This section explains the procedure of managing reports in NVIDIA Run:ai.
Reports allow users to access and organize large amounts of data in a clear, CSV-formatted layout. They enable users to monitor resource consumption, analyze trends, and make data-driven decisions to optimize their AI workloads effectively.
Currently, only consumption reports are available, which provides insights into the consumption of resources such as GPU, CPU, and CPU memory across organizational units.
The Reports table can be found under Analytics in the NVIDIA Run:ai platform.
The Reports table provides a list of all the reports defined in the platform and allows you to manage them.
Users are able to access the reports they have generated themselves. Users with project viewing permissions throughout the tenant can access all reports within the tenant.
The Reports table comprises the following columns:
The description of the report
The different lifecycle phases and representation of the report condition
The type of the report – e.g., consumption
The user who created the report
The timestamp of when the report was created
The period in which the data was collected
The following table describes the reports' condition and whether they were created successfully:
Report is ready and can be downloaded as CSV
Report is in the queue and waiting to be processed
The report couldn’t be created
The report is being created
Customizing the Table ViewFilter - 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
Before you start, make sure you have a project.
To create a new report:
Enter a name for the report (if the name already exists, you will need to choose a different one)
Optional: Provide a description of the report
Set the report’s data collection period
Start date - The date at which the report data commenced
End date - The date at which the report data concluded
Set the report segmentation and filters
Filters - Filter by project or department name
Segment by - Data is collected and aggregated based on the segment
Select the report you want to delete
On the dialog, click DELETE to confirm
Note
To download, the report must be in status “Ready”.
Select the report you want to download
Reports must be saved in a storage solution compatible with S3. To activate this feature for self-hosted accounts, the storage needs to be linked to the account. The configuration should be incorporated into two ConfigMap objects within the Control Plane.
Edit the runai-backend-org-unit-service ConfigMap:
kubectl edit cm runai-backend-org-unit-service -n runai-backendAdd the following lines to the file:
S3_ENDPOINT: <S3_END_POINT_URL>
S3_ACCESS_KEY_ID: <S3_ACCESS_KEY_ID>
S3_ACCESS_KEY: <S3_ACCESS_KEY>
S3_USE_SSL: "true"
S3_BUCKET: <BUCKET_NAME>Edit the runai-backend-metrics-service ConfigMap:
kubectl edit cm runai-backend-metrics-service -n runai-backendAdd the following lines to the file:
S3_ENDPOINT: <S3_END_POINT_URL>
S3_ACCESS_KEY_ID: <S3_ACCESS_KEY_ID>
S3_ACCESS_KEY: <S3_ACCESS_KEY>
S3_USE_SSL: "true"In addition on the same file, under config.yaml section, add the following right after log_level: \"Info\":
reports:\n s3_config:\n bucket: \"<BUCKET_NAME>\"\nRestart the deployments:
kubectl rollout restart deployment runai-backend-metrics-service runai-backend-org-unit-service -n runai-backendRefresh the page to see Reports under Analytics in the NVIDIA Run:ai platform.
To view the available actions, go to the Reports API reference.
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