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Day: March 20, 2026

Azure SQL Managed Instances and CPU

Published 2026-03-20 by Kevin Feasel

Joe Obbish answers a question:

I’m going to open with a perhaps controversial statement: “when you buy 4 vCores on the Azure SQL Managed Instance platform, what you’re actually buying is 2 physical cores presented as 4 hyperthreaded cores to SQL Server”. That means that if you have 8 physical cores on your SQL Server machine today then your starting Managed Instance vCore equivalent count could be closer to 16 vCores instead of 8. Perhaps this is already well known to everyone else, but I couldn’t find any (accurate) writing on this topic so I gave it a shot.

Click through for a series of tests that do not look great for SQL Managed Instances. And it doesn’t even have to do with storage this time. Azure SQL Managed Instance has to be one of the most disappointing Azure products, simply on hardware grounds alone.

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What’s New in SQL Database for Fabric

Published 2026-03-20 by Kevin Feasel

Idris Motiwala makes some announcements:

The new Migration Assistant for SQL databases simplify moving SQL Server and Azure SQL workloads into Fabric. Designed for SQL developers, it imports schema via DACPACs, identifies compatibility issues, and provides clear, actionable guidance before migration. Built-in assessment and data copy workflows help teams move from evaluation to cutover with less manual effort, preserving existing SQL skills while accelerating time to value on Fabric’s unified analytics platform.  Ready to simplify your SQL migration journey? We will begin rolling this out in the coming weeks, and it will soon be accessible through the Fabric portal.

Click through for more things that are currently in place, including several items that are now GA.

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Prevent Future Date Spillage in Power BI Visuals

Published 2026-03-20 by Kevin Feasel

Kenneth Omorodion lives in the now:

For Power BI developers, one very common (and frustrating) issue is when measures spill into future dates on charts especially when working with some time intelligence DAX calculations (e.g. MTD, YTD, etc.), date dimensions that extend beyond current date, and forecast-enabled tables.

In Power BI charts (e.g. line or bar charts), apart from dates with data, measures are also evaluated for every date on the axis, regardless if there is data or not. For example, if my dates table runs to 2026 December, but my data table only have data up to today, when I create a measure that leverages MTD or YTD for example, Power BI will tend to evaluate the measure for all dates that exist in my Dates table, unless I explicitly apply a logic to prevent this behaviour. This behaviour might result in flat lines on charts, misleading trends, and confusion to intended users.

In this article, I will demonstrate some examples of approaches to prevent or manage future dates spillage in Power BI.

Click through for some tips.

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Group Managed Service Accounts and Failover Cluster Instances

Published 2026-03-20 by Kevin Feasel

Deepthi Goguri covers the real value of gMSA accounts:

A Failover Cluster Instance (FCI) is a SQL Server high-availability solution where multiple servers share the same storage. If the active node fails, SQL Server automatically fails over to another node with minimal downtime.

You need to follow all the steps mentioned in the first blog post, which you can find here.

From there, Deepthi covers how to change the SQL Server service account to use a gMSA if you have FCI or other high availability setups for SQL Server.

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What’s New in OneLake

Published 2026-03-20 by Kevin Feasel

Josh Caplan provides an update:

With shortcuts and mirroring in OneLake, you get zero-copy, zero-ETL capabilities to connect your multi-cloud data estate. Whether your data sits in Azure, AWS, Google Cloud, or Oracle, on-premises, or across platforms like SAP, Dataverse, Snowflake, and Azure Databricks, you can connect it to OneLake without data movement or duplication. No more sprawling ETL pipelines. No more out-of-date copies. No more data silos.

Today, we’re expanding mirroring to now include SharePoint lists (Preview) and adding mirroring via shortcuts for Azure Monitor and Dremio (Preview). We are also releasing mirroring for Oracle and SAP Datasphere into general availability. Beyond these core mirroring capabilities, we are now introducing extended capabilities in mirroring designed to help you operationalize mirrored sources at scale. These capabilities include Change Data Feed (CDF) and the ability to create views on top of mirrored data, starting with Snowflake and will be offered as a paid option.

Click through for more of what came out of FabCon.

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