Comparing: HCI vs. Traditional IT vs. dHCI vs. Composable Infrastructure

  • Compare outcomes of hyper-converged, traditional/converged, disaggregated HCI and composable infrastructures, plus hybrid cloud .

  • Some hyper-converged vendors have figured out there is a need for a more configurable resource buffet that retains the management benefits of HCI.

  • Rather than monolithic all-in-one nodes, dHCI products ship separate compute and storage nodes so you can decide the right mix of each without scaling compute and storage linearly in lockstep.


For over a decade, we've seen the meaning of hyper-converged infrastructure evolve. What started as almost a throwaway term has slowly morphed into an actual thriving industry, complete with Magic Quadrant and vendors fighting over the true meaning of HCI. Beyond duking it out on Twitter, hyper-converged infrastructure (HCI) vendors have attempted to move mountains in an effort to shoehorn their infrastructure paradigm into every aspect of IT life -- from the data center to the edge to the public cloud.


For the hyper-converged industry, the mission is clear: supplant every legacy platform with a neatly integrated hyper-converged stack. It's HCI vs. traditional infrastructure and the world. To be fair, this is a good goal! Anyone who knows me at all understands I'm a fan of hyper-convergence in general. I love what it can bring to organizations and enjoyed watching previously startup HCI vendors turn into hyper-converged powerhouses that help customers simplify IT operations .



Read more: CISA RELEASES FIRST OF ITS SERIES OF SIX CYBERSECURITY ESSENTIALS TOOLKITS

Unlike hyper-converged, which tightly integrates data center resources into individual nodes, converged infrastructure's data center components -- compute, networking, servers, storage -- remain separate in the traditional infrastructure mode.

~ HCL


Nutanix has grown from a pure HCI hardware play to a software-centric platform company for which HCI is the core. Scale Computing wrangled edge computing environments into submission, while NetApp, Hewlett Packard Enterprise (HPE), Pivot3, Datrium and DataCore all created HCI products with their own unique flavor. One-size IT infrastructure doesn't fit all. As much as I like hyper-converged, it's clear the one-size-fits-all nature of the technology isn't the right choice for every workload.


For general-purpose needs, it's a fantastic replacement for traditional infrastructure. The very nature of HCI -- linear scalability -- can also be its downfall. Should you start to drift away from general-purpose workloads, a more traditional infrastructure approach may be a better fit than hyper-converged. HCI isn't always appropriate for workloads with intense demands on a single part of the resource stack; for example, big data workloads in which storage capacity can't increase linearly with other resources.


Hyper-convergence does this by making it easier to run the same software in the cloud that runs on on-premises hardware. This makes shifting workloads where they're needed eminently simple.


Hyper-convergence may not be the answer for CPU-intensive workloads either -- especially, if you need to pay for hypervisor licenses for every node -- and it may not work well when virtualizing resources doesn't make sense. Of course, as the hyper-convergence market continues to splinter, hyper-converged products that address these disparate needs may actually appear. Hyper-converged vendors, for example, now view disaggregated hyper-converged infrastructure (dHCI), which decouples storage and compute, as a possible answer. Still, the fact remains many organizations will prefer more traditional IT approaches that leave in place the fine-tuned knobs administrators can use for more granular control of resources.


One possible answer in the software-defined mode is composable infrastructure, which merges aspects of HCI and converged infrastructure with programmatic control of resources to make it easier to stand up and down virtual servers for specific workloads. Let's explore reasons you may or may not choose HCI vs. traditional infrastructure vs. dHCI or composable architecture. Also, what about taking a hybrid approach that brings cloud in the picture or uses a mix of infrastructures? For many, the flexibility provided by a more traditional infrastructure approach just can't be beat. You get to choose each vendor you want to work with. You get to custom-build an infrastructure that meets the unique needs of your applications. And you get to make granular choices around the configuration of each discrete resource.


Read more: GOOGLE TOP CHOICE FOR CYBERCRIMINALS FOR BRAND-IMPERSONATION SPEAR-PHISHING CAMPAIGNS

Spotlight

Spotlight

Related News

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.

Read More

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.

Read More

Data Storage

Astera Labs First to Break Through the Memory Wall with Industry’s Highest Performance CXL Memory Controllers

Business Wire | September 21, 2023

Astera Labs, the global leader in semiconductor-based connectivity solutions for AI infrastructure, today announced that its Leo Memory Connectivity Platform enables data center servers with unprecedented performance for memory intensive workloads. Leo is the industry’s first Compute Express Link™ (CXL™) memory controller that increases total server memory bandwidth by 50% while also decreasing latency by 25% when integrated with the forthcoming 5th Gen Intel® Xeon® Scalable Processor. Through new hardware-based interleaving of CXL-attached and CPU native memory, Astera Labs and Intel eliminate any application-level software changes to augment server memory resources via CXL. Existing applications can effortlessly “plug-and-play” to take advantage of the highest possible memory bandwidth and capacity in the system. “The growth of computing cores and performance has historically outpaced memory throughput advancements, resulting in degraded server performance efficiency over time,” said Sanjay Gajendra, COO of Astera Labs. “This performance scaling challenge has led to the infamous ‘memory wall,’ and thanks to our collaboration with Intel, our Leo Memory Connectivity Platform breaks through this barrier by delivering on the promise of PCIe 5.0 and CXL memory.” Data center infrastructure scaling limitations due to the memory wall are none more evident than in AI servers where memory bandwidth and capacity bottlenecks result in inefficient processor utilization. The CXL innovations delivered by Astera Labs and Intel directly address these bottlenecks and lay the foundation for cloud, hybrid-cloud and enterprise data centers to maximize accelerated computing performance. Extending leadership of PCIe® 5.0 and CXL 2.0 solutions Astera Labs has a history of delivering industry-first solutions that are critical to advancing the PCIe and CXL ecosystems. In addition to memory performance advancements with Leo, Astera Labs is also driving interoperability leadership with its Aries PCIe 5.0 / CXL 2.0 Smart Retimers on state-of-the-art Intel server platforms. As the most widely deployed and proven PCIe/CXL retimer family in the industry, Aries features a low-latency CXL mode that complements Leo to form the most robust CXL memory connectivity solution. “We applaud Astera Labs for their contributions to the CXL ecosystem and are delighted to extend our ongoing collaboration. We believe Memory Connectivity Platforms containing innovations from companies like Astera Labs will help deliver enhanced performance on next generation Intel Xeon processors, and accelerate a myriad of memory intensive workloads,” said Zane Ball, Corporate Vice President and General Manager, Data Center Platform Engineering and Architecture Group, Intel. Visit Astera Labs at Intel Innovation! Astera Labs will showcase Leo and Aries together with Intel’s latest Xeon® Scalable processors at Booth #210, September 19-20 at the San Jose Convention Center. Talk to Astera Labs’ experts to learn more about industry benchmarks and how to optimize PCIe/CXL memory solutions in data center architectures to deliver optimized performance for applications ranging from AI, real time analytics, genomics and modeling. About Astera Labs Astera Labs, Inc. is a global leader in semiconductor-based connectivity solutions purpose-built to unleash the full potential of intelligent data infrastructure at cloud-scale. Its class-defining, first-to-market products based on PCIe, CXL, and Ethernet technologies deliver critical connectivity in accelerated computing platforms optimized for AI applications.

Read More