4.1 Configuring Observability Sources
4.1.1 Observability Sources
4.1.2 Data Pipeline and Parser Configuration
4.1.3 Data Enrichment Techniques
4.2 Configuring RCABot and ML Models
7.2 Authentication and Security
7.3 Data Management and Data Model Handling
7.3.1 Storage
7.3.2 Retention
7.3.3 Export/Import
7.3.4 Working with Data Model
7.4 Control Center
7.4.1 License Entitlements
7.5 Platform Settings
7.5.1 Definitions
7.5.2 Preferences
7.5.3 About
Report Generation >
While Scheduled Reports are recommended, where admin users create and automate report generation, there are cases where you might need an on-demand report. In such cases, regular users can create and generate reports as needed.
To generate an on-demand report, follow these steps:
All the generated reports will be displayed under the Generated Reports tab.
The following fields will be displayed.
In addition, there are other options available at the top of the table
If a report fails, you can access its tracking information by clicking on the Failed status. This helps diagnose the cause of the failure. For instance, if we need to investigate why the Report-Dashboard report has failed, we can click on the report to determine the cause.
Upon clicking the Failed status, a panel will appear, providing the tracked information for failed reports.
Click on the PDF or CSV button under the Action column to download the report. The report will be downloaded and saved to your local machine.
Sample Query
All possible combinations are supported, including Joins, Aggregations, Renaming column names, Mathematical Operations, and Operators.
1. Longterm storage query:
Time selectors are supported, which means if we want to fetch data only for a particular time range, we can do that by including “$start_time” and “$end_time” as the keyword, which will be replaced by the selected time filter.
2. Elasticsearch Queries:
Here, the user needs to provide an index along with the query, multiple buckets like Date Histogram, Terms, Significant Terms, Data range, filters, etc., and multiple metrics like sum, count, average count, min, max, etc. aggregations are supported.
Query – {‘_source’: [‘alert_id’, ‘Alert-Rule-Name’, ‘alarm_state’], ‘size’: 100}
Index – vunet-1-1-notification-*
Here, the user needs to provide an elastic search query including the index and with a time field. Also, multiple buckets like Date Histogram, Terms, Significant Terms, Data range, filters, etc., and multiple metrics like sum, count, average count, min, max, etc. aggregations are supported.
.es(index=vunet-1-1-notification-*, q=*,size=10, timeseries=False)
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