Edge, IoT & Compute · Workflow

GPU job with quota and residency

A job is estimated before it starts, blocked if it could exceed its quota, placed only in residency-compatible pools and costed when it ends.

Step by step

Each step is a governed Action: it is permission-checked, logged, and either reversible or compensated.

1
Submit from a template in AI Lab, Video Factory or the API
2
Dataset access and consent checks run
3
Cost and GPU-time are estimated with an upper bound
4
If the upper estimate exceeds remaining quota, the job is blocked and a quota raise goes to DoA approval
5
Residency and classification policy selects an eligible pool
6
The job runs in a sandbox with checkpoints and stops at the hard cap
7
Artifacts are registered with lineage and JobCost posts to AI FinOps, the ROI Ledger and metering

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