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Category: Microsoft Fabric

When Fabric Mirroring Doesn’t Copy Rows

Published 2026-04-16 by Kevin Feasel

Koen Verbeeck troubleshoots an issue:

A short blog post about an issue with Fabric Mirroring (with Azure SQL DB as the source) that I’ve managed to run into, twice. I’ve set up mirroring by creating a connection using a service principal and this principal has the proper permissions on the source database. Configuring the replication was without issues, and the replication status went from “starting” to “running”. However, no rows were being copied. The tables were all listed in the monitoring pane, but the counters of “rows replicated” remained at zero. There were no errors in the logs (in OneLake) and nothing suspicious was mentioned in the monitoring.

This was a rather pernicious issue. Based on Koen’s explanation, it sounds like there’s no way to know what the actual problem was.

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“Analyze data with” Updates in Microsoft Fabric

Published 2026-04-15 by Kevin Feasel

Tzvia Gitlin Troyna shows off some new functionality:

As Microsoft Fabric continues to converge analytics experiences across workloads, one of the most important steps forward is reducing friction in how users move from raw data to insights. With the latest integrations, the Eventhouse Endpoint is now deeply embedded into the “Analyze data with” entry points across Lakehouse, Data Warehouse, and Eventhouse, bringing a consistent, discoverable, and powerful way to analyze data using SQL Endpoint and Notebooks, both new and existing.

Click through to see what this means. This is a preview feature, but it does help tell the story a bit better around Fabric being a coherent entity rather than a bunch of products slapped together.

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OneLake File Explorer now GA

Published 2026-04-14 by Kevin Feasel

Harmeet Gill announces general availability of OneLake File Explorer:

Imagine this scenario: You’re a data engineer working with files on your local machine—CSV extracts, Excel files from the business, or intermediate outputs generated on your PC. Your goal is to run a Fabric pipeline, explore the data in a notebook, or train a model in Microsoft Fabric.

Traditionally, that means uploading files through a browser, writing scripts to push data into the lake, or coordinating with someone else who has access. It works—but it adds friction.

OneLake File Explorer removes that friction by bringing OneLake directly into Windows File Explorer.

It’s taken about 3 years to get to this point, but I’m glad to see it get past the preview hurdle.

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Updates to Fabric Eventstream

Published 2026-04-10 by Kevin Feasel

Alicia Li and Arindam Chatterjee share some updates:

Over the first quarter of 2026, Fabric Eventstreams shipped meaningful improvements across three themes that have repeatedly come up in feedback from our broad community of customers and partners: broader connectivity, richer real-time processing, and secure enterprise‑ready networking and operations.

This post highlights some of the most impactful new Eventstreams-related features and capabilities delivered between January and March 2026.

Click through to see what’s new. Some of this is GA, though a good amount is in preview.

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Mirroring SQL Server 2025 to Microsoft Fabric

Published 2026-04-10 by Kevin Feasel

Reitse Eskens digs in:

Maybe you’ve read my blog post in the DP-700 certification series about mirroring data. You can find that one here. This blog will be longer and more technical. And involve SQL Server. To make reading a little easier, I’ve listed the Microsoft Learn pages at the end of this blog post.

While writing the DP-700 post, I realised I wanted to dig a little deeper. Not only because I’m presenting a session on this subject, but also to learn more about the processes behind it. And, there’s SQL Server involved, something I still have a soft spot for in my heart. Or maybe even more than that.

The fact that your SQL Server instance has to be Arc-enabled is a bit annoying.

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Shortcut Transformations now GA in Microsoft Fabric

Published 2026-04-08 by Kevin Feasel

Pernal Shah transforms some data:

Organizations today manage data across multiple storage systems, often in formats like CSV, Parquet, and JSON. While this data is readily available, turning it into analytics-ready tables typically requires building and maintaining complex ETL pipelines.

Shortcut transformations remove that complexity.

With Shortcut transformations, you can convert structured files referenced through OneLake shortcuts into Delta tables without building pipelines or writing code.

This currently works for CSV, Parquet, and JSON data and does cut out a very common step for raw-layer transformation.

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ANY_VALUE() in Fabric Data Warehouse

Published 2026-04-07 by Kevin Feasel

Jovan Popovic notes a feature going GA:

Fabric Data Warehouse now supports the ANY_VALUE() aggregate, making it easier to write readable, efficient T-SQL when you want to group by a key but still return descriptive columns that are functionally the same for every row in the group.

Right now, this is only available in the Fabric Data Warehouse, so no Azure SQL DB, Managed Instance, or box product support at this time.

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Role-Playing Dimensions and Direct Lake Semantic Models

Published 2026-04-06 by Kevin Feasel

Chris Webb finds a workaround to something that used to work:

Back in September 2024 I wrote a blog post on how to create multiple copies of the same dimension in a Direct Lake semantic model without creating copies of the underlying Delta table. Not long after that I started getting comments that people who tried following my instructions were getting errors, and while some bugs were fixed others remained. After asking around I have a workaround (thank you Kevin Moore) that will avoid all those errors, so while we’re waiting for the remaining fixes here are the details of the workaround.

I look at the set of steps needed to do this and say there has to be a better way.

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Microsoft Fabric ETL and the Air Traffic Controller

Published 2026-04-02 by Kevin Feasel

Jens Vestergaard rethinks a metaphor:

In February 2025 I wrote about building an event-driven ETL system in Microsoft Fabric. The metaphor was air traffic control: notebooks as flights, Azure Service Bus as the control tower, the Bronze/Silver/Gold medallion layers as the runway sequence. The whole system existed because Fabric has core-based execution limits that throttle how many Spark jobs run simultaneously on a given capacity SKU.

The post was about working around a constraint. You could not just fire all your notebooks at once. You needed something to manage the queue.

More than a year on, it is worth being honest about what held up and what has changed.

Read on to see what has changed in this past year and how Jens thinks of it today.

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