ONTAP AI
A family of validated designs combining NVIDIA accelerated compute and NetApp storage. The goal is predictable deployment, high-throughput data access, and ONTAP data services across training and inference pipelines.
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The practical map of NetApp’s AI data infrastructure: what each offering does, where ONTAP fits in the pipeline, and what has changed recently.
AI offerings
NetApp AIPod
Prevalidated AI infrastructure offered with NVIDIA DGX systems and partner compute, including Lenovo. It is designed to start at a practical footprint and grow without redesigning the data layer.
BlueXP / NetApp Console
NetApp’s hybrid-cloud control plane for discovering, governing, protecting, and moving data. Product naming has shifted from BlueXP toward NetApp Console; workload services help provision cloud data foundations used by AI/ML applications.
ONTAP for AI/ML
NFS, SMB, S3, NVMe/TCP and NVMe/FC access can place training sets, checkpoints, feature data, and application data on one governed platform, with snapshots, clones, replication, tiering, and multiprotocol workflows.
NetApp + NVIDIA
The partnership spans DGX-validated storage, AIPod reference designs, NVIDIA AI Data Platform integration, NeMo Retriever and NIM services, and architectures for RAG, agentic AI, training, and inference.
AI-ready AFF, FAS & AFX
AFF targets performance-sensitive pipelines; capacity-oriented flash and FAS can retain large data estates economically. The newer disaggregated AFX architecture and AI Data Engine focus on exabyte-scale, AI-ready data activation.
Intelligent Data Infrastructure
NetApp’s umbrella strategy connects storage, data services, governance, observability, cyber resilience, and workload operations so enterprise data can be prepared and reused across hybrid-cloud AI workflows.
Start with the I/O profile Training ingest, checkpoint writes, RAG retrieval, and real-time inference stress storage differently. Validate throughput, latency, metadata rate, network design, data governance, and recovery objectives against the actual pipeline.
AI news
Current official announcements, checked 23 August 2026.
SAP, Progress and NetApp race for the AI data layer
Inference spending hits an estimated $23.3B; vendors compete to own the enterprise AI data layer, validating NetApp's AFX + AI Data Engine strategy.
Goldman Sachs names NetApp a top hardware pick on AI boom
Analysts flag Dell, HPE, and NetApp as leading enterprise-hardware plays on accelerating AI infrastructure demand.
NetApp acquires DataPelago
NetApp plans to bring GPU-accelerated, zero-copy data processing closer to the storage layer, aiming to reduce AI data preparation bottlenecks.
NetApp and SK Telecom target enterprise AI
The companies are collaborating on scalable AI data infrastructure and operational models for South Korean enterprises.
Support for AI workloads at massive scale
NetApp expanded its AI infrastructure story around large-scale data estates, high-performance access, and integrated management.
NetApp and Cisco accelerate and secure AI
The expanded collaboration combines data infrastructure and networking to simplify secure enterprise AI deployments.
Enterprise-grade data platform for AI
NetApp introduced AFX, disaggregated ONTAP on AFX 1K, and AI Data Engine integration with the NVIDIA AI Data Platform.
AIPod adopts NVIDIA AI Data Platform design
The reference design connects ONTAP data management with NVIDIA accelerated computing for governed RAG and agentic-AI pipelines.
Community discussions
VAST vs Weka, NetApp and Pure for AI
Practitioner discussion of architecture, network requirements, training I/O, inference, and vendor trade-offs.
Centralized storage for AI/ML
A requirements-first discussion covering mixed datasets, databases, containers, scale-out choices, and AFF sizing.
Storage administration in the AI era
Operators discuss which judgment, governance, and hands-on responsibilities remain even as automation improves.
ONTAP MCP goes GA
A community topic on connecting AI agents to ONTAP operations across NAS, SAN, and NVMe-oF.
Optimizing AI I/O with ONTAP
Performance-oriented guidance for keeping GPUs fed and matching data access to AI pipeline behavior.
GenAI with FSx for ONTAP and S3 access points
A cloud workflow discussion connecting enterprise file data to S3-based GenAI and analytics tools.
Read-only pointers Community links are included for operational perspective, not endorsement. Validate product claims and supported configurations in current NetApp and partner documentation.