Azure Power BI

Dynatrace ingests metrics from Azure Metrics API for Azure Power BI. You can view metrics for each service instance, split metrics into multiple dimensions, and create custom charts that you can pin to your dashboards.


  • Dynatrace version 1.201+
  • Environment ActiveGate version 1.195+

Enable monitoring

To enable monitoring for this service, you first need to set up integration with Azure Monitor.

Add the service to monitoring

In order to view the service metrics, you must add the service to monitoring in your Dynatrace environment.

Monitor resources based on tags

You can choose to monitor resources based on existing Azure tags, as Dynatrace automatically imports them from service instances.

To monitor resources based on tags

  1. Go to Settings > Cloud and virtualization > Azure and select the Azure instance.
  2. For Resource monitoring method, select Monitor resources based on tags.
  3. Enter the Key and Value.
  4. Select Save.

Note: To import the Azure tags automatically into Dynatrace, enable Capture Azure tags automatically.

Configure service metrics

Once you add a service, Dynatrace starts automatically collecting a suite of metrics for this particular service. These are recommended metrics.

Recommended metrics:

  • Are enabled by default
  • Can't be disabled
  • Can have recommended dimensions (enabled by default, can't be disabled)
  • Can have optional dimensions (disabled by default, can be enabled).

Apart from the recommended metrics, most services have the possibility of enabling optional metrics.

Optional metrics:

  • Can be added and configured manually

View service metrics

Once you add the service to monitoring, you can view the service metrics in your Dynatrace environment either on your dashboard page or on the custom device overview page.

Import preset dashboards

Dynatrace provides preset Azure dashboards that you can import from GitHub to your environment's Dashboards page.
Note: To save a preset dashboard locally, create a new JSON file on your local machine and copy-paste the content of the JSON file from GitHub into the new file.
Once you save a preset dashboard locally, there are two ways to import it.


Available metrics

Name Description Unit Dimensions Recommended
QueryDuration DAX query duration in last interval MilliSecond ✔️
QueryPoolJobQueueLength Number of jobs in the queue of the query thread pool Count ✔️
memory_metric Memory ranging 0-3 GB for A1, 0-5 GB for A2, 0-10 GB for A3, 0-20 GB for A4, 0-50 GB for A5, and 0-100 GB for A6 Byte ✔️
memory_thrashing_metric Average memory thrashing Percent
qpu_high_utilization_metric QPU high utilization in last minute, 1 for high QPU utilization, otherwise 0 Count
qpu_metric QPU ranging 0-100 for S1, 0-200 for S2, and 0-400 for S4 Count ✔️
workload_memory_metric The usage of memory in your capacity resource per workload Byte Workload ✔️
workload_qpu_metric The query processing unit (QPU) load on your capacity, per workload Count Workload ✔️