Need information about capacity usage

1. Is there any other way to see capacity usage metric data apart from the Metrics App?

Yes.

To retain and analyze capacity data beyond 14 days, you must enable:

Admin Portal → Capacity → Diagnostic settings

You can export telemetry to:

• Azure Log Analytics

• Storage Account

• Event Hub

Microsoft documentation confirms this is the supported way to access and retain telemetry beyond the built-in 14-day window.

Reference:
Capacity Metrics App (14-day view)
https://learn.microsoft.com/power-bi/enterprise/service-premium-gen2-metrics-app

Diagnostic Logs configuration
https://learn.microsoft.com/power-bi/transform-model/log-analytics/desktop-log-analytics-configure

2. How many times did capacity reach 100% in a month?

This is not available directly in the Metrics App UI.

However, once logs are exported to Log Analytics, you can query CPU percentage over a monthly range and count how many times it reached 100%.

Microsoft documents that CPU metrics are available via Azure Monitor.

Reference:
Supported capacity metrics
https://learn.microsoft.com/azure/azure-monitor/reference/supported-metrics/microsoft-powerbidedicated-capacities-metrics

3. How many times was autoscale triggered in a month?

Autoscale events are recorded in telemetry.

Microsoft states that autoscale is triggered when interactive throttling occurs. Once logs are exported, you can count autoscale events over any time range.

Reference:
Autoscale documentation
https://learn.microsoft.com/power-bi/enterprise/service-premium-auto-scale

4. In a month, which workspaces had high CPU usage?

The Metrics App shows this only for 14 days.

If you export logs, you can aggregate CPU or CU consumption by:

• Workspace

• Dataset

• Operation type

This allows ranking workspaces by usage over any historical period.

Reference:
Log Analytics integration
https://learn.microsoft.com/power-bi/transform-model/log-analytics/desktop-log-analytics-configure

5. Is there a way to analyze which DAX caused high interactive usage?

The Metrics App shows:

• Workspace

• Item

• Operation

• User

But it does not show the exact DAX query text.

For detailed DAX analysis, use:

• XMLA endpoint

• SQL Server Profiler

• DAX Studio

Premium XMLA connectivity documentation:
https://learn.microsoft.com/power-bi/enterprise/service-premium-connect-tools

This is the supported method for tracing long-running queries.

6. What solutions should be considered if interactive or background usage is high?

If interactive usage is high:

• Optimize DAX calculations

• Reduce heavy visuals per page

• Avoid high-cardinality columns in visuals

• Use Aggregations

• Educate heavy users

If background usage is high:

• Stagger refresh schedules

• Use Incremental Refresh

• Optimize Power Query folding

• Reduce concurrent refreshes

Microsoft workload guidance:
https://learn.microsoft.com/fabric/enterprise/powerbi/service-admin-premium-workloads

Performance guidance:
https://learn.microsoft.com/power-bi/guidance/power-bi-optimization

7. Is there an API to create a custom capacity report?

Yes.

The Power BI REST API provides Admin endpoints such as:

• Get Activity Events

• Get Capacities

• Get Refresh history

Admin API reference:
https://learn.microsoft.com/rest/api/power-bi/admin/get-activity-events

Note: Activity Events provide audit data. For detailed capacity metrics, diagnostic log export is required.

8.  Where is capacity metric data stored? How can I access it?

There are two storage layers:

1. Microsoft-managed telemetry (used by the Metrics App)

   • Retention: ~14 days

   • Not directly accessible

2. Your configured Diagnostic export destination

   • Log Analytics / Storage / Event Hub

   • Retention depends on your configuration

Access requires enabling Diagnostic Settings.

References:
Metrics App overview
https://learn.microsoft.com/power-bi/enterprise/service-premium-gen2-metrics-app

Diagnostic export
https://learn.microsoft.com/power-bi/transform-model/log-analytics/desktop-log-analytics-configure

9.  How to achieve more than 14 days of data for root-cause analysis?

The only supported approach is:

1. Enable Diagnostic Settings

2. Export telemetry to Log Analytics

3. Retain data long-term

4. Build a custom semantic model

5. Create governance dashboards to analyze:

   • Monthly CPU saturation

   • Autoscale triggers

   • Workspace-level usage

   • Dataset-level consumption

For DAX-level root cause, use XMLA tracing tools.

Final Conclusion

• Capacity Metrics App = 14-day monitoring window

• Long-term history = Diagnostic log export

• Monthly CPU spikes & autoscale events = Query exported logs

• Exact DAX analysis = XMLA / Profiler tools

• Custom reporting = REST APIs + exported telemetry

All the above is aligned with official Microsoft documentation and supported monitoring architecture.

Hope this clarifies everything clearly and definitively.