Select Metrics from the navigation menu to open the Metrics browser, which gives you an easy way to browse all metrics available in your monitoring environment and make a metric-specific tile for your dashboard.
Filter and sort the table
- By default, the table of metrics is filtered to show only those metrics that were last reported after the start of the selected timeframe (for example,
Last 2 hours). Turn off Filter for metrics last reported after [timestamp] to see all metrics regardless of when they were last reported.
- Set Favorites to
Noto filter the table by metrics that you have favorited.
- To favorite a metric, select the star icon in the Favorite column of the table. Favorited metrics sort to the top of the table by default.
- To unfavorite a metric, select the star again.
- The filter bar (Filtered by) has two options:
Text(enter a string and press Enter to add a text filter. It filters on metric key, metric name, and description.
No). You can combine the two filters.
- Select column header Favorite, Name, or Key to sort by that column.
Review metric details
Expand Details for any metric (row) in the table to see metric details and a chart of the metric over the selected timeframe.
The name of the metric in the user interface.
The fully qualified key of the metric. If a transformation has been used it is reflected in the metric key.
Entity type for this metric.
A short description of the metric.
Tags allow further grouping of metrics.
The timestamp when the metric was created.
The timestamp when the metric was last written.
Whether the metric is subject to Davis data unit (DDU) billing.
The unit of the metric.
The known lower boundary value for the metric.
The known upper boundary value for the metric.
The default aggregation for this metric.
The list of allowed aggregations for this metric.
The fine metric division (for example, process group and process ID for some process-related metric).
Possible transform operators.
Add metric to dashboard
To add a metric to a dashboard
- Expand Details for any metric (row) in the table.
- Select Create chart to open the metric in the Data explorer.
- Adjust the settings as needed.
- Select Pin to dashboard.
- Specify the target dashboard and metric title.
- Select Pin.
Metadata for custom metrics
To provide contextual information for custom metrics (for example, to define the unit of measurement, or to provide display names or descriptions or even information such as lower and upper value ranges or Davis-relevant information), you can create metric metadata per metric key.
Once this information is provided, it becomes part of the metrics descriptor and can be queried via the API and be used in the Metric browser and Data explorer.
- Providing metadata via Settings 2.0 is available only for custom/schemaless metrics, not for built-in/code-registered metrics.
- The metadata provided for a specific metric key exists side-by-side with the metric timeseries itself. You can even create the metric metadata before you ingest datapoints for the first time.
Configuration via API
Metric metadata is fully configurable via API. For details, see Custom metric metadata.
Configuration via web UI
To configure metric metadata for custom metrics via the Dynatrace web UI
- Go to Metrics.
- Expand the Details of a metric.
- Select Edit metadata.
- On the Metric metadata page, enter metadata for the selected metric.
- Display name—Enter a human-friendly name for the metric.
- Description—Enter a free-form decription of the metric: how it is measured, etc.
- Unit—Select a unit from the list.
- Metric properties
- Minimum value—The lower boundary of the metric.
- Maximum value—The upper boundary of the metric.
- Root cause relevant—A root-cause relevant metric represents a strong indicator for a faulty component.
- Impact relevant—An impact-relevant metric is highly dependent on other metrics and changes because an underlying root-cause metric has changed.
- Value type—The type of the metric's value. You have these options:
score: A score metric is a metric where high values indicate a good situation, while low values indicate trouble. An example of such a metric is a success rate.
error: An error metric is a metric where high values indicate trouble, while low values indicate a good situation. An example of such a metric is an error count.
- Latency—The latency of the metric, in minutes. It indicates how long it takes before an ingested new metric data point is available in Dynatrace.
- Metric dimensions—To add a dimension, select Add dimension and enter the Dimension key and Display name for the dimension.
- Tags—To add a tag, select Add tag and enter the tag.
- Save your changes.