Reports

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.

Note

Reports are enabled by default for SaaS. To enable this feature for self-hosted, additional configurations must be added. See Enabling reports for self-hosted accounts.

Report types

Currently, only “Consumption Reports” are available, which provides insights into the consumption of resources such as GPU, CPU, and CPU memory across organizational units.

Reports table

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:

Column	Description
Report	The name of the report
Description	The description of the report
Status	The different lifecycle phases and representation of the report condition
Type	The type of the report – e.g., consumption
Created by	The user who created the report
Creation time	The timestamp of when the report was created
Collection period	The period in which the data was collected

Reports status

The following table describes the reports' condition and whether they were created successfully:

Status	Description
Ready	Report is ready and can be downloaded as CSV
Pending	Report is in the queue and waiting to be processed
Failed	The report couldn’t be created
Processing...	The report is being created

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

Creating a new report

Before you start, make sure you have a project.

To create a new report:

1. Click +NEW REPORT

2. Enter a name for the report (if the name already exists, you will need to choose a different one)

3. Optional: Provide a description of the report

4. 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

5. Set the report segmentation and filters

   • Filters - Filter by project or department name

   • Segment by - Data is collected and aggregated based on the segment

6. Click CREATE REPORT

Deleting a report

1. Select the report you want to delete

2. Click DELETE

3. On the dialog, click DELETE to confirm

Downloading a report

Note

To download, the report must be in status “Ready”.

1. Select the report you want to download

2. Click DOWNLOAD CSV

Enabling reports for self-hosted accounts

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.

1. Edit the runai-backend-org-unit-service ConfigMap:

   kubectl edit cm runai-backend-org-unit-service -n runai-backend

2. Add 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>

3. Edit the runai-backend-metrics-service ConfigMap:

   kubectl edit cm runai-backend-metrics-service -n runai-backend

4. Add 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"

5. 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>\"\n

6. Restart the deployments:

   kubectl rollout restart deployment runai-backend-metrics-service runai-backend-org-unit-service -n runai-backend

7. Refresh the page to see Reports under Analytics in the NVIDIA Run:ai platform.

Using API

To view the available actions, go to the Reports API reference.