AI and data science are transforming industries, but managing the scale and complexity of these workloads remains a challenge. At Domino Data Lab, we’re constantly working to address these issues, and our latest development is a significant step forward: our Enterprise AI platform is now backed by Amazon FSx for NetApp ONTAP. This integration simplifies the complexities of managing data for AI workloads, particularly for IT and data teams tasked with scaling these efforts across hybrid and multi-cloud environments. It is available today for Domino Cloud customers, and can also be enabled for customers self-hosting Domino on AWS.
Seamless AI and Data Management Across Hybrid and Multi-Cloud Environments
One of the toughest problems for IT teams is managing the large data sets needed for AI development. Data typically resides across multiple locations—on-premises and in the cloud—which makes it difficult to ensure availability for data science teams when and where it's needed.
Domino’s data management capabilities make it easy for data scientists to access all of their data, wherever it may be. Our Datasets feature provides versioned and structured file storage that is managed directly in Domino. Data scientists use Datasets to build multiple curated collections of data in one project to be shared with collaborators. With Datasets now backed by Amazon FSx for NetApp ONTAP, our platform lays the foundation for seamless data movement and access, whether it's on-prem or in the cloud.
This means that data scientists and IT professionals no longer have to wrestle with infrastructure complexity. You get the flexibility and control you need for enterprise-level AI projects, while data scientists can focus on what they do best: building models and innovating without worrying about the underlying data logistics and DevOps.
Scalability and Efficiency that Meet AI’s Demands
Scaling AI initiatives requires more than just storage—data science teams need high-performance data access. With Domino’s integration with Amazon FSx for NetApp ONTAP, data science teams get the performance they need to process large data volumes quickly.
Demanding AI workloads such as computer vision and large language model training require high throughput. When operating at the scale of an AI project that runs many concurrent workloads against file storage (e.g., multiple data scientists executing jobs against common datasets), Amazon FSx for NetApp ONTAP is more cost-efficient than other storage options.
Built-In Reproducibility and Governance
Reproducibility is one of the biggest challenges in AI governance. Without it, scaling becomes risky, especially for organizations that need to comply with strict regulatory compliance standards. Reproducibility is essential, and Domino’s platform captures versions of code, data, environments, and results across the model lifecycle.
As part of this, Domino Datasets lets you create read-only snapshots of your Dataset in any moment and time. These immutable dataset snapshots not only allow you to easily share data and iterate on model training, but support broader governance and compliance initiatives along with Domino’s other comprehensive reproducibility features.
This level of built-in governance helps IT and data management teams meet stringent regulatory requirements while allowing data scientists to innovate with confidence, knowing that every step of their workflow is fully auditable.
Bridging the Gap Between IT and Data Science
One persistent issue in scaling AI is the divide between IT and data science teams. IT needs to manage data securely and efficiently, while data scientists need fast, flexible access to that data. Domino and NetApp bridge this gap by providing a unified environment that satisfies both sides. IT can manage and secure data across any infrastructure, and data scientists can access the tools and environments they need – without waiting on DevOps support.
This collaboration not only accelerates AI innovation but also helps control costs and reduces operational risk by making data management more predictable and efficient.
What’s Next?
Our work with NetApp is just getting started. The current integration with Amazon FSx for NetApp ONTAP sets the foundation for deeper integrations to come.
We’re already working on future enhancements that will give enterprises even more flexibility and scalability for managing AI and data workloads across hybrid and multi-cloud environments:
- Intelligent data mobility: Optimized data management with NetApp BlueXP and ONTAP, featuring instant snapshots from Domino and compression for streamlined storage and enhanced access.
- Optimized hybrid operations: Run AI/ML workloads across any compute cluster with Domino's single-pane-of-glass, powered by NetApp ONTAP, for AIOps-driven automation and unified, multi-cloud control.
- Seamless access: Simplify data access for developers and API users with secure, consistent management across all environments, powered by Domino’s access control and permission features.
- Trusted and secure: Achieve data and AI compliance and auditability with efficient snapshotting and immutable datasets using Domino Datasets, NetApp ONTAP Snapshot, and SnapLock.
To learn more about how Domino Data Lab and NetApp are working together to transform AI initiatives, read Domino’s press release and check out our latest resources.
