# Using the Scheduler with Third-Party Workloads

By default, Kubernetes uses its own native scheduler to determine pod placement. The NVIDIA Run:ai platform provides a custom scheduler, `runai-scheduler`, which is used by default for workloads submitted using the [NVIDIA Run:ai](/self-hosted/2.20/workloads-in-nvidia-run-ai/introduction-to-workloads.md) platform. This section outlines how to configure third-party workloads, such as those submitted directly to Kubernetes, to run with the [NVIDIA Run:ai Scheduler](/self-hosted/2.20/platform-management/runai-scheduler/scheduling/concepts.md), `runai-scheduler`, instead of the default Kubernetes scheduler.

## Specify the Scheduler in the Workload YAML <a href="#specify-the-scheduler-in-the-workload-yaml" id="specify-the-scheduler-in-the-workload-yaml"></a>

To use the NVIDIA Run:ai Scheduler for third-party workloads, specify it in the workload’s YAML file. This instructs Kubernetes to schedule the workload using the NVIDIA Run:ai Scheduler instead of the default one.

```yaml
spec:schedulerName: runai-scheduler
```

**For example:**

```yaml
apiVersion: v1
kind: Pod
metadata:
  annotations:
    user: test
    gpu-fraction: "0.5"
    gpu-fraction-num-devices: "2"
  labels:
    runai/queue: test
  name: multi-fractional-pod-job
  namespace: test
spec:
  containers:
  - image: gcr.io/run-ai-demo/quickstart-cuda
    imagePullPolicy: Always
    name: job
    env:
    - name: RUNAI_VERBOSE
      value: "1"
    resources:
      limits:
        cpu: 200m
        memory: 200Mi
      requests:
        cpu: 100m
        memory: 100Mi
    securityContext:
      capabilities:
        drop: ["ALL"]
  schedulerName: runai-scheduler
  serviceAccount: default
  serviceAccountName: default
  terminationGracePeriodSeconds: 5
```

## Enforce the Scheduler at the Namespace Level <a href="#enforce-the-scheduler-at-the-namespace-level" id="enforce-the-scheduler-at-the-namespace-level"></a>

If modifying the workload YAML is not possible, you can enforce the use of the NVIDIA Run:ai Scheduler for all workloads in a given namespace (i.e., NVIDIA Run:ai [project](/self-hosted/2.20/platform-management/aiinitiatives/organization/projects.md)) by applying an annotation. Once applied, all workloads submitted to the annotated namespace will automatically use the NVIDIA Run:ai Scheduler without requiring individual YAML modifications.

1. Annotate the namespace with: `runai/enforce-scheduler-name: true`. For example, to annotate a project named `proj-a`, use the following command:

```bash
kubectl annotate ns runai-proj-a runai/enforce-scheduler-name=true
```

2. Verify the namespace in YAML format to see the annotation by running the following:

```bash
kubectl get ns runai-proj-a -o yaml
```

The following shows an example output:

```yaml
apiVersion: v1
kind: Namespace
metadata:
  annotations:
    runai/enforce-scheduler-name: "true"
  creationTimestamp: "2024-04-09T08:15:50Z"
  labels:
    kubernetes.io/metadata.name: runai-proj-a
    runai/namespace-version: v2
    runai/queue: proj-a
  name: runai-proj-a
  resourceVersion: "388336"
  uid: c53af666-7989-43df-9804-42bf8965ce83
spec:
  finalizers:
  - kubernetes
status:
  phase: Active
```


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