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NetApp Extends ONTAP Data into AWS AI and ML Workflows through Native S3 Access
AWS/NetApp partnership brings enterprise file data directly into AI and analytics pipelines
12/04/2025
Key Highlights:
- NetApp and AWS introduced native S3 API access for FSx for ONTAP data, enabling AI, ML, and analytics services to directly consume ONTAP-managed file data in the cloud or on premises.
- The update removes the need to duplicate or re-ingest enterprise file datasets into separate object stores, reducing operational friction and data sprawl.
- FSx for ONTAP continues to mature as a fully managed, enterprise-grade service on AWS, reinforcing the depth of the collaboration between the two companies.
- Enterprises gain a more flexible way to operationalize AI on existing data while preserving governance, protection, and performance characteristics.
The News
NetApp announced that Amazon FSx for NetApp ONTAP now provides native S3 API access to ONTAP-managed file data through Amazon S3 Access Points. This allows applications on AWS to treat file-based datasets as if they were stored in S3 object storage without requiring migration or duplication. The capability is positioned for AI, ML, analytics, and data processing services that rely on S3-compatible interfaces. The integration applies to both cloud-native FSx for ONTAP deployments and on-premises systems used in hybrid architectures. For more information, read the NetApp press release.
What Was Announced
With Amazon S3 Access Points for FSx for ONTAP, organizations can use S3-based AWS services and ISV applications with ONTAP file systems as if the data were stored in S3 buckets. Applications can issue S3 API calls directly against ONTAP-managed datasets, allowing the data to participate in object-centric workflows even though it continues to reside in the file system. This removes the need to duplicate or migrate file data into separate object stores.
ONTAP’s native replication capabilities also allow data to move easily between on-premises systems and FSx for ONTAP, supporting hybrid environments while maintaining consistent protection and governance. Teams can create named, permission-scoped S3 Access Points to control how different users or applications interact with the data. As a result, file datasets stored on FSx for ONTAP become directly usable by the broad range of AI, ML, analytics, and serverless services that rely on S3 access patterns.
This capability builds on the broader FSx for ONTAP service, which provides multi-protocol access, enterprise data services such as snapshots, clones, replication, compression, and deduplication, independent scaling of storage and throughput, high-performance SSD tiers with sub-millisecond latency, automated lifecycle management, and hybrid-cloud mobility through NetApp SnapMirror.
These features allow FSx for ONTAP to support mission-critical workloads across enterprise applications, databases, containers, and virtualized environments. The addition of S3 access extends the service into analytics and AI-driven patterns that historically required S3-native object stores. Instead of creating parallel data lakes or migrating archives into separate object tiers, organizations can unify access models and simplify their pipelines.
Looking Ahead
This update has the potential to influence how enterprises prepare their datasets for AI and analytics. Many organizations have carefully structured their ONTAP environments over the years, and extending those same datasets into S3 workflows without relocation or reformatting will help reduce the operational friction that often slows down AI adoption. As AI becomes part of mainstream business processes, the ability to use operational file data directly in training, retrieval, and analytics workflows will become increasingly valuable.
I expect early movement in environments where teams have been reluctant to create duplicate object repositories or build parallel data lakes simply to satisfy S3 interface requirements. Treating ONTAP datasets as both file-native and S3-addressable allows data engineering teams to adopt modern analytics and transformation patterns without separating storage from established governance and protection practices.
There is also a positive implication for cyber resiliency strategies. ONTAP’s data services can now support upstream AI and analytics workflows without creating unmanaged object copies. This keeps protection, lineage, and recovery consistent even as organizations expand into more compute-intensive workloads.
Looking ahead, I will be listening to how customers describe the role of FSx for ONTAP in new analytics and AI architectures. Positive signs to watch for include adoption of ONTAP-backed S3 paths in modern data pipelines, references to reduced data movement or simplified preparation steps, and deeper integration points with AWS native AI and ML services. If these patterns emerge, it will indicate that the integration is influencing real architectural decisions rather than operating as a convenience layer.
In my opinion, this announcement moves the AWS and NetApp partnership further along a strategic path. It reinforces the idea that enterprises can bring AI to their data rather than restructure their storage to suit AI. A unified file and object access layer, delivered as a managed cloud service, provides a practical and adaptable foundation for the next phase of AI-driven architectures.
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.