This page documents V2 of the Metrics Service. If you used Metrics V1 in the past, you will notice that the API is more explicit than in V1.
In case you have existing scripts or processes based on Metrics V1, we've got you covered - all Metrics V1 URLs will keep working and behave just as before.
In modern IT organizations, a wide range of expert tools generate high amounts of data. The big challenge is to leverage this data. According to Gartner, 90% of the information assets from big data analytics efforts through 2017 will be siloed and unleveragable. LeanIX Metrics allows to display time series data in the context of Fact Sheets and thereby establish a useful business context.
With LeanIX Metrics, you can store time series data in LeanIX and create interactive charts to display the data. In addition the data can be linked to Fact Sheets, presented on the Dashboard or be displayed within the "Reports" area.
Navigate over to the Administration area, by selecting the person icon available in the upper right hand corner. Then select Metrics from the left hand panel.
Once you have imported the points the measurement is available in your workspace. You can create a chart and define other specifics.
To do so select the plus icon next to the measurement that you would like to graphically represent.
Associate series information, by using the drop downs. The field name directly corresponds to the key fields in the measure JSON. Define the color for this particular field and the Type of chart, the options are bar, line and area, as well as other information.
Link the Fact Sheet ID used in LeanIX to the right field you provided by adding a rule.
Use the Add button to continue adding Series information to your chart.
|Schema (V1 name: "measurement")
|Schemas contain data points stored over time, which are related to the same topic. The schema defines which Metrics (numeric attributes) and Dimensions (string attributes to filter in charts) exist in points.
|Each data-point is stored for a specific moment (timestamp) and has one or more values for that instant of time. The values are stored in Metric attributes.
|Metric attributes (V1 name: "fields")
|Each data-point stores has one or more Metrics, which contain numeric values that have been collected for the instant of time associated with the data point. When creating a chart the values of the fields can be displayed as a series. For that different aggregation functions are available such as COUNT or SUM.
|Dimension attributes (V1 name: "tags")
|Furthermore a data-point has Dimension attributes, consisting of a key and a value.
The Dimensions further describe a data point and enable to filter for certain data points when displaying a chart for different contexts.
You need to generate an API Token by using the Technical User functionality and enter it on the top right to execute queries directly from the API documentation.
In the API Explorer, you can see all the available actions.
Change to Metrics V1
Schemas are what was called Measurements in Metrics V1. In contrast to V1, schemas are not created or altered implicity by writing points. Instead, a schema has to be created explicitly via the schemas API.
Use this code snippet as body to POST /schemas to create a new schema named "My First Metric":
"name": "My First Metric",
"description": "This is a test metric for LeanIX EAM docs",
This call will return the UUID of the newly created schema. Then write a point to this schema by sending a POST request to /schemas/<schema_uuid>/points with the following body:
"factSheetID": "<your Fact Sheet ID>"
You need to adapt to your context. Now, go to Admin -> Metrics, and you should see the first measurement.
We provide a showcase python implementation here:
LeanIX Metrics Python Script to import metrics
For more details on the Metrics API and supported functionalities, have a look at the
OpenAPI docs. There, all endpoints are explained with examples and descriptions.
The Integration API provides the ability to import and export data using a generic LeanIX Data Interchange Format (LDIF). LDIF is a JSON format with a very simple structure described in the following sections. All mapping and processing of the incoming and outgoing data is done using "Data Processors" that are configured behind the API. Configuration of the processors can be done using the UI, please see the Setup page for more information. The configurations can be managed using the Integration API as well.
Please see the Integration API documentation for Metrics Example.
|Review Swagger API documentation
|Schemas should contain the uploaded data, split into Points
|Each Point has a unique time stamp
|Charts describe how to represent the Schema graphically
|For example as a Bar Chart
|Charts contain Rules which define how the measurement data is mapped to your Fact Sheets (one option is to map using the External ID)
Updated 3 months ago