NVIDIA Run:ai Workload properties API
Workload properties define the behavioral and scheduling characteristics of a workload submitted to the NVIDIA Run:ai platform. These properties such as type, category, and priority determine how workloads are classified, monitored, and scheduled. - Type - Defines the functional behavior of a workload, such as training or inference, and serves as the foundation for how it is classified within the platform. Each workload type includes a default category (used for monitoring) and a default priority (used for scheduling within a project). - Category - Represents the role or purpose of a workload, such as Build, Train, Deploy. Each workload type is assigned a default category to ensure consistent classification across the platform for monitoring purposes. See [Monitor workloads by category](https://run-ai-docs.nvidia.com/saas/platform-management/monitor-performance/workload-categories). - Priority - Determines the scheduling order of workloads within a project and whether a workload can be preempted. Higher-priority workloads are scheduled first and may become non-preemptible, preventing interruption by lower-priority workloads. See [Workload priority control](https://run-ai-docs.nvidia.com/saas/platform-management/runai-scheduler/scheduling/workload-priority-control).