Seven strategy considerations for future-proofing AI-era data storage with Dell PowerScale

TL;DR

• To perform optimally, AI systems require sustained, high-speed current access to very large volumes of data
• Scale-out platforms such as Dell PowerScale allow extensive expansion with minimal disruption
• High-performance and archival nodes can be combined in a cluster to tailor storage provision as needed
• Dell OneFS presents a unified namespace, enabling multiple AI stages and workflows to work on a single stored dataset
• Integration with cloud environments provides flexibility for local and remote AI deployments
• Access controls and cyber-resilience capabilities are on hand to protect sensitive information
• PowerScale’s automatic placement and data tiering capabilities help businesses maximise performance without wasteful over-provisioning

As the use of AI increases, businesses need to manage fast-growing volumes of unstructured data. IDC’s Data Age 2025 report estimates that data used by “cognitive systems” is expanding by a factor of 100 year on year.

To handle such explosive growth, businesses need new storage strategies. Designed for the needs of the AI era, Dell PowerScale provides huge scope for expansion via a scale-out architecture, with the OneFS operating system offering strong security and unified data access within a single namespace. Support for mixed nodes and automated management features help AI infrastructure to operate without performance bottlenecks.

1. How can you optimise storage for maximum AI performance?

To optimise storage for maximum AI performance, systems must deliver continuous high-speed throughput, to keep parallel processing architectures supplied with data.

When multiple GPUs are processing large datasets, traditional file-server architectures may struggle to sustain throughput, particularly when handling metadata or large volumes of small files. As Nvidia has cautioned, “when considering end-to-end application performance, fast GPUs are increasingly starved by slow I/O”.

A scale-out architecture such as Dell PowerScale can help maintain a consistent flow of data, improving performance and overall utilisation of AI hardware.

2. Scaling storage to keep pace with unstructured data growth

To keep pace with unstructured data growth, scale-out architectures can expand to extremely high capacities, and allow for new nodes to be added with no planned downtime. Dell PowerScale supports incremental expansion with minimal administrative overhead and a single namespace, so businesses don’t need to worry about hitting limits as with scale-up platforms.

3. A storage strategy that adapts to changing hardware and cost dynamics

To adapt to changing hardware and cost dynamics, organisations need a flexible storage architecture that can evolve over time.

Dell PowerScale nodes can accommodate both high-performance flash storage nodes and cost-effective mechanical drives within a cluster. As AI demand drives fluctuations in flash pricing and availability, PowerScale lets businesses deploy infrastructure that suits their current needs, and upgrade and adapt as requirements change.

4. What role can storage play in accelerating AI pipelines?

Storage can directly accelerate AI pipelines by making datasets available across multiple stages and models, rather than requiring data to be duplicated or moved. Dell PowerScale’s OneFS operating system provides a unified namespace, allowing businesses to perform training, validation and inferencing on a single, in-place data set. The result is simpler management, improved storage efficiency and reduced delays when models are updated and redeployed.

5. Enabling seamless data access across hybrid and multi-cloud environments

To enable seamless operations across hybrid and multi-cloud environments, storage platforms should provide consistent access to local, edge and cloud data. Dell PowerScale’s integrated cloud support helps make remote data directly accessible over standard protocols with no conversion required – reducing the need to duplicate datasets between locations, which can otherwise result in wasted resources, increased operational complexity and a risk of inconsistent results.

6. Securing AI data while maintaining accessibility and compliance

To secure AI data while maintaining accessibility and compliance, storage platforms must combine strong access controls with built-in data-protection and recovery capabilities.

Dell PowerScale incorporates access controls that can integrate with broader security and data-protection frameworks such as Dell PowerProtect for consistent policy management. The platform also provides native data-protection capabilities including at-rest encryption and immutable snapshots, supporting cyber-resilience strategies and helping organisations recover clean data in the event of a ransomware attack.

7. Intelligently balancing performance and cost

An efficient storage strategy incorporates both high-performance media for workloads that need it and cheaper archival for low-priority data. OneFS can perform policy-based data placement based on access patterns, ensuring fast access to active data without requiring complex manual tiering, and without wasteful over-provisioning. By moving “cold” data into low-cost storage, PowerScale can also help reduce energy consumption and infrastructure costs.

Conclusion

Storage for AI systems requires a scalable architecture that offers performance, security, cost and flexibility – and the ability to manage cloud data with the same tools and policies as on-premises information. Combining all of these capabilities with automated data management, Dell PowerScale helps businesses maximise the value of their current AI deployments, and adapt as requirements change.

If you think PowerScale is the right storage solution for your business, find out more on the Dell website: US readers click here and CA readers here.