Use cases / 01–04
Infrastructure.
In operation.
Four workflows across the distributed AI estate.
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Recover a known failure.
A VM or service stops responding.
Propose a supported recovery, authorize the action and check fresh service health.
Validate a change before rollout.
A firmware, configuration or workload change is proposed.
Evaluate the supported change against a model and constraints before an approved rollout.
Place workloads under policy.
An AI workload needs execution capacity.
Select a permitted destination, authorize execution and record usage.
Find what limits GPU capacity.
Demand grows or a workload slows.
Investigate constraints and review a capacity recommendation before any operational change.
Illustrative operating scenarios based on the Invences portfolio. Integrations and operating boundaries depend on the deployment.