Anomaly Detection allows you to create custom alerts, set up customized alerts, and transform metric events configuration. You can also save time and create a custom alert in
Notebooks while using the app.
To use the latest version of
Anomaly Detection, you need to have appropriate permissions. For more information, see
Anomaly Detection overview.
To manually create a simple custom alert configuration
Go to
Anomaly Detection.
Select New alert > Create your own custom alert to create a new alert. To edit an existing custom alert, select any custom alert from the list.
On the Simple tab, expand Set scope.
Optional In Segments, choose one or more segments you want to filter by.
Use case: Use segments with Anomaly Detection custom alerts.
In Query, provide the DQL query to fetch your data.
We recommend that you use the interval: 1m parameter to ensure proper data resolution for the analysis.
Expand Define alert condition.
In Select use case, choose the preferred analyzer. For details, see Analyzer type and parameters.
In Set a condition > Threshold, select Suggest values if you want Dynatrace Intelligence to automatically suggest a value based on the latest behavior of your data. You can also choose the desired threshold value and the Unit of your value manually.
Optional In Set a condition > Alert condition, select:
You can write { to let Dynatrace Intelligence suggest you placeholder names with desired value (for example, {alert_condition}). For more information, see Event template.
Whenever you Create or Save your custom alert, its configuration gets automatically validated. If the there's no errors present in your configuration, you'll be able to save or update your configuration. If there are any errors, the section will be highlighted with red and marked with Error message under the section title.
Check the Status of the new configuration shortly after creation to ensure there are no errors in the execution.
With Dynatrace Intelligence for Notebooks, you can preview your custom alert configuration and evaluate its effectiveness. This option takes you to
Notebooks, where you configure the query and monitoring strategy, and then back to
Anomaly Detection to create an event template.
Anomaly Detection.
Notebooks.For a DQL query, we recommend that you use the interval: 1m parameter to ensure proper data resolution for the analysis.
Anomaly Detection.Check the Status of the new configuration shortly after creation to ensure there are no errors in the execution.
Metric events enhance anomaly detection, expanding them beyond out-of-the-box use cases into metric-based events. With the power of DQL, you can extend this reach further.
To convert a metric event to the custom alert configuration
Anomaly Detection.interval:1m parameter to the query.Check the Status of the new configuration shortly after creation to ensure there are no errors in the execution.