Pure Storage Supercharges AI-Ready Enterprise Cloud
At Pure//Accelerate 2025, Pure Storage (NYSE: PSTG) unveiled a sweeping upgrade to its Enterprise Data Cloud platform, aiming to make AI adoption smoother for hybrid and cloud-first enterprises. The latest enhancements promise to unify data management, accelerate AI workloads, and extend cloud-native capabilities—all while keeping operations secure and efficient.
“Access to data is everything in today’s AI era,” said Rob Lee, Pure Storage CTO. “Managing your data, not just storing it, is the foundation for AI readiness—across cloud, core, and edge.”
The platform updates touch three critical areas: hybrid cloud integration, intelligent data control, and AI workload performance.
Hybrid Cloud Gets Smarter with Azure Native
Hybrid cloud adoption often hits a roadblock when migrating data-heavy workloads like VMware to public clouds. Pure Storage’s answer: Pure Storage Cloud Azure Native, now generally available. Built for Azure VMware Solution, this fully managed service allows enterprises to decouple storage from compute, migrate workloads without refactoring, and access cloud AI tools seamlessly.
“Moving storage-intensive VMware workloads to Azure has been a headache for many organizations,” said Aung Oo, VP of Azure Storage. “Partnering with Pure Storage makes it far easier to leverage Azure’s AI and analytics capabilities.”
The update reinforces Pure’s strategy to unify data mobility across on-premises and cloud environments, a key differentiator as rivals like NetApp and Dell Technologies push their hybrid storage solutions.
Intelligent Data Control with Portworx and Pure Fusion
Data chaos is a killer for AI projects. To address this, Pure Storage expanded its Portworx integration with Pure Fusion, enabling enterprises to manage both traditional and modern containerized workloads on a single platform. The integration supports Kubernetes, KubeVirt VMs, and hybrid deployments, giving IT teams a unified view of all data assets.
Meanwhile, the Pure1 AI Copilot platform now extends to Portworx, allowing administrators to query clusters conversationally, monitor Kubernetes at scale, and troubleshoot via natural language—making AI-powered platform management accessible to non-experts.
Faster, Leaner AI Inference
AI operations are notoriously resource-hungry. Pure Storage introduced the Key Value Accelerator, now integrating with NVIDIA Dynamo, designed to speed up AI inference across multi-GPU environments. The goal: lower latency, reduce compute overhead, and even trim carbon footprints.
“Efficient AI inference depends on instant data access,” said Dion Harris, NVIDIA director for HPC and AI Infrastructure. “This integration delivers faster, more scalable AI performance straight out of the box.”
Additional performance boosts come from Purity Deep Reduce, a next-gen data reduction engine using pattern recognition and similarity-based reduction to maximize storage efficiency without sacrificing speed.
Next-Gen FlashArray Updates
Pure Storage continues to expand its FlashArray portfolio for latency-sensitive and high-throughput workloads:
- FlashArray//XL 190 – GA Q4 FY26
- FlashArray//X R5 – GA now
- FlashArray//C R5 – GA now
This architecture allows organizations to run enterprise apps and AI/ML pipelines on the same scalable foundation, simplifying IT operations while ensuring performance.
Why It Matters
The latest Pure Storage updates reinforce its position in the high-end hybrid cloud market. By combining unified data management, AI-driven control, and accelerated inference, the company is helping enterprises overcome key barriers to AI adoption—especially the complexity of managing data across on-prem, cloud, and containerized workloads.
As AI becomes table stakes for competitive business intelligence, solutions that reduce migration headaches, automate data governance, and accelerate inference will increasingly define leaders in the storage space. Pure Storage appears ready to play that role.
Pure Storage Supercharges AI-Ready Enterprise Cloud
At Pure//Accelerate 2025, Pure Storage (NYSE: PSTG) unveiled a sweeping upgrade to its Enterprise Data Cloud platform, aiming to make AI adoption smoother for hybrid and cloud-first enterprises. The latest enhancements promise to unify data management, accelerate AI workloads, and extend cloud-native capabilities—all while keeping operations secure and efficient.
“Access to data is everything in today’s AI era,” said Rob Lee, Pure Storage CTO. “Managing your data, not just storing it, is the foundation for AI readiness—across cloud, core, and edge.”
The platform updates touch three critical areas: hybrid cloud integration, intelligent data control, and AI workload performance.
Hybrid Cloud Gets Smarter with Azure Native
Hybrid cloud adoption often hits a roadblock when migrating data-heavy workloads like VMware to public clouds. Pure Storage’s answer: Pure Storage Cloud Azure Native, now generally available. Built for Azure VMware Solution, this fully managed service allows enterprises to decouple storage from compute, migrate workloads without refactoring, and access cloud AI tools seamlessly.
“Moving storage-intensive VMware workloads to Azure has been a headache for many organizations,” said Aung Oo, VP of Azure Storage. “Partnering with Pure Storage makes it far easier to leverage Azure’s AI and analytics capabilities.”
The update reinforces Pure’s strategy to unify data mobility across on-premises and cloud environments, a key differentiator as rivals like NetApp and Dell Technologies push their hybrid storage solutions.
Intelligent Data Control with Portworx and Pure Fusion
Data chaos is a killer for AI projects. To address this, Pure Storage expanded its Portworx integration with Pure Fusion, enabling enterprises to manage both traditional and modern containerized workloads on a single platform. The integration supports Kubernetes, KubeVirt VMs, and hybrid deployments, giving IT teams a unified view of all data assets.
Meanwhile, the Pure1 AI Copilot platform now extends to Portworx, allowing administrators to query clusters conversationally, monitor Kubernetes at scale, and troubleshoot via natural language—making AI-powered platform management accessible to non-experts.
Faster, Leaner AI Inference
AI operations are notoriously resource-hungry. Pure Storage introduced the Key Value Accelerator, now integrating with NVIDIA Dynamo, designed to speed up AI inference across multi-GPU environments. The goal: lower latency, reduce compute overhead, and even trim carbon footprints.
“Efficient AI inference depends on instant data access,” said Dion Harris, NVIDIA director for HPC and AI Infrastructure. “This integration delivers faster, more scalable AI performance straight out of the box.”
Additional performance boosts come from Purity Deep Reduce, a next-gen data reduction engine using pattern recognition and similarity-based reduction to maximize storage efficiency without sacrificing speed.
Next-Gen FlashArray Updates
Pure Storage continues to expand its FlashArray portfolio for latency-sensitive and high-throughput workloads:
- FlashArray//XL 190 – GA Q4 FY26
- FlashArray//X R5 – GA now
- FlashArray//C R5 – GA now
This architecture allows organizations to run enterprise apps and AI/ML pipelines on the same scalable foundation, simplifying IT operations while ensuring performance.
Why It Matters
The latest Pure Storage updates reinforce its position in the high-end hybrid cloud market. By combining unified data management, AI-driven control, and accelerated inference, the company is helping enterprises overcome key barriers to AI adoption—especially the complexity of managing data across on-prem, cloud, and containerized workloads.
As AI becomes table stakes for competitive business intelligence, solutions that reduce migration headaches, automate data governance, and accelerate inference will increasingly define leaders in the storage space. Pure Storage appears ready to play that role.
Pure Storage Supercharges AI-Ready Enterprise Cloud
At Pure//Accelerate 2025, Pure Storage (NYSE: PSTG) unveiled a sweeping upgrade to its Enterprise Data Cloud platform, aiming to make AI adoption smoother for hybrid and cloud-first enterprises. The latest enhancements promise to unify data management, accelerate AI workloads, and extend cloud-native capabilities—all while keeping operations secure and efficient.
“Access to data is everything in today’s AI era,” said Rob Lee, Pure Storage CTO. “Managing your data, not just storing it, is the foundation for AI readiness—across cloud, core, and edge.”
The platform updates touch three critical areas: hybrid cloud integration, intelligent data control, and AI workload performance.
Hybrid Cloud Gets Smarter with Azure Native
Hybrid cloud adoption often hits a roadblock when migrating data-heavy workloads like VMware to public clouds. Pure Storage’s answer: Pure Storage Cloud Azure Native, now generally available. Built for Azure VMware Solution, this fully managed service allows enterprises to decouple storage from compute, migrate workloads without refactoring, and access cloud AI tools seamlessly.
“Moving storage-intensive VMware workloads to Azure has been a headache for many organizations,” said Aung Oo, VP of Azure Storage. “Partnering with Pure Storage makes it far easier to leverage Azure’s AI and analytics capabilities.”
The update reinforces Pure’s strategy to unify data mobility across on-premises and cloud environments, a key differentiator as rivals like NetApp and Dell Technologies push their hybrid storage solutions.
Intelligent Data Control with Portworx and Pure Fusion
Data chaos is a killer for AI projects. To address this, Pure Storage expanded its Portworx integration with Pure Fusion, enabling enterprises to manage both traditional and modern containerized workloads on a single platform. The integration supports Kubernetes, KubeVirt VMs, and hybrid deployments, giving IT teams a unified view of all data assets.
Meanwhile, the Pure1 AI Copilot platform now extends to Portworx, allowing administrators to query clusters conversationally, monitor Kubernetes at scale, and troubleshoot via natural language—making AI-powered platform management accessible to non-experts.
Faster, Leaner AI Inference
AI operations are notoriously resource-hungry. Pure Storage introduced the Key Value Accelerator, now integrating with NVIDIA Dynamo, designed to speed up AI inference across multi-GPU environments. The goal: lower latency, reduce compute overhead, and even trim carbon footprints.
“Efficient AI inference depends on instant data access,” said Dion Harris, NVIDIA director for HPC and AI Infrastructure. “This integration delivers faster, more scalable AI performance straight out of the box.”
Additional performance boosts come from Purity Deep Reduce, a next-gen data reduction engine using pattern recognition and similarity-based reduction to maximize storage efficiency without sacrificing speed.
Next-Gen FlashArray Updates
Pure Storage continues to expand its FlashArray portfolio for latency-sensitive and high-throughput workloads:
- FlashArray//XL 190 – GA Q4 FY26
- FlashArray//X R5 – GA now
- FlashArray//C R5 – GA now
This architecture allows organizations to run enterprise apps and AI/ML pipelines on the same scalable foundation, simplifying IT operations while ensuring performance.
Why It Matters
The latest Pure Storage updates reinforce its position in the high-end hybrid cloud market. By combining unified data management, AI-driven control, and accelerated inference, the company is helping enterprises overcome key barriers to AI adoption—especially the complexity of managing data across on-prem, cloud, and containerized workloads.
As AI becomes table stakes for competitive business intelligence, solutions that reduce migration headaches, automate data governance, and accelerate inference will increasingly define leaders in the storage space. Pure Storage appears ready to play that role.
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