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Cincinnati Pure User Group: Real-time Enterprise File
Register Now => Join us for an exclusive Pure User Group (PUG) session dedicated to the future of file services. This isn't just a technical briefing; it’s a community gathering designed for peer-to-peer learning and strategic roadmap building. We’re diving deep into the Real-time Enterprise File vision—exploring how to unify your environment across FlashArray and FlashBlade to eliminate silos and escape the "forklift upgrade" trap forever. Whether you’re managing simple departmental shares or complex AI/ML pipelines, this is your chance to connect with local experts, share battle-tested insights, and see how to make your data plane as agile as your business demands. What You’ll Learn The Power of Choice: Understand how Pure’s file capabilities span the entire portfolio. We’ll clarify exactly when to leverage FlashArray vs. FlashBlade for workloads ranging from VDI and VMware over NFS to massive AI/ML repositories. Production-Ready Excellence: Go beyond the basics with a look at the capabilities that matter in the real world: multi-protocol support (SMB/NFS), directory integration, Kerberos security, and multi-tenancy for segmented environments. The "Last Refresh" Strategy: Get practical, no-nonsense guidance on sizing and migration tooling. Learn how to consolidate legacy filers and execute a migration that ensures you never have to do a forklift upgrade again. Peer-to-Peer Wisdom: This is a user group first. You’ll hear directly from local customers about their real-world journeys—what worked, what didn't, and the lessons they learned that you can apply to your own data center tomorrow. Event Agenda 2:00 PM | Welcome & Round-the-Room: We start with quick intros. We want to know who you are and exactly what technical hurdles you’re looking to clear. 2:15 PM | The Real-time Enterprise File Vision: An overview of the vision and where the portfolio is headed. See what’s new and what’s next for FlashArray and FlashBlade. 2:40 PM | Deep Dive: Design Patterns & Use Cases: We’ll walk through common architectural designs for home directories, content repositories, and NFS datastores, including proven protection and recovery patterns. 3:10 PM | Customer Spotlight & Panel: A 25-minute interactive session with local peers. Hear their architecture stories and get your toughest questions answered in an open Q&A. 3:35 PM | Whiteboard Session: Your File Roadmap: An open, interactive conversation about your specific challenges—from unstructured data growth to migration blockers. Let’s map out where Pure can help. 3:55 PM | Wrap-up & Next Steps: Key takeaways, resources for your team, and a preview of our next PUG event. 4:00 PM | Networking & Happy Hour Date & Time January 28, 2026 2:00 PM - 4:00 PM EST Location Aces Pickleball 2730 Maverick Dr Norwood, OH 45212 (Factory 52)Ask Us Everything about Pure Storage + Nutanix
💬 Get ready for our January 2026 edition of Ask Us Everything, this Friday, January 16th at 9 AM Pacific. This month is all about Pure Storage + Nutanix. If you have a burning question, feel free to ask it here early and we'll add it to the list to answer on Friday. Or if we can't get it answered live, our Pure Storage + Nutanix experts can follow up here. thomasbrown Cody_Hosterman jhoughes & dpoorman are the experts answering your questions during the conversation and here on the community. See you this Friday! (Oh, and if you haven't registered yet, there's still time!) Or, check out some of these self-serve resources: Solution Brief Pure Report Podcast Pure360 Video Nutanix, Intel, & Pure white paper EDIT: Thanks for joining in! If you have additional burning questions and comments, leave them in the comments below for the team!Pure Storage Cloud Dedicated on Azure: An intro to Performance
Introduction With Pure Storage Cloud Dedicated on Microsoft Azure, performance is largely governed by three factors that need to be taken into consideration: front-end controller networking, controller back‑end connection to managed disks, and the Purity data path. This post explains how Azure building blocks and these factors influence overal performance. Disclaimer: This post requires basic understanding of PSC Dedicated architecture. Real-life Performance varies based on configuration and workload; examples here are illustrative. Architecture: the building blocks that shape performance Cloud performance often comes from how compute, storage, and networking are assembled. PSC Dedicated deploys two Azure VMs as storage controllers running the Purity operating environment and uses Azure Managed Disks as persistent media. Initiator VMs connect over the Azure Virtual Network using in‑guest iSCSI or NVMe/TCP. Features like inline data reduction, write coalescing through NVRAM, and an I/O rate limiter help keep the array stable and with predictable performance under saturation. Front-end performance: networking caps Azure limits the outbound (egress) bandwidth of Virtual Machines. Each Azure VM has a certain network egress cap assigned and cannot send out more data than what the limit allows. As PSC Dedicated controllers run on Azure VMs, this translates into the following: Network traffic going INTO the PSC Dedicated array - writes - not throttled by Azure outbound bandwidth limits Network traffic going OUT of the PSC Dedicated array - reads - limited User-requested reads (e.g. from an application) as well as any replication traffic leaving the controller share the same egress budget. Because of that, planning workloads with replication should be done carefully to avoid competing with client reads. Back-end performance: VM caps, NVMe, and the write path The Controller VM caps Similarly to frontend network read throughput, Azure enforces per‑VM limits on total backend IOPS and combined read/write throughput. The overall IOPS/throughput of a VM is therefore limited by the lower of: the controller VM's IOPS/throughput cap and the combined IOPS/throughput of all attached managed disks. To avoid unnecessary spend due to overprovisioning, managed disks of PSC Dedicated arrays are configured as to saturate the controller backend caps just right. NVMe backend raises the ceiling Recent PSC Dedicated releases adopt an NVMe backend on supported Azure Premium SSD v2 based SKUs, increasing the controller VM’s backend IOPS and bandwidth ceilings. The disk layout and economics remain the same while the array gains backend headroom. The write path Purity secures initiator writes to NVRAM (for fast acknowledgment) and later destages to data managed disks. For each logical write, the backend cap is therefore tapped multiple times: a write to NVRAM a read from NVRAM during flush and a write to the data managed disks Under mixed read/write non-reducible workloads this can exhaust the combined read/write backend bandwidth and IOPS of the controller VM. Raised caps of the NVMe backend help here. Workload characteristics: iSCSI sessions and data reducibility Block size and session count Increasing iSCSI session count between Initiator VMs and the array does not guarantee better performance; with large blocks, too many sessions can increase latency without improving throughput, especially when multiple initiators converge on the same controller. Establish at least one session per controller for resiliency, then tune based on measured throughput and latency. Data reduction helps extend backend headroom When data is reducible, PSC Dedicated writes fewer physical bytes to backend managed disks. That directly reduces backend write MBps for the same logical workload, delaying the point where Azure’s VM backend caps are reached. The effect is most pronounced for write‑heavy and mixed workloads. Conversely, non‑reducible data translates almost 1:1 to backend traffic, hitting limits sooner and raising latency at high load. Conclusion Predictable performance in the cloud is about aligning architecture and operations with the platform’s limits. For PSC Dedicated on Azure, that means selecting the right controller and initiator VM SKUs, co‑locating resources to minimise network distance, enabling accelerated networking, and tuning workloads (block size, sessions, protocol) to the caps that actually matter. Inline data reduction and NVMe backend extend headroom meaningfully (particularly for mixed workloads) while Purity’s design keeps the experience consistent. Hopefully, this post was able to shed light on at least some of the performance factors of PSC Dedicated on Azure.
Veeam v13 Integration and Plugin
Hi Everyone, We're new Pure customers this year and have two Flasharray C models, one for virtual infrastructure and the other will be used solely as a storage repository to back up those virtual machines using Veeam Backup and Replication. Our plan is to move away from the current windows-based Veeam v12 in favor of Veeam v13 hardened Linux appliances. We're in the design phase now but have Veeam v13 working great in separate environment with VMware and HPE Nimble. Our question is around Pure Storage and Veeam v13 integration and Plugin support. Veeam's product team mentions there is native integrations in v12, but that storage vendors should be "adopting USAPI" going forward. Is this something that Pure is working on, or maybe already has completed with Veeam Backup and Replication v13?
Proxmox VE
Hi all Hope you're all having a great day. We have several customers going down the Proxmox VE road. One of my colleagues was put onto https://github.com/kolesa-team/pve-purestorage-plugin as a possible solution (as using Pure behind Proxmox (using the native Proxmox release) is not a particularly Pure-like experience. Could someone from Pure comment on the plugin's validity/supportability?
5 AI Predictions Every Infrastructure Leader Needs to Know in 2026
January 22 | Register Now! In 2026, AI moves from experimentation to execution—and infrastructure leaders are in the driver's seat. Organizations that build the right data foundations now will be the ones turning AI into a true competitive advantage. Join us as we explore five trends shaping the future of AI infrastructure, from unlocking the value of your data to architecting for production-scale AI workloads. Walk away with a clear roadmap for positioning your infrastructure as the engine that powers your organization's AI ambitions. In this webinar, you'll learn: How to get your data ready for AI All about the NVIDIA AI Factory and Data Platform What it takes to scale AI from pilot to production Practical ways to bring AI into your organization Register Now!
Stop Prompting, Start Context Engineering
4 MIN READ This blog post argues that Context Engineering is the critical new discipline for building autonomous, goal-driven AI agents. Since Large Language Models (LLMs) are stateless and forget information outside their immediate context window, Context Engineering focuses on assembling and managing the necessary information—such as session history, long-term memory (embeddings, RAG indexes), and tool outputs—for the agent every single turn. The post asserts that storage, not the LLM or the prompt, is the primary performance bottleneck for AI at scale. The speed of the underlying storage architecture dictates the agent's responsiveness because it must quickly retrieve and persist context data repeatedly.Taking Snapshots of Databases on VMFS Datastores
Hey friends - hopefully you all are taking advantage of our snapshots for copy data management? Well, those of you who use VMDKs know that there's an extra headache thanks to the VMFS datastore layer. Fortunately, I've just published some new examples in our Github repository and have written up a solution overview on my blog! Check it out! https://sqlbek.wordpress.com/2026/01/08/taking-snapshots-of-databases-on-vmfs-datastores/ Github: Refresh VMFS VMDK(s) with Snapshot Point in Time Recovery – VMFSAnnouncing the General Availability of Purity//FB 4.6.6
We are happy to announce the general availability of 4.6.6, the seventh release in the 4.6 Feature Release line. See the release notes for all the details about these, and the many other features, bug fixes, and security updates included in the 4.6 release line. UPGRADE RECOMMENDATIONS AND EOL SCHEDULE Customers who are running any previous 4.6 version should upgrade to 4.6.6. Customers who are looking for long-term maintenance of a consistent feature set are recommended to upgrade to the 4.5 LLR. Check out our AI Copilot intelligent assistant for deeper insights into release content and recommendations. Development on the 4.6 release line will continue through February 2026. After this time the full 4.6 feature set will roll into the 4.7 Long Life Release line for long-term maintenance, and the 4.6 line will be declared End-of-Life (EOL). HARDWARE SUPPORT This release is supported on the following FlashBlade Platforms: FB//S100, FB//S200 (R1, R2), FB//S500 (R1, R2), FB//ZMT, FB//E, FB//EXA LINKS AND REFERENCES Purity//FB 4.6 Release Notes Purity//FB Release and End-of-Life Schedule Purity//FB Release Guidelines FlashBlade Hardware and End-of-Support FlashBlade Capacity and Feature Limits Pure1 Manage AI Copilot
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Got questions about Pure Storage + Nutanix? Get answers.
In this month’s episode of Ask Us Everything, we’re talking about the next chapter in...
This blog post argues that Context Engineering is the critical new discipline for building autonomous, goal-driven AI agents. Since Large Language Models (LLMs) are stateless and forget information o...
This article originally appeared on Medium.com and is republished with permission from the author.
Cloud-native applications must often co-exist with legacy applications. Those legacy applications ...
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