Ask Us Everything: Everpure Object — What You Need to Know
Why Object Exists (and Why It’s Different) Justin opened with a reset that resonated: file and object may both store unstructured data, but they are built on different assumptions. File storage evolved from human workflows — folders, directories, locking semantics, POSIX guarantees. That model works well for users and shared drives. But those same assumptions become friction at cloud scale. Object storage was built for machines. It uses a flat namespace, atomic operations, embedded metadata, and native versioning. That’s why modern applications — backup platforms, analytics engines, AI frameworks — increasingly request S3 buckets instead of file shares. It’s not that file storage is going away; it’s that machines prefer object. Scale: 3.8 Trillion Objects and Counting One of the standout moments was a validation that Everpure ran for a customer, which tested 3.8 trillion objects in a single bucket on FlashBlade. They didn’t stop because they hit a ceiling — they stopped because they ran out of time. That matters because unlimited scaling isn’t guaranteed in most on-prem object systems. Many legacy solutions quietly impose metadata or bucket limits that don’t surface until you’re deep into production. If your roadmap includes AI datasets, large backup repositories, analytics pipelines, or content delivery use cases, scale limits quickly become real-world constraints. Object for AI: Performance Has Changed the Conversation Using object for AI dominated the Q&A — and for good reason. Training workloads demand enormous throughput, especially for checkpointing bursts across large GPU clusters. Inference workloads are more latency-sensitive and read-heavy. FlashBlade’s architecture, including S3 over RDMA, separates metadata authentication from the data path and enables direct, high-throughput access to data nodes. The team referenced performance in the hundreds of GB/sec range on multi-chassis systems. Justin made an important observation: AI initially landed on file systems simply because object storage wasn’t considered performant enough. That assumption is changing rapidly. Object on FlashArray: The “Alongside Block” Story A lot of questions focused on object running on FlashArray — resiliency, performance expectations, and which workloads are a fit. Writes are acknowledged only after safe persistence, and standard object retry logic handles failure scenarios cleanly. So, you can be sure of data integrity, even if a controller fails. FlashArray Object is designed for smaller-scale S3 use cases: artifact repositories, container workloads, image stores, edge environments, and test/dev scenarios. FlashBlade remains the scale-out platform for massive object footprints. Over time, Everpure Fusion will increasingly abstract placement decisions so workloads land on the right platform without adding operational complexity. Data Reduction and Garbage Collection: The Hidden Advantages One of the more practical differentiators discussed was garbage collection. Many legacy object systems struggle with delete churn because of layered indirection — objects are marked, then nodes are marked, then underlying file systems are marked, then media eventually reclaims space. Because Everpure controls the stack end-to-end — logical object through physical media — reclamation is cohesive and efficient. Combined with always-on compression and similarity-based DeepReduce techniques, customers see meaningful space savings without sacrificing performance. Migration: It’s an Application Decision Perhaps the most important takeaway: moving from file to object isn’t a storage copy exercise. It’s an application transition. Backup software, artifact repositories, and analytics platforms increasingly support object natively. Let the application drive the migration instead of trying to brute-force a file-to-object copy. Object is growing quickly, but the shift doesn’t require abandoning everything at once. With FlashArray for edge and unified workloads, FlashBlade for scale-out performance, and Everpure Fusion tying it together, we are building a platform where object can grow naturally alongside block — not replace it overnight. If you have follow-up questions, bring them into the Pure Community. The conversation around object is only getting bigger.
New IDC Research: Building Data Infrastructure for AI
March 5 | Register now! What's behind AI agents that are fast, safe, and reliable? It starts with smarter data infrastructure. Pure Storage and IDC have been studying what separates organizations that are pulling ahead in AI from those that are stalling. Join us to see the research, hear what's changing, and rethink your data strategy to get ready for AI. In this webinar, we’ll share: Drivers of AI performance today New IDC research on how leaders are building for AI What separates fast-movers from the rest A preview of where Pure Storage and IDC see the market heading Register Now!Ask Us Everything about Object Storage
💬 Get ready for our February 2026 edition of Ask Us Everything, this Friday, February 20th at 9 AM Pacific. This month is all about Object Storage. If you have a burning question, feel free to ask it here early and we'll add it to the list to answer tomorrow. Or if we can't get it answered live, our Pure Storage experts can follow up here. Karthik Srinivasan, Flashman & 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 this self-serve resource: Object Storage Webinar EDIT: Thanks for joining in! If you have additional burning questions and comments, leave them in the comments below for the team!The Foundations of Cyber Resilience: Visibility and Indelibility
February 24 | Register now! Ransomware and operational risk haven’t gone away, yet many organizations still overlook the fundamentals that provide the strongest protection. In this back-to-basics webinar, we’ll break down how Pure Storage SafeMode™ Snapshots and Pure1® security assessments work together to form a resilient last line of defense for your data. In this live demonstration, you’ll see how they protect data integrity, accelerate recovery, and simplify security operations. Key takeaways: How immutable SafeMode Snapshots protect data from ransomware and insider threats Best practices for snapshot policies that balance recovery speed and operational efficiency What “secure by default” looks like when these features work together in real environments Register Now!
Simplifying Observability: Native OpenTelemetry in Purity
As enterprises modernize and accelerate their infrastructure through automation, blind spots become more expensive. When systems move faster, teams need telemetry that’s reliable, portable, and easy to integrate across a heterogeneous stack. Pure Storage’s Enterprise Data Cloud vision reflects that shift: infrastructure that delivers cloud-like simplicity and speed while preserving the control, security, and performance enterprises expect. Fusion supports this by standardizing and scaling self-service workflows, turning storage into an on-demand platform. But faster operations require a stronger feedback loop. As automation increases, teams need confidence that systems remain healthy and predictable. That’s why consolidated observability is foundational. Instead of running separate monitoring tools per layer, organizations are centralizing telemetry into a single observability platform that can correlate signals end-to-end; from the end user’s experience (e.g. browser or mobile app), through the network and application code, all the way down to infrastructure like servers, databases, containers, and storage. This consolidation reduces redundant tools and fragmented dashboards while giving teams the correlated insights they need to resolve incidents faster and make better decisions. The Siloed Vendor Problem Yet achieving this unified vision has proven challenging. Traditional infrastructure vendors have long provided proprietary monitoring tools designed exclusively for their own products. A storage vendor offers one monitoring interface, the compute vendor another, and the network vendor yet another. Each tool uses different data formats, separate dashboards, and incompatible alerting mechanisms. For organizations running heterogeneous environments (which is nearly all of them), this creates an untenable situation. IT teams must context-switch between multiple tools, correlate data manually across platforms, and maintain expertise in numerous vendor-specific interfaces. When an application performance issue arises, determining whether the root cause lies in storage latency, network congestion, or compute resource exhaustion becomes an exercise in detective work across disconnected systems. The promise of consolidated observability cannot be realized with vendor-specific, siloed monitoring tools. A different approach is needed. The Open Standard Solution This challenge has driven the industry toward open, vendor-agnostic standards that enable telemetry interoperability. OpenMetrics emerged as one such standard, providing a common data model for exposing metrics (counters, gauges, and histograms) in a format that any observability platform can consume. By standardizing metric exposition, OpenMetrics reduced vendor lock-in and became foundational to Prometheus-based monitoring at scale. However, standardizing the format of metrics is only one part of what organizations need to make consolidated observability work in practice. Enterprises also need consistency in how telemetry is named, described, transported, and exported, so that infrastructure data can flow cleanly across heterogeneous environments without bespoke integrations. Enter OpenTelemetry, which expands on the same vendor-neutral principles to create a comprehensive observability framework. In other words, it helps ensure telemetry isn’t just emitted in a readable format, but is also structured and delivered in a way that remains portable across vendors and backends. Think of it as establishing the equivalent of a USB standard for telemetry data: any "device" (an application or infrastructure component) can plug into any "peripheral" (an observability platform) without requiring proprietary connectors. The primary benefit is profound: freedom from vendor lock-in. Organizations can choose best-of-breed observability platforms based on capabilities and cost rather than being constrained by what their infrastructure vendors support. The External Agent Bottleneck OpenTelemetry and OpenMetrics have made consolidated observability technically feasible, but most storage vendors have adopted these standards through what can only be described as a "bolt-on" approach. This forces customers to manage a complex chain of external agents, sidecars, or dedicated VMs, just to get telemetry from their platforms visualized onto their dashboards. This presents a problem that’s two-fold: Operational Overhead: Instead of simply consuming data, IT teams are burdened with sizing, patching, and troubleshooting the monitoring infrastructure itself. New Failure Modes: If an agent crashes or becomes misconfigured, visibility into critical infrastructure disappears precisely when it's needed most. Teams find themselves monitoring their monitoring infrastructure; a meta-problem that defeats the original purpose. The Native Integration Imperative In the Pure Storage platform, observability is a first-class capability instead of an afterthought. Thus, Pure Storage has taken a different path: an OpenTelemetry collector embedded into Purity OS. Instead of asking customers to deploy and maintain external agents, exporters, or intermediary infrastructure, Pure Storage platforms will now expose telemetry in standardized OpenTelemetry format as an intrinsic platform capability. The result is sending storage telemetry directly into any OpenTelemetry-compatible Observability platform-of-choice (eg., Datadog, Dynatrace, Splunk, Grafana, etc.). Fig. Numbers represent the sequence of steps in the workflow Pure Storage’s commitment has always been simplicity. Native OpenTelemetry in Purity OS extends that principle to observability: less integration friction, fewer moving parts, and more time spent acting on insight instead of maintaining the pipeline. More information on the native integration of OpenTelemetry Collector within Purity//FB can be found here. Purity//FA to follow soon.FlashBlade & SQL Server: Enterprise Scale Rapid Recovery
February 19 | Register now! SQL Server estates are continually growing, and traditional backup targets often become the primary bottleneck in failing to meet aggressive recovery time objectives. Stop managing backups and start orchestrating them. Explore how Pure Storage FlashBlade®, as part of the Enterprise Data Cloud, overcomes constraints through a scale-out architecture for rapid backup and recovery throughput. We will share baseline performance data, including restore speeds exceeding 100 TB/hr, and provide practical guidance on integrating FlashBlade with native T-SQL backup using SMB and S3 protocols. Key Takeaways: Operational simplicity: Uses policy templates to eliminate manual configuration and human error. Flexible multi-protocol integration: Advantages of using both SMB and S3-compatible object storage as native backup targets, including the use of multiple Virtual Interfaces (VIFs) to maximize throughput. Optimized performance tuning: Gain insights from real-world validation data on how to balance host CPU usage and compression (using ZSTD) to achieve the most efficient backup and restore windows for your environment. Register Now!Ask Us Everything: Evergreen//One™ Edition — What the Community Learned
A recent Ask Us Everything (AUE) session on Pure Storage Evergreen//One™ was a lively, deeply technical conversation—and exactly the kind of dialogue that makes the Pure Community special. Here are some of the biggest takeaways, organized around the questions asked and the insights that followed.We are just one week away PUG#3
January 28th, the Cincinnati Pure User Group will be convening at Ace's Pickleball to discuss Enterprise file. We will be joined by Matt Niederhelman Unstructured Data Field Solutions Architect to help guide conversation and answer questions about what he is experiencing amongst other customers. Click the link below to register and come join us. Help us guide the conversation with your ideas for future topics. https://info.purestorage.com/2025-Q4AMS-COMREPLTFSCincinnatiPUG-LP_01---Registration-Page.html
