Ask Us Everything About Pure1 AI Copilot, MCP Server and Fusion
September 18 | Register Now! Got questions about AI-powered storage management? Get answers. This month we’re diving into how AI and automation can help infrastructure teams simplify storage operations at scale. See how Pure1® AI Copilot, the Pure1 Manage MCP Server, and Everpure Fusion™ work together to help you understand what’s happening across your environment, connect AI tools to operational data, and simplify management across your fleet. Learn to manage your storage with even less effort, and: Get actionable answers in plain language with Pure1 AI Copilot Connect AI agents and tools to live Pure1 operational data with the Pure1 Manage MCP Server Simplify provisioning and day-to-day management across arrays with Everpure Fusion Move from insight to action faster with an intelligent, more connected approach to operations Bring your questions for our experts, who are ready to discuss real-world AI and automation use cases and show how these capabilities can help you simplify operations while maintaining control across your Everpure environment. Register Now!Enterprise Data Cloud: Managing Data, Not Just Storage
August 6 | Register Now Infrastructure teams have always managed applications. AI requires them to manage data. That's a different challenge, and most platforms weren't built for it. The Enterprise Data Cloud architecture from Everpure bridges that gap, bringing data intelligence into the same platform infrastructure teams already manage, so infrastructure and data teams are finally working from a single, unified view. In this session, we'll dig into what it means to manage a platform built for both operational performance and AI readiness, and the changes when infrastructure can finally gain visibility into its data, not just storage. Key takeaways: Why the shift from application-centric to data-first infrastructure changes how platforms need to be managed How Everpure brings data intelligence into the operational layer without adding tools, teams, or complexity What shared visibility across infrastructure and data teams actually unlocks for AI initiatives How to manage a platform that serves every workload, from archive to AI Register Now!
Fusion preset: VMFS datastore volumes for VMware ESXi clusters (with two-tier snapshots and QoS)
Hi all, I put together a Fusion preset for one of the most common block use cases in our environment: provisioning VMFS datastore volumes for a VMware ESXi cluster. What it does: - 4x 4 TiB datastore volumes on a FlashArray//X storage class (adjust count/size to your cluster design) - Two-tier snapshot retention: hourly snapshots kept for 1 day (fast rollback) plus daily snapshots kept for 30 days - Per-volume QoS limit (50k IOPS / 1 GiB/s) so a single datastore cannot starve the array - An "environment" parameter (prod/test/dev) that is requested at deployment time and written into the workload tags for filtering and chargeback The JSON follows the conventions of the official PureStorage-OpenConnect/fusion-presets repository, including the _comment documentation style. One honest note is included in the preset itself: array-side snapshots of VMFS datastores are crash-consistent, not VM-consistent, so treat them as an extra safety net next to your backup solution. GitHub link: https://github.com/knabespecht/pure_workflows/blob/main/presets/vmware-esxi-datastores.json Feedback welcome, especially on the QoS defaults and retention values you use for similar setups.
