Caladrius

GPU infrastructure native

Stalls? Slowdowns? Stragglers?Know in minutes.Not hours.

When a training or inference job stalls or slows, Caladrius names the root cause across device, fabric, and storage, drives the fix on approval, and verifies it held. It often identifies problems while they're still forming.

DeviceFabricStorage
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From the first signal to a confirmed fix.

Diagnose the fault, attribute it to the right layer, drive the fix on your approval, and verify it held. Often the catch comes while the problem is still forming.

  1. Catch

    Alerts from every layer, correlated into one incident.

    • Device
    • Fabric
    • Storage
    • Workload

  2. Diagnose

    The root cause named: device, fabric, storage, or workload.

  3. Attribute

    Routed to whoever owns the fix.

  4. Rollback

    Fix

    Recommended, approved, executed.

    • Recommended
    • Approved
    • Executed

  5. Verify

    Checked that it held. Rolled back if it didn't.

    verified incident-to-action-to-outcome record

The operator's fleet.The customer's workload.One product.

Each side of the boundary gets its own console.And its own answers.

The operator

Fleet Console

Operators run the Fleet Console over their whole fleet, every rack, node, and GPU. When a customer's job stalls or slows, the console names the root cause, calls which side owns the fault, drives the fix on approval, and verifies it held. Often it catches problems while they're still forming, before the customer ever feels them.

The customer

Workload Console

Customers run the Workload Console in their own environments. It discovers their assets itself, no operator required. When a job stalls or slows, the console identifies the root cause, drives the fix on the customer's approval, and verifies it held. Faults on the operator's side go over already attributed, evidence attached.

The private fleet

Both at once.

Own and operate your GPU fleet? Then you're both. Run the Fleet Console with the platform team and the Workload Console with the AI/ML teams, over one estate. The boundary is internal, workload versus infrastructure, and the same analysis settles that argument with evidence.

Security and control

How Caladrius runs under your control.
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  • Access you grant

    Caladrius acts only within the permissions you set, and you decide what it may recommend and what it may execute.

  • Auditable by design

    Every action Caladrius proposes or takes is logged and auditable.

  • Tenant-isolated

    Scoped views enforce that each customer sees only their own resources.

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