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Beyond Storage: Has NetApp Realized its Vision of Intelligent Data Infrastructure?
New AFX and AI Data Engine offerings, paired with Keystone STaaS, FlexPod AI, and deeper Azure, Google, and AWS integrations, reveal how NetApp is transforming its vision of intelligent data infrastructure into practice.
Key Highlights:
- NetApp’s latest announcements at NetApp Insight 2025 underscore its strategy to make AI a first-class workload across hybrid and multicloud environments.
- The company is extending its long-standing strengths in data management, security, and governance into the operational layers where AI pipelines are built and sustained.
- NetApp is turning its intelligent data infrastructure vision into a practical foundation for enterprise AI deployment.
The News
NetApp introduced AFX disaggregated flash systems powered by its ONTAP software and the AI Data Engine (AIDE), extending its enterprise data platform for AI workloads. Integration with NVIDIA, Cisco, and all major hyperscalers help position NetApp as a unified data foundation for operational AI. Complementary updates, including enhanced ransomware resilience, the Shift Toolkit, and Workload Factory, show continuity in NetApp’s intelligent data infrastructure roadmap. For more information, read the company press release.
Analyst Take
For years, NetApp has consistently adapted to and ridden transformational technology waves. We see no signs of it faltering in the era of AI. At NetApp Insight 2025, the company continued to execute against CEO George Kurian’s vision of disciplined innovation and client-focused leadership. The company has translated its storage expertise into a cohesive platform for data unification, privacy, and AI readiness.
AI adoption has shifted from pilot programs to business-critical deployment. Enterprises are now moving large-scale data pipelines from experimentation into production, creating new demands for consistent governance, performance, and trust across hybrid environments. This is the inflection point NetApp has anticipated. Rather than chasing models or training frameworks, the company is concentrating on the data infrastructure that enables them. That clarity of focus positions NetApp to benefit as enterprise AI spending pivots toward storage, orchestration, and data management layers.
The rise of AI factories marks a profound change in enterprise infrastructure buildout. For example, the NetApp AFX all-flash storage system provides the performance and control needed for these data-centric environments, allowing enterprises to process, catalog, and train AI workloads closer to where data resides. AI factories, as defined today, bring compute, data, and orchestration into proximity to minimize latency and preserve control. Their success depends on a unified data fabric that can classify, move, and secure information without breaking compliance chains. NetApp’s disaggregated AFX architecture and AI Data Engine provide this foundation by coupling flash performance with metadata intelligence and policy enforcement. In practical terms, AFX turns a traditional storage layer into an operational core for AI pipelines, bridging on-premise data gravity with hyperscaler scale-out.
Compared with competitors such as Dell, HPE, and Pure Storage, NetApp’s differentiation lies in its unified control plane, consistent data governance, and ability to extend these capabilities across multiple clouds. We view this level of coherence as unique in the industry.
NetApp’s deep collaboration with NVIDIA strengthens its AI credibility. The integration of the NVIDIA AI Data Platform and AI Enterprise software, combined with DGX SuperPOD certification, validates AFX performance at enterprise scale. The partnership makes NetApp a natural storage and data pipeline layer for NVIDIA-driven AI deployments.
The company’s open engagement with hyperscalers reinforces its hybrid positioning. Azure NetApp Files, Google Cloud NetApp Volumes, and AWS FSx for ONTAP each show how NetApp adapts to partner ecosystems while preserving data governance and control. This pragmatic approach helps organizations in regulated industries deploy AI securely across mixed environments.
In our view, the operational value for customers is clear: simplified AI data pipelines, built-in compliance, and reduced duplication of data. These efficiencies can benefit end-user customers with faster access to usable AI insights and lower infrastructure overhead. With this foundation, NetApp believes it is not just unifying data and preparing for AI workloads, but helping bring meaning and insights to that data. We acknowledge the clarity and scale of NetApp’s vision, with constant maturation and consistent execution.
That said, execution risks remain. Scaling AIDE adoption and ensuring seamless integration with partner ecosystems will require continued focus. NetApp’s disciplined culture and track record in managing technology transitions suggest it is well-positioned to deliver.
What Was Announced
NetApp announced numerous product and solution updates as part of its intelligent data infrastructure strategy. The centerpiece of the launch was AFX and AIDE, designed to simplify and secure enterprise-scale AI pipelines while maintaining the proven data protection and resilience of ONTAP.
AFX: NetApp AFX is a disaggregated all-flash platform that separates performance from capacity to achieve linear scalability and predictable throughput. Powered by ONTAP, it includes a global metadata catalog for real-time data visibility and integrates with DX50 compute nodes for high-performance metadata services. AFX is positioned as a data foundation for AI factories, enabling compute and governance to operate near enterprise data while linking to public cloud resources at scale.
AIDE: The NetApp AI Data Engine provides an end-to-end service for ingesting, curating, and preparing data for AI applications. Built with NVIDIA AI Enterprise software and accelerated computing, AIDE automates metadata discovery, data vectorization, and privacy enforcement through policy-based guardrails. Its unified control plane allows enterprises to manage their AI data lifecycle without creating redundant copies or losing compliance visibility.
Keystone STaaS for Enterprise AI: Customers can now access AFX and AIDE through a subscription-based model that delivers consumption-based scalability. The service provides the flexibility of cloud consumption with the assurance of on-premises control.
FlexPod AI with Cisco: The new FlexPod AI solution integrates AFX with Cisco UCS and Nexus platforms. It delivers a validated architecture for hybrid AI workloads that aligns with Cisco’s Secure AI framework, combining storage, compute, and networking in a single, secure configuration.
Cloud Integrations: NetApp extended native AI capabilities across Azure, Google Cloud, and AWS. Customers can now apply AI models directly to ONTAP data without replication. Azure NetApp Files now supports Object API access, Google Cloud NetApp Volumes integrates directly with Google AI applications, and AWS FSx for ONTAP supports Amazon Elastic VMware Service for hybrid workload mobility.
Additional Portfolio Updates: NetApp also enhanced its ransomware resilience capabilities with new breach detection and isolated recovery features, expanded its Shift Toolkit for hypervisor migration, and released ONTAP 9.18.1, the new NetApp Console, and Workload Factory. Together, these reinforce NetApp’s ongoing modernization of its data services portfolio.
Looking Ahead
NetApp is now moving beyond data management toward orchestrating data and knowledge pipelines across AI factories and hybrid environments. For enterprises, unified data governance and hybrid interoperability should now be viewed as prerequisites for AI at scale. In our view, NetApp’s combination of AFX, AIDE, and hyperscaler partnerships offers a practical model for organizations that must balance performance with trust. With these announcements, we examine how far along NetApp is on its quest to deliver intelligent data infrastructure.
For NetApp, the opportunity is to extend its AI factory vision through deeper partnerships with NVIDIA, Cisco, and system integrators, and to highlight sustainability advantages derived from flash efficiency and data consolidation.
AFX and AIDE mark a pivotal point in NetApp’s transformation into a foundational AI infrastructure provider. The company’s consistent execution of its core strategy to unify, secure, and accelerate enterprise data positions it well for AI-driven enterprise growth.
We believe the next phase of NetApp’s evolution will center on deepening metadata intelligence, automating AI data pipelines, and improving sustainability across flash and hybrid environments. By embedding data cataloging and governance directly into its control plane, NetApp can close the operational gap between data creation and AI consumption, similar to the way hybrid infrastructure bridges public cloud and on-premises worlds. Furthermore, the company’s openness to ecosystem partners such as NVIDIA, Cisco, and the hyperscalers embodies the “quiet confidence” Kurian emphasizes, advancing innovation through collaboration rather than isolation. As enterprise AI matures, efficiency, trust, and adaptability will define the winners.
We believe NetApp’s ability to unify these qualities under one consistent data architecture gives it a fresh and influential position in shaping the infrastructure layer of an AI-driven future.
Don Gentile | Analyst-in-Residence -- Storage & Data Resiliency
Don Gentile brings three decades of experience turning complex enterprise technologies into clear, differentiated narratives that drive competitive relevance and market leadership. He has helped shape iconic infrastructure platforms including IBM z16 and z17 mainframes, HPE ProLiant servers, and HPE GreenLake — guiding strategies that connect technology innovation with customer needs and fast-moving market dynamics.
His current focus spans flash storage, storage area networking, hyperconverged infrastructure (HCI), software-defined storage (SDS), hybrid cloud storage, Ceph/open source, cyber resiliency, and emerging models for integrating AI workloads across storage and compute. By applying deep knowledge of infrastructure technologies with proven skills in positioning, content strategy, and thought leadership, Don helps vendors sharpen their story, differentiate their offerings, and achieve stronger competitive standing across business, media, and technical audiences.
Steven Dickens | CEO HyperFRAME Research
Regarded as a luminary at the intersection of technology and business transformation, Steven Dickens is the CEO and Principal Analyst at HyperFRAME Research.
Ranked consistently among the Top 10 Analysts by AR Insights and a contributor to Forbes, Steven's expert perspectives are sought after by tier one media outlets such as The Wall Street Journal and CNBC, and he is a regular on TV networks including the Schwab Network and Bloomberg.