# HDD Published articles for HDD. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Seagate and WD AI Storage Research Finds Enterprises Rank Storage Above Compute as the AI Bottleneck DevFeed: [Seagate and WD AI Storage Research Finds Enterprises Rank Storage Above Compute as the AI Bottleneck]() Original publisher: [Read original article]() Author: Lyle Smith Published: 2026-09-15T17:23:54Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [Data Infrastructure](), [AI Infrastructure](), [idc](), [Inference](), [Retrieval-Augmented Generation](), [synthetic-data]() Tags: [ai](), [compute](), [data-infrastructure](), [datasets](), [enterprise](), [genai](), [hdd](), [idc](), [inference](), [reports](), [research](), [retrieval](), [storage](), [synthetic-data]() ### AI overview Seagate and WD published separate studies indicating that AI is increasing enterprise storage requirements and extending data retention. Although their headline percentages differ because they asked different questions, both reports point to storage becoming a larger part of AI infrastructure planning alongside growing archive and retrieval needs. ### Source excerpt Seagate and WD published separate AI storage studies within days of each other; the headline numbers: Seagate says 99% of enterprises expect AI to increase their storage requirements over the next three years, while WD's IDC research puts the comparable figure at 74%. Read the fine print, and both reports land in the same directional The post Seagate and WD AI Storage Research Finds Enterprises Rank Storage Above Compute as the AI Bottleneck appeared first on StorageReview.com. ## Micron 6600 ION 245TB: Swap the Hard Drives, Power an NVL72 for Free DevFeed: [Micron 6600 ION 245TB: Swap the Hard Drives, Power an NVL72 for Free]() Original publisher: [Read original article]() Author: Brian Beeler Published: 2026-09-03T17:00:39Z Content type: article Language: en Sources: [StorageReview.com]() Topics: [Benchmark](), [benchmarking](), [datacenter](), [GB200](), [GPU](), [Server](), [dell]() Tags: [benchmark](), [compute](), [data-center](), [dell](), [efficiency](), [enterprise](), [gb200](), [gpu](), [hdd](), [measurements](), [nvl72](), [performance](), [servers](), [ssd](), [storage]() ### AI overview This article evaluates replacing eight 30TB nearline HDDs with one 245TB Micron 6600 ION SSD. Its measurements indicate lower power consumption, substantially higher read efficiency, and a reduction from 22 racks of HDD storage to six racks of flash at exabyte scale, potentially freeing enough power for a GB200 NVL72. ### Source excerpt For two decades, the SSD-versus-HDD conversation ended the same way: flash wins on performance, disk wins on price per terabyte, and the size of that price gap settled the argument in favor of bulk storage. As storage technology has matured and AI has taken over, that framing is clearly out of date. The largest data The post Micron 6600 ION 245TB: Swap the Hard Drives, Power an NVL72 for Free appeared first on StorageReview.com. ## Unifi UNAS 2 and UNAS 4. - One Year Later DevFeed: [Unifi UNAS 2 and UNAS 4. - One Year Later]() Original publisher: [Read original article]() Author: Rob Andrews Published: 2026-08-26T11:01:27Z Content type: comparison Language: en Sources: [NAS Compares]() Topics: [UNAS 2](), [UNAS 4](), [DRIVE](), [Ubiquiti](), [systems]() Tags: [drive](), [hdd](), [network-attached-storage-nas](), [review](), [storage](), [ubiquiti](), [unas](), [unas-2](), [unas-2-1-year-later](), [unas-2-bad](), [unas-2-good](), [unas-2-nas](), [unas-2-vs-4](), [unas-2026](), [unas-4](), [unas-4-1-year-later](), [unas-4-nas](), [unas-4-ne-year-later](), [unas-4-review](), [unas-review](), [unas-vs-qnap](), [unas-vs-synology](), [unas-vs-ugreen](), [uncategorised](), [unifi-2026](), [unifi-2027](), [unifi-enas](), [unifi-nas](), [unifi-nas-2026](), [unifi-nas-review](), [unifi-unas-2](), [unifi-unas-4](), [unifi-unas-6](), [unifi-unas-pro]() ### AI overview A one-year-later review of Ubiquiti's UniFi UNAS 2 and UNAS 4 desktop storage systems, including their positioning within the UniFi Drive platform and the UNAS 2's two-HDD-bay design for smaller deployments. ### Source excerpt UniFi UNAS 2 and UNAS 4 1 Year Later Review When Ubiquiti introduced the UNAS 2 and UNAS 4 in September 2025, the company was attempting to bring its comparatively simple UniFi Drive storage platform into a pair of compact desktop systems. The UNAS 2 targeted smaller deployments with 2 HDD bays, while the UNAS [...] ## Monitor Your Drive Health with Performance Co-Pilot on Fedora DevFeed: [Monitor Your Drive Health with Performance Co-Pilot on Fedora]() Original publisher: [Read original article]() Author: Paul Evans Published: 2026-08-10T08:00:00Z Content type: article Language: en Sources: [Fedora Magazine]() Topics: [Fedora](), [Monitoring](), [Grafana](), [telemetry]() Tags: [data](), [diagnostics](), [drive](), [farm](), [fedora-project-community](), [grafana](), [hdd](), [health](), [home-server](), [metrics](), [monitor](), [monitoring](), [nvme](), [open-source](), [performance](), [performance-metrics](), [self-hosted](), [server](), [smart](), [ssd](), [telemetry](), [wwid]() ### AI overview This article explains how to monitor drive health on Fedora using Performance Co-Pilot (PCP). It covers SMART metric collection for HDDs, SSDs, and NVMe drives, NVMe error-log decoding, WWID-based tracking, Seagate FARM telemetry, continuous metric collection, and Grafana dashboards for viewing drive-health trends. ### Source excerpt You wake up one morning to find your home server unresponsive, after some investigation you discover a failed NVMe drive taking your self-hosted services and data with it. Perhaps you're a system administrator and a workstation's SSD has been silently accumulating errors for months, and now a user is reporting corrupted files. Drive failures are [...] ## Shucking WD Elements 20TB DevFeed: [Shucking WD Elements 20TB]() Original publisher: [Read original article]() Author: Tom Published: 2025-11-30T00:00:00Z Content type: tutorial Language: en Sources: [Tomasz Gągor]() Topics: [benchmarking](), [Testing](), [Synology]() Tags: [20tb-hard-drive](), [backup](), [badblocks-testing](), [bash](), [benchmarks](), [fio-performance](), [guide](), [hdd](), [linux](), [nas](), [nas-upgrade](), [performance](), [shucking-wd-elements](), [speed](), [standard](), [storage](), [stress](), [synology](), [testing](), [zfs]() ### AI overview A hands-on guide to shucking WD Elements 20TB hard drives for use in a Synology NAS. It reports average read/write performance just below 200 MB/s and describes stress-testing the drives before installation, including a workload adjustment that improved throughput to 200-300 MB/s. ### Source excerpt A detailed guide on shucking WD Elements 20TB drives, including testing, performance benchmarks, and stress testing. ## Remote VAEs for decoding with Inference Endpoints 🤗 DevFeed: [Remote VAEs for decoding with Inference Endpoints 🤗]() Original publisher: [Read original article]() Author: hlky; Sayak Paul Published: 2025-02-24T00:00:00Z Content type: tutorial Language: en Sources: [Hugging Face - Blog]() Topics: [VAE](), [inference-endpoints](), [diffusers](), [hugging face](), [Inference Performance](), [Open Source](), [Deadlock]() Tags: [artificial-intelligence](), [concurrency](), [cpu](), [data](), [diffusers](), [diffusion](), [generate](), [generation](), [getting-started](), [gpu](), [hdd](), [inference](), [inference-endpoints](), [nvme](), [open-source](), [queue](), [remote](), [tensors](), [time](), [vae]() ### AI overview This article presents an experimental approach for decoding latent-space diffusion outputs with remote VAEs hosted on Inference Endpoints. It explains how remote decoding can reduce consumer GPU memory pressure, avoid the quality loss associated with tiled decoding, and improve concurrency by queueing generation requests. The article includes setup and usage examples for random tensors and pipelines involving SD v1.5, Flux, and HunyuanVideo. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Amazon EBS Basics and Best Practices DevFeed: [Amazon EBS Basics and Best Practices]() Original publisher: [Read original article]() Author: Guillermo Ojeda Published: 2023-08-30T16:15:03Z Content type: tutorial Language: en Sources: [Guille Ojeda]() Topics: [Amazon EC2](), [Amazon Web Services](), [cloud-infrastructure](), [Cloud]() Tags: [amazon](), [aws](), [beginner-developers](), [cloud-architecture](), [cloud-computing](), [cost](), [ec2](), [hdd](), [latency](), [ssd](), [storage]() ### AI overview A tutorial covering Amazon Elastic Block Store (EBS) fundamentals and best practices, including how EBS volumes provide persistent storage for Amazon EC2 instances, how volumes are managed, and the characteristics of GP3 volumes. ### Source excerpt Elastic Block Store (EBS for short) is a block-level storage service for EC2 instances. Essentially it's a virtual SSD or HDD that you attach to EC2 instances, so they can have persistent storage. Honestly, EBS is pretty boring to talk about, but if ... ## Persistent memory design choices and use-cases DevFeed: [Persistent memory design choices and use-cases]() Original publisher: [Read original article]() Published: 2022-05-26T00:00:00Z Content type: article Language: en Sources: [Kt. Academy]() Topics: [Data structures](), [data]() Tags: [code](), [data-structure](), [hdd](), [memory](), [node](), [persistence](), [storage](), [workshop-learning-programming]() ### AI overview This article explains persistent memory as non-volatile storage and examines full versus selective persistence for data structures. It also discusses use cases, including a persistent dictionary and a key/value storage engine using a skiplist. ### Source excerpt Let's understand some design choices with persistent memory and use-cases of persistent memory. ## Introducing persistent memory DevFeed: [Introducing persistent memory]() Original publisher: [Read original article]() Published: 2022-05-12T00:00:00Z Content type: tutorial Language: en Sources: [Kt. Academy]() Topics: [data](), [Latency](), [IO](), [servers]() Tags: [hdd](), [io](), [latency](), [memory](), [nvme](), [overhead](), [performance](), [ssd](), [storage](), [storage-engine](), [workshop-learning-programming]() ### AI overview An introduction to persistent memory, a non-volatile storage technology that fits in standard DIMM slots. It explains its position between DRAM and storage, its durability and byte addressability, and how applications can use it to avoid block I/O overhead. ### Source excerpt Let's learn the basics of persistent memory, its characteristics, how it works and the beauty of byte addressability. ## What You Can Learn From Old Hard Drive Adverts DevFeed: [What You Can Learn From Old Hard Drive Adverts]() Original publisher: [Read original article]() Author: Marc Brooker Published: 2021-03-25T00:00:00Z Content type: article Language: en Sources: [Marc Brooker's Blog](), [Marc Brooker's Blog]() Topics: [Latency](), [systems](), [Hardware](), [IO]() Tags: [hardware](), [hdd](), [io](), [latency](), [ssd](), [storage](), [systems]() ### AI overview The article examines how storage technology has improved over time, showing that capacity and bandwidth have grown much faster than latency. Comparing old hard drives, modern hard drives, and SSDs, it explains why random I/O remains increasingly costly despite major hardware advances. ### Source excerpt What You Can Learn From Old Hard Drive Adverts The single most important trend in systems. Adverts for old computer hardware, especially hard drives, are a fun staple of computer forums and the nerdier side of the internet1. For example, a couple days ago, Glenn Lockwood tweeted out this old ad: At least this isn't an ad for a HAMR drive. $10k in today's dollars. pic.twitter.com/2h2g3Gnguw -- Glenn K. Lockwood (@glennklockwood) March 24, 2021 Apparently from the early '80s, these drives offered seek times of 70ms, access speeds of about 900kB/s, and capacities up to 10MB. Laughable, right? But these same ads hide a really important trend that's informed system design more than any other. To understand what's going on, let's compare this creaky old 10MB drive to a modern competitor. Most consumers don't buy magnetic drives anymore, so we'll throw in an SSD for good measure. XCOMP 10MB Modern HDD Change Modern SSD Change Capacity 10MB 18TiB 1.8 million times 2 TiB 200,000x Latency 70ms 5ms 14x 50μs 1400x Throughput 900kB/s 220MB/s 250x 3000MB/s 3300x IOPS/GiB (QD1) 1400 0.01 0.00007x 10 0.007x Or there abouts2. Starting with the magnetic disk, we've made HUGE gains in storage size, big gains in throughput, modest gains in latency, and a seen a massive drop in random IO per unit of storage. What may be surprising to you is that SSDs, despite being much faster in every department, have seen pretty much the same overall trend. This is not, by any stretch, a new observation. 15 years ago the great Jim Gray said "Disk is Tape". David Patterson (you know, Turing award winner, RISC co-inventor, etc) wrote a great paper back in 2004 titled Latency Lags Bandwidth that made the same observation. He wrote: I am struck by a consistent theme across many technologies: bandwidth improves much more quickly than latency. and In the time that bandwidth doubles, latency improves by no more than a factor of 1.2 to 1.4. That may not sound like a huge amount, but remember that we're talking ## Linux I/O 栈浅析 DevFeed: [Linux I/O 栈浅析]() Original publisher: [Read original article]() Author: Joway Published: 2019-08-11T00:00:00Z Content type: tutorial Language: zh Sources: [Random Thoughts]() Topics: [IO](), [Linux](), [Cache](), [file](), [Ext4](), [XFS]() Tags: [block](), [cache](), [ceph](), [ext4](), [file](), [filesystem](), [hdd](), [hdfs](), [io](), [linux](), [mysql](), [oracle](), [ssd](), [tech](), [xfs]() ### AI overview This article provides a high-level overview of Linux file I/O, tracing the path from applications through VFS, page cache, filesystems, FUSE, block devices, and I/O scheduling. It also explains hard and symbolic links, direct I/O, filesystem partitioning, and access to raw devices. ### Source excerpt 在 Linux 中，所有外部资源都以文件形式作为一个抽象视图，并提供一套统一的接口给应用程序调用。本文将以宏观视角试图阐述 Linux 中关于文件 IO 的整个调用脉络。 VFS 在 Linux 中，所有 IO 都必须先经由 VFS 层进行转发。通过 VFS 将包括磁盘、网络 Socket、打印机、管道等资源全部封装成统一的接口。