Data stays put even when your workspace changes: Ensuring AI research continuity with independent storage

Hi, this is the Runyour team.

When operating GPU infrastructure for enterprise companies and professional research institutions, there is a task as critical as the efficient allocation of computing resources: the persistence and secure management of research data.

What happens when a machine is replaced or returned at the end of a project, and the terabytes of training datasets, model checkpoints, and experimental outputs stored within it are not properly protected?

This goes beyond mere inconvenience; it inevitably leads to a massive loss of research assets for the entire organization.

3 Limitations of Coupling Workspaces and Data

In traditional GPU work environments, it has been standard practice to store data directly on the machine's internal disk.

In this structure, where the workspace (computing resources) and storage space are combined, the following operational bottlenecks occur whenever infrastructure is reconfigured.

Inefficiency in data migration when changing machine specs: Every time you upgrade to a higher-spec GPU machine or move your workspace, you waste a significant amount of time manually backing up existing data and re-uploading it to the new machine.
Risk of research data loss upon resource return: When a resource allocation period expires and the workspace must be returned, there is a risk that important model checkpoints and results remaining on the internal disk will be deleted. This often leads to unstable situations where data must be backed up in a rush.
Unnecessary duplicate copies of the same dataset: When multiple project teams or researchers use the same large-scale dataset (e.g., hundreds of GBs of image data) for experiments, valuable storage space is wasted as the data is redundantly copied to every machine.

Innovating Data Management with Runyour Cloud's 'Independent Storage'

To solve these problems, Runyour Cloud offers a next-generation data operations solution that completely separates GPU workspaces (containers/bare metal) from storage space: 'Independent Storage' that reflects enterprise management hierarchies.

It works just like an external USB drive that you can freely connect to any computer you need. Even if a machine is replaced or deleted, your valuable research data remains safely preserved in a separate, independent storage volume.

Organizations can flexibly configure this independent storage to suit various project types and workflows.

💡 Key Benefits of Independent Storage

Configure up to 3 storage volumes for purpose-driven management
You can create up to three independent storage volumes within your total allocated capacity. This allows you to physically separate and systematically manage data based on its type, such as "training datasets," "model checkpoints," and "experimental outputs."

Connect one storage volume to up to 10 machines simultaneously (optimized for parallel experiments)
Mount a single independent storage volume to up to 10 worker machines simultaneously. Multiple researchers can reference the same storage to conduct parallel experiments efficiently, without the need to copy large datasets to each machine.

Intuitive web-based file browser
No more tedious terminal or SSH commands just to check your data. With the Runyour Cloud web console, you can view and manage your stored files and directory structures at a glance with just a few clicks.

Smart notifications to prevent data loss and operational disruptions

Research data is a core asset that accumulates over time. Therefore, a proactive management system is essential to prevent training jobs from being interrupted by storage reclamation or capacity limits.

Runyour Cloud eases the burden on administrators with its comprehensive notification features.

Instant alerts at 80% capacity: If storage usage reaches 80% due to accumulating large training datasets or checkpoints, an alert email is sent immediately.This prevents the unfortunate scenario where AI training jobs meant to run overnight are halted due to insufficient space.
Advance notice for reclamation and contract expiration: We send an email notification 7 days before storage reclamation to ensure you have enough time to respond. Additionally, as your contract approaches its end, we provide step-by-step notifications at 30 days and 7 days prior, helping you safely back up your data or plan for future operations.

Conclusion

In enterprise AI infrastructure, storage is more than just a file repository—it is a robust foundation that ensures the continuity of your research assets.

Runyour Cloud’s independent storage provides a secure data management system that remains unaffected by frequent changes or returns of worker machines.

Now, your researchers can focus entirely on AI model development and driving innovation without worrying about data loss.