprise Data is the next-gen version of Alluxio Enterprise Edition, and will continue to be the ideal choice for businesses focused primarily on analytic workloads. Accelerating End-to-End Machine Learning Pipeline Alluxio Enterprise AI enables enterprise AI infrastructure to be performant, seamless, scalable and cost-effective on existing data lakes. Alluxio Enterprise AI helps data and AI leaders and practitioners achieve four key objectives in their AI initiatives: high-performance model training and deployment to yield quick business results; seamless data access for workloads across regions and clouds; infinite scale that has been battle-tested at internet giant’s scale; and maximized return on investments by working with existing tech stack instead of costly specialized storage. With Alluxio Enterprise AI, enterprises can expect up to 20x faster training speed compared to commodity storage, up to 10x accelerated model serving, over 90% GPU utilization, and up to 90% lower costs for AI infrastructure. Alluxio Enterprise AI has a distributed system architecture with decentralized metadata to eliminate bottlenecks when accessing massive numbers of small files, typical of AI workloads. This provides unlimited scalability beyond legacy architectures, regardless of file size or quantity. The distributed cache is tailored to AI workload I/O patterns, unlike traditional analytics. Finally, it supports analytics and full machine learning pipelines - from ingestion to ETL, pre-processing, training and serving. Alluxio Enterprise AI includes the following key features: Epic Performance for Model Training and Model Serving - Alluxio Enterprise AI offers significant performance improvements to model training and serving on an enterprise’s existing data lakes. The enhanced set of APIs for model training can deliver up to 20x performance over commodity storage. For model serving, Alluxio provides extreme concurrency and up to 10x acceleration for serving models from offline training clusters for online inference. Intelligent Distributed Caching Tailored to I/O Patterns of AI Workloads - Alluxio Enterprise AI’s distributed caching feature enables AI engines to read and write data through the high performance Alluxio cache instead of slow data lake storage. Alluxio’s intelligent caching strategies are tailored to the I/O patterns of AI engines – large file sequential access, large file random access, and massive small file access. This optimization delivers high throughput and low latency for data-hungry GPUs. Training clusters are continuously fed data from the high-performance distributed cache, achieving over 90% GPU utilization. Seamless Data Access for AI Workloads Across On-prem and Cloud Environments - Alluxio Enterprise AI provides a single pane of glass for enterprises to manage AI workloads across diverse infrastructure environments easily. Providing a source of truth of data for the machine learning pipeline, the product fundamentally removes the bottleneck of data lake silos in large enterprises. Sharing data between different business units and geographical locations becomes seamless with a standard data access layer via the Alluxio Enterprise AI platform. New Distributed System Architecture, Battle-tested At Scale - Alluxio Enterprise AI builds on a new innovative decentralized architecture, DORA (Decentralized Object Repository Architecture). This architecture sets the foundation to provide infinite scale for AI workloads. It allows an AI platform to handle up to 100 billion objects with commodity storage like Amazon S3. Leveraging Alluxio’s proven expertise in distributed systems, this new architecture has addressed the ever-increasing challenges of system scalability, metadata management, high availability, and performance. “Performance, cost optimization and GPU utilization are critical for optimizing next-generation workloads as organizations seek to scale AI throughout their businesses,” said Mike Leone, Analyst, Enterprise Strategy Group. “Alluxio has a compelling offering that can truly help data and AI teams achieve higher performance, seamless data access, and ease of management for model training and model serving.” “We've collaborated closely with Alluxio and consider their platform essential to our data infrastructure,” said Rob Collins, Analytics Cloud Engineering Director, Aunalytics. “Aunalytics is enthusiastic about Alluxio's new distributed system for Enterprise AI, recognizing its immense potential in the ever-evolving AI industry.” “Our in-house-trained large language model powers our Q&A application and recommendation engines, greatly enhancing user experience and engagement,” said Mengyu Hu, Software Engineer in the data platform team, Zhihu. “In our AI infrastructure, Alluxio is at the core and center. Using Alluxio as the data access layer, we’ve significantly enhanced model training performance by 3x and deployment by 10x with GPU utilization doubled. We are excited about Alluxio’s Enterprise AI and its new DORA architecture supporting access to massive small files. This offering gives us confidence in supporting AI applications facing the upcoming artificial intelligence wave.” Deploying Alluxio in Machine Learning Pipelines According to Gartner, data accessibility and data volume/complexity is one the top three barriers to the implementation of AI techniques within an organization. Alluxio Enterprise AI can be added to the existing AI infrastructure consisting of AI compute engines and data lake storage. Sitting in the middle of compute and storage, Alluxio can work across model training and model serving in the machine learning pipeline to achieve optimal speed and cost. For example, using PyTorch as the engine for training and serving, and Amazon S3 as the existing data lake: Model Training: When a user is training models, the PyTorch data loader loads datasets from a virtual local path /mnt/alluxio_fuse/training_datasets. Instead of loading directly from S3, the data loader will load from the Alluxio cache instead. During training, the cached datasets will be used in multiple epochs, so the entire training speed is no longer bottlenecked by retrieving from S3. In this way, Alluxio speeds up training by shortening data loading and eliminates GPU idle time, increasing GPU utilization. After the models are trained, PyTorch writes the model files to S3 through Alluxio. Model Serving: The latest trained models need to be deployed to the inference cluster. Multiple TorchServe instances read the model files concurrently from S3. Alluxio caches these latest model files from S3 and serves them to inference clusters with low latency. As a result, downstream AI applications can start inferencing using the most up-to-date models as soon as they are available. Platform Integration with Existing Systems To integrate Alluxio with the existing platform, users can deploy an Alluxio cluster between compute engines and storage systems. On the compute engine side, Alluxio integrates seamlessly with popular machine learning frameworks like PyTorch, Apache Spark, TensorFlow and Ray. Enterprises can integrate Alluxio with these compute frameworks via REST API, POSIX API or S3 API. On the storage side, Alluxio connects with all types of filesystems or object storage in any location, whether on-premises, in the cloud, or both. Supported storage systems include Amazon S3, Google GCS, Azure Blob Storage, MinIO, Ceph, HDFS, and more. Alluxio works on both on-premise and cloud, either bare-metal or containerized environments. Supported cloud platforms include AWS, GCP and Azure Cloud.

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Data Storage

AMI to Drive Intel DCM's Future and Broaden Manageability Solutions for Sustainable Data Centers

Cision Canada | October 17, 2023

AMI, the leader in foundational technology for sustainable, scalable, and secure global computing, is set to drive the future of Intel Data Center Manager (DCM) as it takes over the development, sales, and support of DCM under an agreement with Intel. This strategic transition empowers AMI to lead further the innovation and expansion of the Intel DCM product. With a unique position in the industry, AMI plays a pivotal role in enabling the cloud and data center ecosystem for all compute platforms. Intel DCM empowers data centers with the capability to manage and fine-tune server performance, energy consumption, and cooling efficiency. This operational optimization reduces the total cost of ownership, improves sustainability, and elevates performance benchmarks. We thank Intel for trusting AMI to lead Intel DCM into the future. This solution for efficient data center management will play a crucial role in enhancing the operational eco-efficiency of the data centers. It empowers data center managers with real-time insights into energy usage, thermal status, device health, and asset management, says Sanjoy Maity, CEO at AMI. AMI remains steadfast in aiding data center operators in achieving their manageability and sustainability objectives. About AMI AMI is Firmware Reimagined for modern computing. As a global leader in Dynamic Firmware for security, orchestration, and manageability solutions, AMI enables the world's compute platforms from on-premises to the cloud to the edge. AMI's industry-leading foundational technology and unwavering customer support have generated lasting partnerships and spurred innovation for some of the most prominent brands in the high-tech industry. For more information, visit ami.com.

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Data Storage

CoolIT Systems Partners with Switch Datacenters to Launch Advanced Energy-Efficient Data Centers

PRWeb | October 12, 2023

CoolIT Systems, a global leader in advanced cooling technology, and Switch Datacenters, a leading sustainable data center operator and developer, are thrilled to unveil a strategic partnership that will benefit an industry seeking to improve the sustainability of data centers. Following the recent release of the World Economic Forum's Top 10 Emerging Technologies featuring "Sustainable Computing" as the 9th-ranked emerging technology, the collaboration between Switch Datacenters and CoolIT facilitates data center space and the necessary technology to significantly curtail energy and water consumption inherent in modern data centers. With a history spanning more than a decade, Switch Datacenters has consistently demonstrated a commitment to environmental responsibility and sustainability. Their latest 45MW AMS6 data center near the Schiphol airport area features an HPC/AI-ready design that uses data center heat to warm adjacent greenhouses. Currently under development, their AMS5s is designed to make a significant contribution to the Amsterdam municipal heat grid with green, CO2-neutral heat. For both data centers, there's a marked preference for liquid cooling because it allows heat extraction at temperatures higher than traditional air cooling, offering enhanced economic value. CoolIT Systems is the industry-leading provider of efficient Direct Liquid Cooling (DLC) and Rear Door Heat Exchangers (RDHx) that enable heat reuse and help customers meet key Environmental, Social, and Governance (ESG) targets. CoolIT DLC technology is featured as a factory-installed, warranty-approved feature from most major servers OEMs. "CoolIT's DLC and RDHx technologies have been instrumental in various data center heat reuse projects for years, with customers reporting at minimum a savings of 10% on energy bills (OPEX), more than 50% on CAPEX spends, and examples of PUE lowered from 1.30 to 1.02," expressed Peggy Burroughs, Director of CoolIT Next. "Our collaborations with most major server OEMs have cultivated an expansive ecosystem for clients aspiring to achieve both business and ESG goals." CoolIT is the right company to help make our vision a reality at an industrial scale. Both CoolIT and Switch Datacenters have shared the same passion for sustainable innovation for years and truly want to elevate the industry's adoption of liquid cooling. We believe liquid cooling will be the game-changer in the next wave of sustainable data center designs, and CoolIT is one of the very few companies that can lead this upcoming demand, thanks to their long history of innovation, reliability, breadth of portfolio, and capabilities to scale with their numerous IT partners worldwide, says Gregor Snip, CEO of Switch Datacenters. Data centers are projected to account for 8% of the global electricity consumption by 20301. Technologies such as Direct Liquid Cooling can significantly reduce data center energy consumption by 25-40% and deliver water savings of 70-97%, depending on local climate and specific implementations2. Switch Datacenters is leading the charge in embracing sustainable alternatives for heating by reusing data center-generated heat. With their latest project, Switch Datacenters AMS6, they will revolutionize the way nearby greenhouses are heated by providing high-temperature heat from their data center. This innovative solution will replace traditional fossil fuel-based heating and contribute to a greener future. By harnessing the power of IT servers to generate green heat for large-scale crop cultivation, Switch Datacenters is driving the transition away from fossil fuels. They strongly advocate for the integration of heat-recapture-enabled data centers in areas with high demand for heat, making it a standard design principle. With the world calling for sustainable IT and data centers, the time is ripe for this much-needed change. With the combined expertise of CoolIT and Switch Datacenters, customers can now harness technologically advanced solutions that not only result in considerable energy and water savings but also contribute significantly to the global drive for reduced environmental impact, aligning with the United Nations Sustainable Development Goals of Affordable and Clean Energy (SDG 7), Industry, Innovation, and Infrastructure (SDG 9), and Climate Action (SDG 13). About CoolIT Systems CoolIT Systems is renowned for its scalable liquid cooling solutions tailored for the world's most challenging computing contexts. In both enterprise data centers and high-performance computing domains, CoolIT collaborates with global OEM server design leaders, formulating efficient and trustworthy liquid cooling solutions. In the desktop enthusiast arena, CoolIT delivers unmatched performance for a diverse range of gaming setups. Their modular Direct Liquid Cooling technology, Rack DLC™, empowers dramatic spikes in rack densities, component efficacy, and power savings. Jointly, CoolIT and its allies are pioneering the large-scale adoption of sophisticated cooling techniques. About Switch Datacenters Switch Datacenters is a Dutch privately-owned data center operator and developer founded in 2010 by Gregor Snip and his brother. Initially established as a private data center for their successful hosting company, the Amsterdam-based company later expanded into a fully-fledged commercial data center operator. It added several highly efficient and environmentally-friendly data center sites to its portfolio, with a current focus on constructing and managing wholesale data centers for large global customers while also providing tailor-made data center services. Switch Datacenters is an ambitious, 100% Dutch player in the Amsterdam data center sector, experiencing rapid growth by continually partnering with leading and globally recognized industry players and customers. The company maintains a steadfast commitment to innovative and sustainable site development. Currently, Switch Datacenters has over 200MW of new sustainable data center capacity in development. This year, it will launch its flagship sustainable data center, AMS4, with major customers having already pre-leased the 15-18MW facility.

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