Monitor Workloads by Category

A workload category represents the role or purpose of a workload such as training, building, or deploying models. Each workload type is automatically assigned a default category to ensure consistent classification across the platform.

Categories appear in the Overview dashboard, allowing administrators to filter, group, and monitor workloads based on their function. Administrators can modify the default category mapping for a workload type using the NVIDIA Run:ai API.

Default Category Mapping

NVIDIA Run:ai defines the following default mappings of workload types to categories.

Note

To see the default priority assigned to each of the workload types listed below, refer to Workload priority control.

NVIDIA Run:ai Workloads

Workload Type	Build	Train	Deploy
Workspaces
Standard training
Distributed training
Custom inference
Hugging Face inference
NVIDIA NIM inference

Third-Party Workloads

BuildTrainDeploy

Workload Type	Build	Train	Deploy
NVIDIA Cloud Functions (NVCF)
Deployment
Seldon Deployment
StatefulSet
ReplicaSet
Pod
Service
CronJob
RayService
PipelineRun
Workflow
ScheduledWorkflow
DevWorkspace
Notebook
Job
TaskRun
VirtualMachineInstance
TFJob
PyTorchJob
XGBoostJob
MPIJob
AmlJob
RayCluster
RayJob

Update the Default Category Mapping

Administrators can change the default category assigned to a workload type by updating the category mapping using the NVIDIA Run:ai API. To update the category mapping:

1. Retrieve the list of workload types and their IDs using GET /api/v1/workload-types.
2. Identify the workloadTypeId of the workload type you want to modify.
3. Retrieve the list of available categories and their IDs using GET /api/v1/workload-categories.
4. Send a request to update the workload type with the new category using PUT /api/v1/workload-types/{workloadTypeId} and include the categoryId in the request body.

Using API

Go to the Workload properties API reference to view the available actions.