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Month: October 2026

Entry Points and Graph Neighborhoods with DiskANN

Published 2026-10-21 by Kevin Feasel

Mala Mahadevan tries something out:

I was experimenting with vector search in SQL Server 2025 using approximately 3.8 million Hacker News articles that that I used for my talk on SQL Server-based vector search feature at EightKB. I generated two sets of embeddings from the same articles: one stored as FP32 (32-bit floating point) and the other as FP16 (16-bit floating point). Both sets contained the same articles and used DiskANN vector indexes.I used a query as below to find articles similar to a selected example.

What Mala found was that FP16 queries could sometimes take longer and require more reads than FP32 queries, which doesn’t make sense on its face. Click through to see two experiments she devised to come up with the answer.

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Clock Changes and SQL Server

Published 2026-10-21 by Kevin Feasel

Dualcore DBA turns back time:

In this post we’ll look at the behaviour of a SQL Server application that needs to deal with events that are logged over the period of a UK clock change where the clocks change from GMT (Greenwich Mean Time) to BST (British Summer Time).

The data itself is in UTC (which is good), but getting from UTC to the user’s local time can be a major challenge, especially in T-SQL. There are application libraries that make this a lot easier, which is why I recommend bouncing this up to the application layer whenever possible.

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Lessons Learned from Troubleshooting with LLMs

Published 2026-10-21 by Kevin Feasel

Grant Fritchey spends a weekend:

Grant Fritchey walks through a real troubleshooting saga – using Wine, a shim DLL, a misconfigured registry entry, and a lot of trial and error – to get a BridgeCom Maverick radio’s Windows CPS running on Linux Mint.

Along the way, repeated dead ends revealed a pattern: AI tools stay locked onto whatever direction you last pointed them, and it’s up to you to redirect, request alternatives, and demand measurement over guesswork.

In this article, Grant shares everything he learned from the experience, including 8 key takeaways to help you avoid similar trouble when using AI in the future.

Grant takes us through the story and shares eight tips for better troubleshooting along the way. Oh, and Wine is notoriously finicky, so I can totally get why it’d take a while to sort out the issues Grant had.

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Auto-Indexing in SQL Server

Published 2026-10-21 by Kevin Feasel

Brent Ozar unveils a secret:

It’s super simple: the installation file, AutoIndex.sql, creates an Agent job and a series of stored procedures including auto_create_index and auto_drop_index. They watch the index usage and missing index DMVs, log their findings to tables, and trend the data over time in order to figure out which indexes to create, and which ones to prune back because they’re only slowing you down.

And it’s even free!

I enjoy these posts, where Brent goes back to ideas people had 20+ years ago. It really shows how creative the SQL Server development team was back in the day.

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XACT_ABORT vs TRY_CATCH

Published 2026-10-21 by Kevin Feasel

Jared Westover explains the difference:

After creating a SQL script and a pull request, a savvy developer left a comment on the PR because they were confused about why I was using both XACT_ABORT and TRY…CATCH. They thought that including both in one script was redundant. That got me thinking: is it true that setting XACT_ABORT ON makes TRY…CATCH redundant?

The most interesting part of this post is the cases in which you would use both in the same script.

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Working with the Power BI Gantt Chart

Published 2026-10-20 by Kevin Feasel

Valerie Junk tries out a new built-in visual:

Almost every company runs projects or has some kind of timeline, and most of the time that planning is tracked somewhere else, for example, in an Excel file or in another tool. But at the same time, most of our data is already in Power BI. Until now you basically had two options:

  • A custom visual which might need a paid license.
  • A workaround you build yourself, like a stacked bar chart or a matrix with conditional formatting, which works, but every change means fixing your own workaround.

It looks fairly reasonable, though I do hope the Power BI team is able to relax some of those restrictions before it goes GA. Because I’m only so much of a masochist, I didn’t look up whether Power BI Report Server will include this visual. Maybe it will three years from now.

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Full-Text Indexing and Power BI Semantic Model Refresh Times

Published 2026-10-20 by Kevin Feasel

Chris Webb runs a test:

The September release of Power BI saw the introduction of a powerful new feature: full text indexing, which makes searching and filtering on text columns much faster and enables the use of the new TextContains() and TextSimilarity() DAX functions. You need to enable it on a per-column basis and when you do that you have the option to rebuild the full-text index for those columns when you do a Full refresh or when you do a refresh of the type Indexes. So the big question is: how long does it take to build a full-text index on a column and what impact will it have on your overall refresh times?

Read on for that answer in a reasonably-sized dataset containing street addresses.

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Building an Isolated Hyper-V Network for Azure Communications

Published 2026-10-20 by Kevin Feasel

Jordan Boich continues a series on networking for the DBA:

Before I even touched anything related to Azure, I needed to make sure that nothing I did could impact my Wi-Fi at home. The whole reason why I love home lab environments so much is because it is contained end to end. If I break something in my lab, it’s comforting to know that nothing important will ever be in that blast radius. This post is all about hitting the prerequisites that don’t touch anything important like setting up an isolated lab network, save points for my existing VMs, license checks, and creating an Azure subscription that doesn’t touch anything else.

Read on to see what Jordan did.

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Connecting Azure Databricks to a Microsoft Foundry AI Gateway

Published 2026-10-20 by Kevin Feasel

Drew Furgiuele connects the dots:

While some people might look at the different capabilities and think this is an “either/or” scenario, the reality is that most Azure customers are going use (or even need to use) both: developers building apps and agents in Databricks, for example, may want to leverage a model or other agent deployed in Foundry. Meanwhile, developers in Foundry may need to call a Databricks managed MCP service.

These types of calls aren’t all that difficult; in fact, both platforms provide built-in connectors or UI solutions to make this happen: simply provide the service endpoint, pick your authentication method, and you’re pretty much done. However, the introduction of the respective gateways, especially on the Foundry side, can make this just a little more complicated. Let’s look at one example.

Click through for that issue and how Drew was able to work around it.

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Creating an Azure DevOps Deployment

Published 2026-10-20 by Kevin Feasel

Reitse Eskens deploys some Microsoft Fabric assets:

Let me generalise first: you can essentially choose two options to promote your hand-crafted and superior code compared to anyone else from development to production. The first way is to use the Fabric deployment pipelines. These are essentially copy actions that move the development state to production. Option two is to use either GitHub Actions or Azure DevOps pipelines.

The main issue I’ve seen with the Fabric deployment pipelines is that the deployed code still references the development environment. This results in your notebook running in production and happily writing the results in the development lakehouse. To mitigate this, you can add actions to the Fabric pipeline, check out the newly announced Fabric deployment plans, or remember to update all references.

Click through for a high-level depiction of the process.

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