Supported Workload Types

NVIDIA Run:ai supports a broad range of workloads from the ML and Kubernetes ecosystem that are already registered as workload types in the platform and ready to use. These workloads are managed by the Resource Interface (RI), which ensures they receive the same advanced scheduling, orchestration, and monitoring capabilities as NVIDIA Run:ai native workloads. For more details on feature support, see Supported features.

All supported workload types are pre-registered using the Workload Types API. You can retrieve the full list of these workloads and their current configuration defaults.

Note

To define and register workload types beyond those provided by NVIDIA Run:ai, see Extending workload support with Resource Interface.

List of Supported Workload Types

The following workload types are already registered in the platform and ready to use:

• NVIDIA - NIM Services, DynamoGraphDeployment

• Kubernetes - LeaderWorkerSet (LWS), Deployment, StatefulSet, ReplicaSet, Pod, CronJob, Job (kubernetes.io)

• Kubeflow - TFJob, PyTorchJob, MPIJob, XGBoostJob, JAXJob, Notebook, ScheduledWorkflow (kubeflow.org)

• Ray - RayService, RayCluster, RayJob (ray.io)

• Tekton - PipelineRun, TaskRun (tekton.dev)

• Additional frameworks - SeldonDeployment, AMLJob, Workflow, DevWorkspace, Service, VirtualMachineInstance, InferenceService (KServe)

Submitting Supported Workload Types

Supported workload types are submitted as standard Kubernetes YAML manifests. Once submitted, the workload is created and appears in the Workloads table for monitoring and management. See Submit supported workload types via YAML.

Workload Types and Defaults

Each workload type is assigned a default category, which determines its default priority and preemptibility. These defaults influence how workloads are scheduled and prioritized within a project, as well as how they are grouped for monitoring and reporting.

Note

To retrieve the default category and priority per workload type, refer to the List workload types API.

Category	Default Priority	Default Preemptibility
Build	High	Non-preemptible
Train	Low	Preemptible
Deploy	Very high	Non-preemptible

Workload Types by Default Category

Workload Type	Build	Train	Deploy
AMLJob
CronJob
Deployment
DevWorkspace
DynamoGraphDeployment
InferenceService (KServe)
JAXJob
Job
LeaderWorkerSet (LWS)
MPIJob
NIMCache
NIMServices
Notebook
PipelineRun
Pod
PyTorchJob
RayCluster
RayJob
RayService
ReplicaSet
ScheduledWorkflow
SeldonDeployment
Service
SPOTRequest
StatefulSet
TaskRun
TFJob
VirtualMachineInstance
Workflow
XGBoostJob

Updating Default Category and Priority Mapping

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

• To update the priority mapping, see Workload priority control

• To update the category mapping, see Monitor workloads by category