Post Syndicated from Will Taillac original https://www.servethehome.com/lexar-play-2280-4tb-m-2-nvme-ssd-review/
In our Lexar Play 2280 4TB M.2 NVMe SSD review, we see how this PCIe Gen4 drive pairs a Maxio controller and YMTC NAND to deliver performance
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Post Syndicated from Eric Smith original https://www.servethehome.com/blackmagic-cloud-dock-2-a-dual-10gbe-nas-that-is-too-easy/
In our Blackmagic Cloud Dock 2 Review we see how this two SSD and dual 10GbE NAS is designed well, but it might be too simplified for many
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Post Syndicated from Eric Smith original https://www.servethehome.com/samsung-pro-plus-1tb-microsdxc-card-review/
We take a quick look at the Samsung Pro Plus 1TB now with claimed 180MB/s speeds and see how it performs compared to its competition
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Post Syndicated from Eric Smith original https://www.servethehome.com/the-pny-1-5tb-pro-elite-prime-microsdxc-card-review-wins-in-value/
In our PNY 1.5TB PRO Elite Prime microSDXC card mini-review, we see why this tiny and high-capacity card is a better value than other options
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Post Syndicated from Cliff Robinson original https://www.servethehome.com/broadcom-emulex-secure-fibre-channel-host-bus-adapters-encrypt-data-end-to-end/
The new Broadcom Emulex Secure Fibre Channel Host Bus Adapters encrypt data end-to-end for zero trust storage networking
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Post Syndicated from Will Taillac original https://www.servethehome.com/wd-blue-sn5000-1tb-nvme-ssd-review/
We test the WD Blue SN5000, a 1TB NVMe SSD targeted at the mainstream PCIe Gen4 market with a low cost. The question is: how does it perform?
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Post Syndicated from Eric Smith original https://www.servethehome.com/dapustor-haishen5-ssd-h5100-30-72tb-pcie-gen5-nvme-ssd-review/
In our DapuStor Haishen5 SSD H5100 30.72TB review, we see how this high capacity PCIe Gen5 NVMe SSD performs
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Post Syndicated from Will Taillac original https://www.servethehome.com/kingston-fury-renegade-2tb-nvme-ssd-review/
In our Kingston Fury Renegade review, we see how this 2TB PCIe Gen4 NVMe SSD performs compared to other drives we have tested
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Post Syndicated from Eric Smith original https://www.servethehome.com/tiny-sandisk-extreme-2tb-microsdxc-is-fast-and-small/
This extremely tiny SanDisk Extreme 2TB microSDXC card is fast, but it might be too small for its own good
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Post Syndicated from Cliff Robinson original https://www.servethehome.com/lenovo-buying-infinidat-for-enterprise-storage/
Lenovo is buying Infinidat to bolster its offerings in the enterprise storage space and increase coverage in its infrastructure solutions
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Post Syndicated from Will Taillac original https://www.servethehome.com/wd-black-sn7100-2tb-nvme-ssd-review/
In our WD Black SN7100 2TB review, we see if this PCIe Gen4 NVMe SSD deserves to be called a “Black” series drive
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Post Syndicated from E Lopez original https://www.servethehome.com/what-all-of-the-markings-on-sd-microsd-and-microsdxc-cards-mean/
A quick guide to what all of the markings on SD, microSD, and microSDXC cards mean including speeds, capacities, and more
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Post Syndicated from Eric Smith original https://www.servethehome.com/the-sandisk-1-5tb-ultra-microsdxc-card-is-too-small/
These days 1.5TB of storage fits in a tiny microSDXC card which is almost crazy to think about given the capacity and size
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Post Syndicated from Eric Smith original https://www.servethehome.com/blackmagic-cloud-pod-10gbe-usb-ssd-sharing-device/
The Blackmagic Cloud Pod might be the simplest 10GbE NAS out there providing an easy way to make USB SSDs accessible as network storage
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Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/amazon-fsx-for-lustre-unlocks-full-network-bandwidth-and-gpu-performance/
Today, we are announcing support for Elastic Fabric Adapter (EFA) and NVIDIA GPUDirect Storage (GDS) on Amazon FSx for Lustre. EFA is a network interface for Amazon EC2 instances that makes it possible to run applications requiring high levels of inter-node communications at scale. GDS is a technology that creates a direct data path between local or remote storage and GPU memory. With these enhancements, Amazon FSx for Lustre with EFA/GDS support provides up to 12 times higher (up to 1200 Gbps) per-client throughput compared to the previous FSx for Lustre version.
You can use FSx for Lustre to build and run the most performance demanding applications, such as deep learning training, drug discovery, financial modeling, and autonomous vehicle development. As datasets grow and new technologies emerge, you can adopt increasingly powerful GPU and HPC instances such as Amazon EC2 P5, Trn1, and Hpc7a. Until now, when accessing FSx for Lustre file systems, the use of traditional TCP networking limited throughput to 100 Gbps for individual client instances. This adoption is driving the need for FSx for Lustre file systems to provide the performance necessary to optimally utilize the increasing network bandwidth of these cutting-edge EC2 instances when accessing large datasets.
With EFA and GDS support in FSx for Lustre, you can now achieve up to 1,200 Gbps throughput per client instance (twelve times more throughput than previously) when using P5 GPU instances and NVIDIA CUDA in your applications.
With this new capability, you can fully utilize the network bandwidth of the most powerful compute instances and accelerate your machine learning (ML) and HPC workloads. EFA enhances performance by bypassing the operating system and using the AWS Scalable Reliable Datagram (SRD) protocol to optimize data transfer. GDS further improves performance by enabling direct data transfer between the file system and GPU memory, bypassing the CPU and eliminating redundant memory copies.
Let’s see how this works in practice.
Creating an Amazon FSx for Lustre file system with EFA enabled
To get started, in the Amazon FSx console, I choose Create file system and then Amazon FSx for Lustre.
I enter a name for the file system. In the Deployment and storage type section, I select Persistent, SSD and the new with EFA enabled option. I select 1000 MB/s/TiB in the Throughput per unit of storage section. With these settings, I enter 4.8 TiB for Storage capacity, which is the minimum supported with these settings.
For networking, I use the default virtual private cloud (VPC) and an EFA-enabled security group. I leave all other options to their default values.
I review all the options and proceed to create the file system. After a few minutes, the file system is ready to be used.
Mounting an Amazon FSx for Lustre file system with EFA enabled from an Amazon EC2 instance
In the Amazon EC2 console, I choose Launch instance, enter a name for the instance, and select the Ubuntu Amazon Machine Image (AMI). For Instance type, I select trn1.32xlarge.
In Network settings, I edit the default settings and select the same subnet used by the FSx Lustre file system. In Firewall (security groups), I select three existing security groups: the EFA-enabled security group used by the FSx for Lustre file system, the default security group, and a security group that provides Secure Shell (SSH) access.
In Advanced network configuration, I select ENA and EFA as Interface type. Without this setting, the instance would use traditional TCP networking and the connection with the FSx for Lustre file system would still be limited to 100 Gbps in throughput.
To have more throughput, I can add more EFA network interfaces, depending on the instance type.
I launch the instance and, when the instance is ready, I connect using EC2 Instance Connect and follow the instructions for installing the Lustre client in the FSx for Lustre User Guide and configuring EFA clients.
Then, I follow the instructions for mounting an FSx for Lustre file system from an EC2 instance.
I create a folder to use as mount point:
I select the file system in the FSx console and lookup the DNS name and Mount name. Using these values, I mount the file system:
EFA is automatically used when you access an EFA-enabled file system from client instances that support EFA and are using Lustre version 2.15 or higher.
Things to know
EFA and GDS support is available today with no additional cost on new Amazon FSx for Lustre file systems in all AWS Regions where persistent 2 is offered. FSx for Lustre automatically uses EFA when customers access an EFA-enabled file system from client instances that support EFA, without requiring any additional configuration. For a list of EC2 client instances that support EFA, see supported instance types in the Amazon EC2 User Guide. This network specifications table describes network bandwidths and EFA support for instance types in the accelerated computing category.
To use EFA-enabled instances with FSx for Lustre file systems, you must use Lustre 2.15 clients on Ubuntu 22.04 with kernel 6.8 or higher.
Note that your client instances and your file systems must be located in the same subnet within your Amazon Virtual Private Cloud (Amazon VPC) connection.
GDS is automatically supported on EFA-enabled file systems. To use GDS with your FSx for Lustre file systems, you need the NVIDIA Compute Unified Device Architecture (CUDA) package, the open source NVIDIA driver, and the NVIDIA GPUDirect Storage Driver installed on your client instance. These packages come preinstalled on the AWS Deep Learning AMI. You can then use your CUDA-enabled application to use GPUDirect storage for data transfer between your file system and GPUs.
When planning your deployment, note that EFA-enabled file systems have larger minimum storage capacity increments than file systems that are not EFA-enabled. For instance, if you choose the 1,000 MB/s/TiB throughput tier, the minimum storage capacity for EFA-enabled file systems starts at 4.8 TiB as compared to 1.2TB for FSx for Lustre file systems not enabling EFA. If you’re looking to migrate your existing workloads, you can use AWS DataSync to move your data from an existing file system to a new one that supports EFA and GDS.
For maximum flexibility, FSx for Lustre maintains compatibility with both EFA and non-EFA workloads. When accessing an EFA-enabled file system, traffic from non-EFA client instances automatically flows over traditional TCP/IP networking using Elastic Network Adapter (ENA), allowing seamless access for all workloads without any additional configuration.
To learn more about EFA and GDS support on FSx for Lustre, including detailed setup instructions and best practices, visit the Amazon FSx for Lustre documentation. Get started today and experience the fastest storage performance available for your GPU instances in the cloud.
— Danilo
Update 11/27: post updated to reflect 12x throughput
Post Syndicated from Patrick Kennedy original https://www.servethehome.com/solidigm-d5-p5336-122-88tb-nvme-ssd-launched-shipping-in-q1-2025/
The enormous new Solidigm D5-P5336 122.88TB NVMe SSD allows for 3PB of storage in standard 2U servers from almost any vendor
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Post Syndicated from Eric Smith original https://www.servethehome.com/micron-6550-ion-61-44tb-pcie-gen5-nvme-ssd-launched/
The Micron 6550 ION is a new 61.44TB NVMe SSD that brings high capcity to PCIe Gen5 and dense E3.S form factors
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Post Syndicated from Luca Mezzalira original https://aws.amazon.com/blogs/architecture/lets-architect-modern-data-architectures-2/
Data is the fuel for AI; modern data is even more important for generative AI and advanced data analytics, producing more accurate, relevant, and impactful results. Modern data comes in various forms: real-time, unstructured, or user-generated. Each form requires a different solution. AWS’s data journey began with Amazon Simple Storage Service (Amazon S3) in 2006, marking the start of cloud-based data storage at scale. Since then, AWS has expanded its data offerings to cover the entire data lifecycle, offering a comprehensive ecosystem of services designed to harness the full potential of modern data, from ingestion and storage to processing and analysis, supporting the entire lifecycle of AI-driven innovation.
In this blog post, we will cover some AWS use cases for modern data architectures, showing how AWS enables organizations to leverage the power of data and generative AI technologies.
This blog focuses on selecting the right database for generative AI applications and provide knowledge that can enhance your understanding, guide your decision making, and ultimately lead to more successful AI projects. Selecting the right database for generative AI applications is not just about storage; it significantly impacts performance, scalability, ease of integration, and overall effectiveness of the AI solution.
Figure 1. Diagram that shows the key steps in a RAG workflow
Adopting a data mesh architecture can enhance an organization’s ability to manage data effectively, leading to improved performance, innovation, and overall business success. In this guidance, you will discover some strategies to build data mesh solutions on AWS.
Figure 2. The data mesh organizes data into domains, where data are seen as quality products to expose for consumption
Amazon S3 is an object storage service that supports multiple use cases, including data architectures. Big data pipelines can use Amazon S3 to store input, output, and intermediate results. Machine learning systems use Amazon S3 to process application logs and build the datasets both for experimentation and for production model training. Given the importance of the service and the number of use cases that a foundational storage service can support, we want to share best practices, performance optimization, and cost optimization strategies to work with Amazon S3. This video shows how Anthropic designs its architecture around Amazon S3 in their data architecture.
Figure 3. Workloads with predictable patterns often have low retrieval rates for long periods of time after, so we can design to adopt cheaper storage classes for them
If you are curious about the underlying architecture of Amazon S3 and want to drill down into its internal design, you can watch the re:Invent video Dive deep on Amazon S3.
This is an AWS case study on how HPE Aruba Supply Chain successfully re-architected and deployed their data solution by adopting a modern data architecture on AWS. The new solution has helped Aruba integrate data from multiple sources, along with optimizing their cost, performance, and scalability. This has also allowed the Aruba Supply Chain leadership to receive in-depth and timely insights for better decision-making, thereby elevating the customer experience.
Figure 4. Reference architecture diagram showing HPE Aruba Supply Chain’s architecture, featuring Amazon S3
This workshop highlights advantage of adopting a modern data architecture on AWS. By integrating the flexibility of a data lake with specialized analytics services, organizations can significantly enhance their data-driven decision-making capabilities. We encourage everyone to explore how this architecture can streamline their analytics processes and support diverse use cases, from real-time insights to advanced machine learning. It’s an excellent opportunity to leverage modern data architecture.
Figure 5. Data architectures are fundamental to power use cases ranging from analytics to machine learning
Thanks for reading! In the next blog, we will cover some tips on how to get the best out of your developer experience on AWS. To revisit any of our previous posts or explore the entire series, visit the Let’s Architect! page.
Post Syndicated from Donnie Prakoso original https://aws.amazon.com/blogs/aws/simplify-and-enhance-amazon-s3-static-website-hosting-with-aws-amplify/
We are announcing an integration between AWS Amplify Hosting and Amazon Simple Storage Service (Amazon S3). Now, you can deploy static websites with content stored in your S3 buckets and serve over a content delivery network (CDN) with just a few clicks.
AWS Amplify Hosting is a fully managed service for hosting static sites that handles various aspects of deploying a website. It gives you benefits such as custom domain configuration with SSL, redirects, custom headers, and deployment on a globally available CDN powered by Amazon CloudFront.
When deploying a static website, Amplify remembers the connection between your S3 bucket and deployed website, so you can easily update your website with a single click when you make changes to website content in your S3 bucket. Using AWS Amplify Hosting is the recommended approach for static website hosting because it offers more streamlined and faster deployment without extensive setup.
Here’s how the integration works starting from the Amazon S3 console:
Deploying a static website using the Amazon S3 console
Let’s use this new integration to host a personal website directly from my S3 bucket.
To get started, I navigate to my bucket in the Amazon S3 console . Here’s the list of all the content in that S3 bucket:
To use the new integration with AWS Amplify Hosting, I navigate to the Properties section, then I scroll down until I find Static website hosting and select Create Amplify app.
Then, it redirects me to the Amplify page and populates the details from my S3 bucket. Here, I configure my App name and the Branch name. Then, I select Save and deploy.
Within seconds, AWS Amplify has deployed my static website, and I can visit the site by selecting Visit deployed URL. If I make any subsequent changes in my S3 bucket for my static website, I need to redeploy my application in the Amplify console by selecting the Deploy updates button.
I can also use the AWS Command Line Interface (AWS CLI) for programmatic deployment. To do that, I need to get the values for required parameters, such as APP_ID and BRANCH_NAME from my AWS Amplify dashboard. Here’s the command I use for deployment:
aws amplify start-deployment --appId APP_ID --branchName BRANCH_NAME --sourceUrlType=BUCKET_PREFIX --sourceUrl s3://S3_BUCKET/S3_PREFIXAfter Amplify Hosting generates a URL for my website, I can optionally configure a custom domain for my static website. To do that, I navigate to my apps in AWS Amplify and select Custom domains in the navigation pane. Then, I select Add domain to start configuring a custom domain for my static website. Learn more about setting up custom domains in the Amplify Hosting User Guide.
In the following screenshot, I have my static website configured with my custom domain. Amplify also issues an SSL/TLS certificate for my domain so that all traffic is secured through HTTPS.
Now, I have my static site ready, and I can check it out at https://donnie.id.
Things you need to know
More available features – AWS Amplify Hosting has more features you can use for your static websites. Visit the AWS Amplify product page to learn more.
Deployment options – You can get started deploying a static website from Amazon S3 using the Amplify Hosting console, AWS CLI, or AWS SDKs.
Pricing – For pricing information, visit Amazon S3 pricing page and AWS Amplify pricing page.
Availability – Amplify Hosting integration with Amazon S3 is now available in AWS Regions where Amplify Hosting is available.
Start building your static website with this new integration. To learn more about Amazon S3 static website hosting with AWS Amplify, visit the AWS Amplify Hosting User Guide.
Happy building,
— Donnie
Post Syndicated from Patrick Kennedy original https://www.servethehome.com/inside-100000-nvidia-gpu-xai-colossus-cluster-supermicro-helped-build-for-elon-musk/
We get inside access into the 100K NVIDIA GPU xAI Colossus cluster that Supermicro built for Elon Musk’s teams
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