A Fine Slice Of SQL Server
When feeding a program with command line arguments, single quotes and double quotes make a significant difference.
Click through to see how the behavior is different between a command line shell like bash, versus the R programming language itself, as well as R Console.
Leave a CommentNikola Ilic presses the Easy button:
For the longest time, building a medallion architecture in Microsoft Fabric meant stitching together a small orchestra of moving parts: notebooks for the transformations, pipelines for orchestration, schedules for refresh, custom code for data quality checks, and the Monitor Hub for keeping an eye on whether anything actually worked. Every layer worked – until something didn’t, and then you had to figure out which layer broke, why, and which downstream layers got affected along the way.
If you’ve ever tried to debug a silver layer that didn’t update because the bronze notebook failed three hours ago, you know exactly what I’m talking about.
Then, at FabCon Atlanta in March 2026, materialized lake views (MLVs) went generally available. And the story they’re telling is simple: what if your entire medallion pipeline could be a few SELECT statements?
Let me walk you through the whole thing – what they are, how they work, what changed between preview and GA, and where they fit (and where they don’t) in your architecture.
Read on for that walkthrough.
Leave a CommentBack in December the FabricAI.Prompt() M function was released in Fabric Dataflows Gen2. Most of the people writing about it at that time, as in this great post by my colleague Sandeep Pawar, focused on calling this function for each row in a table – something that the UI in the editor makes easy. However the FabricAI.Prompt() function itself is a lot more flexible. You can use it to summarise whole tables of data as I showed here; you can also use it to generate sample data. This is similar to what I blogged about here where I got Copilot to generate M code that returned sample data but using FabricAI.Prompt() is maybe a bit simpler.
Click through to see how.
Leave a CommentAnthony Nocentino performs additional testing:
In my planned failover walkthrough, I showed what happens when you deliberately move the primary role to another replica. That’s the easy case. Now I want to show what happens when the primary pod just disappears unexpectedly, like during a node failure or a container crash. No graceful shutdown, no demotion, just gone.
I ran two test scenarios, each cycling the primary role across all three pods by force-deleting the current primary three times in a row. First, a 5GB TPC-C database idle. Then, that same 5GB database under sustained HammerDB TPC-C load. Six force-deletes total, six successful automatic failovers. I’ll walk through the error log from the promoted replica, the operator’s detection and recovery behavior, and the full timing data.
Read on to see how Anthony’s SQL Server Kubernetes operator handles when things go bump in the night.
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