Introduction
Pure Storage, a leader in all-flash data storage solutions, has unveiled its next-generation FlashArray and FlashBlade platforms built specifically to address the growing demands of artificial intelligence (AI) and machine learning (ML) workloads. These enhancements deliver unprecedented performance, scalability and reliability for both structured and unstructured data environments, helping organizations accelerate AI development, improve total cost of ownership (TCO) and simplify data management.
1. Meeting the Demands of AI Workloads
AI and ML applications—ranging from training large-scale deep learning models to real-time inference—pose unique challenges for storage systems. They require massive throughput, minimal latency and the ability to handle mixed workloads of small, random I/O as well as large, sequential streams. Pure Storage’s new generation of FlashArray and FlashBlade platforms has been architected from the ground up to satisfy these rigorous requirements:
• Extreme Performance: Sub-millisecond latencies and multi-million IOPS per chassis
• High Bandwidth: Up to 400 GB/s throughput for unstructured data
• Massive Capacity: Support for multi-petabyte deployments in a single rack
• Predictable Scaling: Non-disruptive upgrades and pay-as-you-grow licensing
2. Next-Generation FlashArray: Accelerating Structured AI Data
FlashArray has long been Pure’s flagship block storage array for databases, virtual desktop infrastructure (VDI) and transactional applications. The latest iteration adds key enhancements tailored for AI:
• NVMe/TCP and NVMe over Fibre Channel (NVMe/FC) support to unlock full NVMe performance across networks
• Enhanced controller architecture with next-gen CPUs and accelerated metadata engines
• Increased drive density: up to 25 15.36 TB NVMe SSDs per chassis (384 TB raw)
• Inline data reduction—compression, deduplication and zero-detect—delivering up to 10:1 space savings
• Integrated support for orchestration platforms like Kubernetes and AI frameworks such as TensorFlow, PyTorch and MXNet
These improvements translate into dramatic speedups for AI training pipelines that ingest, preprocess and store vast quantities of structured data. FlashArray’s consistent microsecond latency and high IOPS ensure that data preprocessing and feature engineering jobs run without storage bottlenecks.
3. Next-Generation FlashBlade: Powering Unstructured AI Content
Unstructured data—files, logs, images, videos and sensor streams—forms the backbone of many AI workloads. FlashBlade, Pure’s scale-out file and object storage platform, has been refreshed as FlashBlade//S to deliver the following:
• Scalable chassis architecture supporting up to 6.4 PB raw capacity in a single rack
• 400 GB/s aggregate throughput and over 10M file operations per second
• Enhanced file system metadata performance for millions of small files
• Native S3 object support alongside parallel NFS/SMB access
• Automated data lifecycle policies to tier cold data to cloud or on-premises object tiers
FlashBlade//S empowers AI teams to train large language models (LLMs), perform image recognition at scale and run genomics pipelines without worrying about storage throughput or capacity limits.
4. Pure1 Cloud-Based Management and Analytics
Both new platforms integrate tightly with Pure1, the company’s SaaS-based storage management and monitoring service. Key Pure1 capabilities include:
• Predictive analytics powered by artificial intelligence to forecast capacity, performance bottlenecks and component failures
• Automated capacity planning and non-disruptive upgrades with proactive alerts
• Unified dashboard for all FlashArray and FlashBlade systems, including multi-cloud object tiers
• Role-based access control (RBAC) and audit trails for governance and compliance
With Pure1, IT teams gain deep visibility into workload characteristics and can optimize infrastructure investments across on-premises and cloud environments.
5. Enterprise-Grade Resiliency and Security
Given the critical nature of AI workloads and the sensitivity of training data, the new FlashArray and FlashBlade models emphasize robust data protection and security:
• Built-in ransomware protection: immutable snapshots with Pure SafeMode to prevent deletion or tampering
• End-to-end encryption: AES-256 data-at-rest and TLS-v1.3 data-in-flight encryption
• Continuous data availability: ActiveCluster synchronous replication for zero RPO across two sites
• Rapid recovery: Instantaneous restores from snapshots and simplified disaster recovery orchestration
These features ensure that AI pipelines can withstand both operational and cyber threats without extended downtime or potential data loss.
6. Simplified Consumption with Evergreen Subscription
Pure Storage’s Evergreen subscription model allows organizations to consume storage capacity and features as a service, with predictable budgeting and non-disruptive hardware and software upgrades. Key benefits include:
• Flexible term lengths (1, 3, 5 years) and predictable monthly costs
• Right-sized capacity planning with the option to scale up or down
• Continuous access to the latest hardware and software releases at no additional charge
• Simplified procurement and budgeting aligned to OPEX vs. CAPEX
This consumption-based approach aligns with many enterprises’ shift to cloud-like financial models for on-premises infrastructure.
Three Key Takeaways
1. Purpose-Built for AI: The next-gen FlashArray and FlashBlade deliver sub-millisecond latency, multi-million IOPS and hundreds of gigabytes per second of throughput, addressing the full spectrum of AI workload demands from structured data pipelines to unstructured model training.
2. Software-Driven Simplicity: Pure1 provides AI-powered predictive analytics, unified management, automated upgrades and cloud-tiering, enabling IT teams to focus on AI innovation rather than storage administration.
3. Resilient and Secure: Built-in ransomware protection, encryption, multi-site replication and immutable snapshots safeguard critical AI assets and ensure continuous pipeline availability.
Three-Question FAQ
Q1. How do Pure’s new arrays differ from the previous generation?
A1. The latest models feature upgraded controllers, higher-density NVMe SSDs, support for NVMe/TCP and NVMe/FC, expanded scale-out capacity and enhanced software capabilities such as AI-powered predictive analytics in Pure1.
Q2. Can I run both structured and unstructured AI workloads on the same platform?
A2. Pure recommends FlashArray for structured, block-based workloads (databases, analytics pipelines) and FlashBlade for unstructured, file- and object-based AI workloads (model training, large language model data lakes). Both platforms integrate via Pure1 for unified management.
Q3. What is Evergreen, and how does it benefit my AI initiatives?
A3. Evergreen is Pure Storage’s subscription-based consumption model that provides flexible capacity, continuous non-disruptive upgrades to the latest hardware and software, and predictable operational expenses—ideal for dynamic AI workloads that require frequent scaling and feature enhancements.
Conclusion
With its next-generation FlashArray and FlashBlade platforms, Pure Storage empowers enterprises to accelerate AI and ML initiatives by addressing the core storage challenges of performance, scalability, simplicity and security. By combining purpose-built hardware with AI-driven management and a flexible consumption model, organizations can deliver faster insights, improve collaboration among data science teams and drive innovation without the traditional complexities of infrastructure management.
