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Microsoft just added Logic Apps Automation to the mix. Technically, it’s a new SKU, but it brings so much more.

Let me tell you why I started using AI to modernize this blog. At first, it was just an expertiment, but it saved time, removed boring repetition, and let me focus on the parts that actually matter; cool examples, and opinions. :).

Are your tired of parametrizing dozens of pipelines via templates, maybe you want a more metadata driven approach, or simply you are hitting ADF temmplate parameter limits. If yes, this blog entry is for you.

I’ve been building Logic App workflows for AI agents lately-both autonomous and conversational patterns-and the experience is interesting. This post summarizes what I found from the current documentation and my own experiments.

Over the past decade, Azure Logic Apps has been my go-to for building reliable, scalable integrations without the hassle of custom code. Trust me, it’s transformed how I approach automation; let me share why.

This is the final wrap-up in our Unity Catalog migration series. These are the practical tips we landed on after the migration, the ones that would have saved us time if we had known them before we started.

The most important migration decision was not technical. It was about teams and roles. In Unity Catalog, the wrong role model makes the whole platform hard to operate.

In our platform, one of the first questions we answered was: what is a project in Unity Catalog? That decision shaped every later governance and onboarding choice.

One of the biggest surprises in our Unity Catalog migration was how much of the design depended on product limits. If you do not know which limits are soft and which are fixed, you can build a design that stops before it starts.

The most surprising part of our Databricks migration was this: without previews, we would not have finished. The features we used were not in plain sight, but they were the only path through several blockers.