This blog post will explain how to capture the data from real-time events for Fabric Operation Events and store the results in a Lakehouse.

My approach is to use a Python notebook to query Eventhouse.

The reason for this is the Python notebook runs very quickly and because it consumes very little Capacity Units, it is a very efficient way to store the Fabric Operational Events to be analyzed over a long period of time.

Here is my previous blog post where I detailed how to set up the Fabric Operational Events: https://www.fourmoo.com/2026/09/09/monitoring-microsoft-fabric-capacity-usage-with-operation-events/

Getting the Source Details

Before running the notebook, I had to get the following details

Eventhouse URI

I had to get my Eventhouse URI so that I could query the Eventhouse.

  • I went into my Eventhouse

1. I make sure I have selected my Eventhouse where I am storing the events

2. I made sure to expand the Database Details

3. I then copied the Ingestion URI

Lakehouse Details

I then got the details for my Lakehouse where I want to store the details

  • To do this I opened my Lakehouse.
  • Then in the URL for the Workspace ID I got the GUID after /groups/
  • For the Lakehouse GUID I copied the GUID after /lakehouses

What the notebook does

There are 2 things that the notebook does (And Yes I did use AI to create some of the code as well as my own skills)

The first part is where it is querying the Eventhouse and aggregates it to Hourly, so I could see the hourly trends over time.

The second part is where I am aggregating the data to every 30 seconds to represent what is the Capacity metrics App.

This then merges the data to the 2 Lakehouse tables.

I now have my data stored which I then use for Power BI report and longer-term analysis.

Summary

In this blog post I have shown you how I get data from the Eventhouse and store it in an aggregated form.

You can find the notebook I used here: https://github.com/GilbertQue/Fabric/blob/main/Blog-CapacityMonitoringItems.ipynb

Thanks for reading, comments or suggestions are always welcome!