Data Sources
This section explains what data sources are and how to create and use them.
Data sources are a type of workload assets and represent a location where data is actually stored. They may represent a remote data location, such as NFS, Git, or S3, or a Kubernetes local resource, such as PVC, ConfigMap, HostPath, or Secret.
This configuration simplifies the mapping of the data into the workload’s file system and handles the mounting process during workload creation for reading and writing. These data sources are reusable and can be easily integrated and used by AI practitioners while submitting workloads across various scopes.
Data Sources Table
The data sources table can be found under Workload manager in the NVIDIA Run:ai platform.
The data sources table provides a list of all the data sources defined in the platform and allows you to manage them.

The data sources table comprises the following columns:
Data source
The name of the data source
Description
A description of the data source
Type
The type of data source connected – e.g., S3 bucket, PVC, or others
Status
The different lifecycle phases and representation of the data source condition
Scope
The scope of the data source within the organizational tree. Click the scope name to view the organizational tree diagram
Kubernetes name
The unique name of the data sources Kubernetes name as it appears in the cluster
Workload(s)
The list of existing workloads that use the data source
Template(s)
The list of workload templates that use the data source
Created by
The user who created the data source
Creation time
The timestamp for when the data source was created
Cluster
The cluster that the data source is associated with
Data Sources Status
The following table describes the data sources' condition and whether they were created successfully for the selected scope.
No issues found
No issues were found while creating the data source
Issues found
Issues were found while propagating the data source credentials
Issues found
The data source couldn’t be created at the cluster
Creating…
The data source is being created
No status / “-”
When the data source’s scope is an account, the current version of the cluster is not up to date, or the asset is not a cluster-syncing entity, the status can’t be displayed
Customizing the Table View
Filter - Click ADD FILTER, select the column to filter by, and enter the filter values
Search - Click SEARCH and type the value to search by
Sort - Click each column header to sort by
Column selection - Click COLUMNS and select the columns to display in the table
Download table - Click MORE and then click ‘Download as CSV’. Export to CSV is limited to 20,000 rows.
Refresh - Click REFRESH to update the table with the latest data
Adding a New Data Source
To create a new data source:
Click +NEW DATA SOURCE
Select the data source type from the list. Follow the step-by-step guide for each data source type:
Copying a Data Source
To copy an existing data source:
Select the data source you want to copy
Click MAKE A COPY
Enter a name for the data source. The name must be unique.
Update the data source and click CREATE DATA SOURCE
Renaming a Data Source
To rename an existing data source:
Select the data source you want to rename
Click Rename and edit the name/description
Deleting a Data Source
To delete a data source:
Select the data source you want to delete
Click DELETE
Confirm you want to delete the data source
Creating PVCs in Advance
Add PVCs in advance to be used when creating a PVC-type data source via the NVIDIA Run:ai UI.
The actions taken by the admin are based on the scope (cluster, department or project) that the admin wants for data source of type PVC. Follow the steps below for each required scope:
Cluster Scope
Locate the PVC in the NVIDIA Run:ai namespace (
runai
)Provide NVIDIA Run:ai with visibility and authorization to share the PVC to your selected scope by implementing the following label:
run.ai/cluster-wide: "true”
The PVC is now displayed for that scope in the list of existing PVCs.
Department Scope
Locate the PVC in the NVIDIA Run:ai namespace (
runai
)To authorize NVIDIA Run:ai to use the PVC, label it:
run.ai/department: "id"
The PVC is now displayed for that scope in the list of existing PVCs.
Project Scope
Locate the PVC in the project’s namespace.
The PVC is now displayed for that scope in the list of existing PVCs.
Creating ConfigMaps in Advance
Add ConfigMaps in advance to be used when creating a ConfigMap-type data source via the NVIDIA Run:ai UI.
Cluster Scope
Locate the ConfigMap in the NVIDIA Run:ai namespace (
runai
)To authorize NVIDIA Run:ai to use the ConfigMap, label it:
run.ai/cluster-wide: "true”
The ConfigMap must have a label of
run.ai/resource: <resource-name>
The ConfigMap is now displayed for that scope in the list of existing ConfigMaps.
Department Scope
Locate the ConfigMap in the NVIDIA Run:ai namespace (
runai
)To authorize NVIDIA Run:ai to use the ConfigMap, label it:
run.ai/department: "<department-id>"
The ConfigMap must have a label of
run.ai/resource: <resource-name>
The ConfigMap is now displayed for that scope in the list of existing ConfigMaps.
Project Scope
Locate the ConfigMap in the project’s namespace
The ConfigMap must have a label of
run.ai/resource: <resource-name>
The ConfigMap is now displayed for that scope in the list of existing ConfigMaps.
Using API
To view the available actions, go to the Data sources API reference.
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