SLO oversight dashboard
The SLO oversight dashboard provides a high-level overview of the current state of your SLOs. It brings together critical metrics for monitoring service health, detecting anomalies, and tracking overdue reviews. With its interactive widgets, the dashboard enables you to stay on top of your organization's reliability goals.
It is made up of the following widgets:
- Highlights with key statistics about your service health, SLO review debt, and data integrity
- Operational health displays the details on the current health of your services and SLOs based on the remaining error budget, segregating them into Healthy, At risk, Exhausted, and No data categories
- SLO quality focuses on SLO review debt and data integrity
To access the SLO oversight dashboard, go to the Dashboards page and open the SLO oversight tab.
- The Organization admin can configure which resources are displayed on the dashboard
- You can access resources from the projects you have permission to view
- Users can filter the dashboard by project, service, or label
- Filters applied are only visible to you and will not affect other users’ views
- You can share the dashboard along with your applied filters by sharing its link
The Highlights widget summarizes key statistics from the Health and SLO quality widgets. It helps you quickly identify areas requiring immediate attention.
- Operational health visualizes the current health of your services
- SLO quality shows the number of flagged SLOs—with an overdue review or data anomalies
Operational health widget
The Operational health widget provides detailed insights into the remaining error budget for services and SLOs, grouped under Healthy, At risk, Exhausted, and No data categories. The categories are defined using the thresholds set for the Service health dashboard by error budget.
This widget breaks down the health information by service and SLO. The detailed view includes:
- The Error budget status diagrams visualize health categories with weekly trends
- The Top budget-consuming services or SLOs table links to pre-filtered lists, enabling further analysis
Each section of the widget links to a more detailed view.
To open the required view, click 
at the top-right corner of a widget.
| Click | Opens |
|---|---|
| Service health | Service health dashboard by error budget |
| Exhausted, At risk, Healthy, and No data services | Service health dashboard, pre-filtered by the corresponding error budget state |
| Top exhausted services | Service list, sorted by the highest error budget exhaustion in the descending order |
| SLO health To exhausted SLOs | SLO list, sorted by the remaining error budget in the descending order |
| Exhausted, At risk, Healthy, and No data SLOs | SLO list, pre-filtered by the corresponding error budget state |
SLO quality widget
Regular reviews and no data anomalies in your SLOs indicate a good SLO quality. To help increase the quality of your SLOs, the SLO quality widget flags SLOs with review or data integrity issues.
The left block of SLO quality presents statistics and trends for the following SLOs:
| SLOs with quality issues | Description |
|---|---|
| Overdue SLOs | SLOs not reviewed before the review due date |
| Dusty SLOs | SLOs not reviewed for six or more months (this timeframe is fixed and non-configurable) |
| SLOs with data anomalies (last 24 hours / 7 days) | SLOs with active data anomalies within the specified timeframes |
Its right block contains the list of services with SLOs to check—those with quality issues shown in the widget.
Additionally, every quality issue category is visualized in a dedicated widget:
Reviews
- SLOs by review status
- The list of services with review debt
The Not started status is assigned to SLOs that meet both of the following conditions:
- No review is scheduled for its service
- The SLO hasn't been reviewed
Data integrity
- The diagram with data anomalies active within the last 24 hours
- The data anomaly heatmap visualizing data anomaly intensity by service over the last 7 days (darker colors represent higher intensity)
The diagram and heatmap include data anomalies as follows:
- Resolved within the last 24 hours / 7 days
- Currently unresolved
Data anomalies can stem from external data source issues or indicate resource misconfiguration in Nobl9. To troubleshoot data source-related problems, refer to the specific data source's troubleshooting guide.
The following table briefly describes data anomaly types, their rules, and potential configuration issues they can indicate:
| Data anomaly type | Description |
|---|---|
| Incremental mismatch | Occurs in ratio SLOs when a non-incremental data point is received by an SLO set to receive incremental data |
| Constant burn | SLO continuously consumes error budget for an unusually extended period |
| No burn | SLO hasn't consumed error budget for an unusually long period |
| No data | SLO reports no data for an unusually extended period |
