Turn Your Data into a Competitive Advantage
AI adoption is accelerating across every industry—but the real gap isn’t in ambition, it’s in operationalizing AI reliably and at scale. If your organization is looking to move from early pilots to production-grade AI, FlashStack for AI shows how you can make that shift with confidence. FlashStack AI Factories, co-engineered by Pure Storage, Cisco, and NVIDIA, delivers AI Factory frameworks and provides clients a predictable, scalable path to train, tune, and deploy AI workloads—without introducing operational risk. FlashStack delivers meaningful advantages that help teams operationalize AI more effectively: Consistent, production-grade AI performance powered by NVIDIA’s full-stack architecture—ensuring compute, networking, and storage operate as a synchronized system for dependable training and inference. Faster deployment and easier scaling, enabled by unified management through Pure1 and Cisco Intersight, reducing operational overhead and accelerating time to value. Stronger cyber resilience and reduced risk, with SafeMode immutable snapshots and deep integration with leading SIEM/SOAR/XDR ecosystems to safeguard high-value AI data. Meaningful business outcomes, from shortening AI innovation cycles to powering new copilots, intelligent assistants, and data-driven services. Together, these capabilities help enterprises turn raw data and processing power into AI-driven results—securely, sustainably, and without operational complexity. Read More! FlashStack AI FactoriesAlternative Virtualization Meet-Up at //Accelerate
Our company like many others have parted ways with VMWare. We decided not to renew this last April and are currently running unsupported/perpetual as we look for a replacement hypervisor. Costs on a 7000+ core renewal came in at about 5x what we paid in previous years. Just a little backstory, but this post is not to discuss that. For hardware we currently run Cisco ACI, Cisco UCS and Pure Storage in a converged architecture. What Cisco/Pure call Flashstack. 4 Sites, 200+ blades, Mix of 14 //x and //c Arrays. We are heavy Vvol users today. We have narrowed our search down to Proxmox, XCP-NG, and OpenShift Virtualization. Successes with Proxmox have been great, deployment (iSCSI Boot), automation, migration, etc. Winning so far. XCP-NG, similar to Proxmox. Some issues with Migrations. But overall working. OpenShift, just started vetting. Have a workshop scheduled with RedHat to really test out and see if the product is a good fit. Would require Portworx. Now to what I am wondering, would any of you that will be attending Pure //Accelerate be interested in a meet-up to network and discuss the trials and tribulations with these or other alternative hypervisors on Pure Storage? I am happy to present my decision process, success criteria, testing results and implementation configuration for each. If we get enough people I can ask my AE/SE to see if Pure would allow us use of a breakout meeting room. If interested let me know, I would prefer to keep this vendor neutral other than Pure, as we would not be going to a Pure conference if not interested or already running Pure Storage.Join Pure Storage at Cisco Live 2025 in San Diego!
Join Pure Storage at Cisco Live 2025! San Diego to see how FlashStack® can help you uncomplicate your hybrid cloud infrastructure. Stop by Booth #2541 to chat with the Pure Storage team and learn how you can - rapidly deploy risk-free AI infrastructure, protect your strategic data from core to edge, and more! Curious about how FlashStack can boost your AI game? Catch our Cisco experts in an in-depth speaker session: Title: The Fastest Path to Successful AI Deployment Speaker: Craig Waters Date: Monday, June 9 Time: 12:40pm Register here!Have you implemented AI solutions using FlashStack?
If so, how has your experience been? If not, do you have any questions? A joint solution by Pure Storage, Cisco, and NVIDIA simplifies the complexities of AI with high performance, validated designs, and enhanced scalability. It's designed to meet the demands of AI workloads with ease. Read all about it!
