How The Storage Industry Can Create a Sustainability Roadmap

One AI customer asked for 100 exabytes of storage, and the simple act of picturing that request tells you why AI infrastructure has entered a new era. In this SNIA Experts on Data episode, we sit down with Aaron Ogus, Technical Fellow at Microsoft working on Azure Storage and Azure Core to translate the big numbers into reality: kilometers of racks, exponentially rising demand, and a supply chain where hard drives, flash, DRAM, and even silicon materials can become the limiting factor. We also wrestle with data center public concerns, sustainability tradeoffs, and the social implications of AI productivity that may outpace current economic assumptions.SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

We keep talking about sustainability like it’s a dashboard metric, but what if the biggest wins are hiding in plain sight, inside the storage hardware we refresh every few years? We talk with Meta Senior Staff Systems Engineer, Lisa Rivalin, about turning storage sustainability into real engineering work, from reusing drives safely to measuring what “useful work” actually means. Hear the specifics on what it takes to reduce real data center environmental impact without turning it into marketing.If you care about circular economy, carbon accounting, GHG Protocol realities, and practical data center sustainability standards, this conversation is for you.SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

AI infrastructure is pushing data centers into a new phase where the limiting factor is not just compute, but power, cooling, and the physics of moving data fast enough to keep GPUs busy. At SDC26, we bring a live panel together with Trent Johnson (IBM), Glenn Hanna (Lenovo), and Anthony Constantine (Micron) to dig into what’s changing on the ground and why the most important work often looks unglamorous: cables, connectors, SSD form factors, and the standards that make multi-vendor systems actually interoperate.We talk candidly about why liquid cooling is shifting from a niche HPC tool to a mainstream requirement, and why that transition is harder than it sounds and we discuss enterprise AI patterns, including hybrid AI strategies where training happens in the cloud while inference and sensitive data stay on-prem for sovereignty and control.SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

The fastest way to waste time with AI is to design it like you live in a perfect hyperscale world. In this episode, we sit down with Rebecca Weekly,  Chief Technology Officer at brk tech, a Berkshire Hathaway Group Company, to talk about what enterprise AI really runs on: durable data, messy history, and constraints you cannot wish away.  Rebecca breaks down the enterprise data estate: silos formed over decades, governance and compliance requirements, and the metadata you need to decide what is trustworthy and what is allowed. And she offers practical guidance on AI governance, AI gateways, authentication and authorization, observability, cost controls, and why starting with productivity use cases can build momentum without putting your crown jewels at risk.SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

The compute curve is exploding, but memory is not, and that gap is now one of the biggest constraints in AI infrastructure. We unpack the “memory wall” and why it shows up so clearly in AI inference, where time to first token, token throughput, and unpredictable demand can make yesterday’s architectures feel suddenly brittle.  We’re joined by Dr. J Metz, Chair of the SNIA Board of Directors, and Jack Guedj, one of three co-chairs of the new SNIA Compute, Memory and Storage Community MRAM Alliance Special Interest Group to talk about MRAM (magnetoresistive random access memory), and why the MRAM Alliance joined forces with SNIA. The goal is straightforward: bring persistent memory conversations into the same room as storage standards, system design realities, and the messy trade-offs that appear at scale. When a “medium” cluster can mean 100,000 GPUs, you cannot treat memory, storage, networking, protection, and security as separate puzzles.  We dig into what makes MRAM interesting for modern systems: very low latency reads, strong performance potential for inference, persistence without power, and the possibility of reducing power draw by eliminating refresh overhead. Hear how to connect the dots between the memory wall, AI inference performance, and discover why persistent memory is becoming a system-level priority. SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

Your customers don’t care who wrote the code, they care that “AWS S3 compatible” actually works with the apps they already run. That’s why SNIA developed the Cloud Object Storage Plugfest Program – a collaborative, multi-vendor interoperability testing environment for S3 developers. In this episode, we sit down with Cloud Object Storage developers, Mark Trinh (Oracle), Jason CWIK (DDN), Veer Kumar (Nutanix) and Michael Hoard (Chair of the SNIA Cloud Storage Technologies Community), to explain why this Plugfest is the fastest path to real S3 interoperability and faster bug fixes.  The Plugfest participants speak candidly about friction points in S3 compatible object storage: clients that behave differently than the documentation suggests, API options that leave too much room for interpretation, and edge cases that only appear when you test across many vendors. They highlight why AI-driven workloads are raising the stakes for S3 compatible storage and discuss why an NDA-based Plugfest model matters for fast troubleshooting, direct engineer-to-engineer collaboration, and practical fixes.SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

DNA data storage is moving from a fascinating research topic toward something that can eventually live alongside enterprise storage in real data centers, but the leap is not only about chemistry or sequencing speed. It is about manageability, interoperability, and standardized APIs that let operators monitor, provision, and troubleshoot systems at scale. In this conversation, Vincent Franceschini, co-chair of the SNIA DNA Data Storage Alliance and Richelle Ahlvers, long-time chair of the SNIA Storage Management Community and primary author of the SNIA Swordfish® specification, connect the dots between a new storage medium and the standards-based management that makes it operable at scale.Archives are turning “active” because of AI, and long-term preservation is back in the spotlight. DNA data can become a durable data center technology if standards are built early, models are shared openly, and the community aligns on terminology, lifecycle operations, and monitoring so tomorrow’s archives remain readable and manageable for decades.  SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

In the most recent webinar in the SNIA Data, Storage & Networking “AI Stack” webinar series, “From Data to Decisions: Understanding How AI Models Learn,” Cal Foshee and Eric Gamble provided an in-depth look at how computer vision models learn. They shared specific techniques and concrete examples of how to train and test these models, drawing on their many years of experience. In this interview, Cal and Eric, take a deeper dive on the questions around how computer vision really works in production: small models working in sequence, bounding boxes as signal gates, and the relentless pursuit of pattern over assumption. Practical tips cover OCR, rotation, error bucketing, versioning, and why “fail fast” is more than a slogan. And webinar moderator, Erik Smith, explains what the “AI Stack” series is all about. SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

 The SNIA Data, Storage & Networking (DSN) Community launched a multi-part AI Stack Webinar Series designed to provide education and a comprehensive view of the AI landscape from data pipelines to model deployment. Hear experts, Erik Smith, Justin Potuznik, and Tim Lustig answer AI frequently asked questions: •       Exploring the differences between AI (the broader concept), machine learning (systems learning from data), and deep learning (neural networks extracting features from massive datasets)•       Understanding the "token economy" monetization model where AI services charge based on inputs/outputs •       Examining the shift toward on-premises AI deployments driven by data sovereignty, security concerns, and cloud cost management •       Implementing security through data validation, sanitization, and guardrails to protect AI systems from misuse •       Recognizing AI's transformative potential beyond current generative applications into agentic systems and physical embodiments  If you'd like to contribute to the AI Stack Webinar Series or have topics you'd like to see covered, contact the SNIA Data, Storage & Networking (DSN) chair at [email protected] or visit the SNIA website at snia.org. SNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn

SNIA Chair, J Metz, introduces SNIA Storage.AI™, an open standards project for efficient data services related to AI workloads. Storage.AI will focus on industry-standard, non-proprietary, and neutral approaches to solving AI-related data problems to optimize the performance, efficiency, and cost-effectiveness of AI workloads. Hear about the industry leaders who have combined forces to solve AI-related data challenges.Learn more at snia.aiSNIA is an industry organization that develops global standards and delivers vendor-neutral education on technologies related to data.  In these interviews, SNIA experts on data cover a wide range of topics on both established and emerging technologies.About SNIA:Website Educational LibraryX/Twitter LinkedIn