Run 24623 TW reports

docs/platform-admin/performance/reports.md

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+
+# Reports
+
+This article explains the procedure of managing reports in 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 is enabled by default for SaaS tenants. In order to enable the feature for  tenants, additional configuration must be added. See **Enabling reports for self-hosted accounts** below.
+
+
+
+## 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 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.
+
+![](img/reports-table.png)
+
+
+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**
+
+## Using API
+
+To view the available actions, go to the [Reports](https://api-docs.run.ai/latest/tag/Reports/) API reference.
+
+## 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:
+   ``` bash
+   kubectl edit cm runai-backend-org-unit-service -n runai-backend
+   ```
+
+2. Add the following lines to the file:
+   ``` bash
+   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:
+   ``` bash
+   kubectl edit cm runai-backend-metrics-service -n runai-backend
+   ```
+
+
+4. Add the following lines to the file:
+   ``` bash
+   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\"\n`:
+   ``` bash
+   reports:\n s3_config:\n bucket: \"<BUCKET_NAME>\"\n
+   ```
+
+6. Restart the deployments:
+   ``` bash
+   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 Run:ai platform.

mkdocs.yml

@@ -326,6 +326,7 @@ nav:
 
     - 'Review your performance' :
       - 'Dashboard Analysis' : 'platform-admin/performance/dashboard-analysis.md'
+      - 'Reports' : 'platform-admin/performance/reports.md'
     - 'Best Practices' :
       - 'From Docker to Run:ai ' : 'admin/researcher-setup/docker-to-runai.md'
     - 'System Configuration' :