A Fine Slice Of SQL Server
Andy Brownsword creates a card:
Last week we looked at utilising Teams to make notifications more collaborative. This week I want to show how we can add more visual and interactive elements by adopting Adaptive Cards.
Andy shows the process for creating an adaptive card, as well as some of the gotchas you might run into along the way.
Leave a CommentKevin Chant announces a new Azure DevOps extension:
This post covers how you can simplify Microsoft Fabric deployments with “Deploy Microsoft Fabric items with fabric-cicd”. Which is an Azure DevOps extension that I recently published.
To manage expectations, this post shows how to start working with the extension and its associated task within the GUI-based classic release pipelines in Azure DevOps. Like in the below screenshot.
Read on to see how the extension works.
Leave a CommentChris Webb covers a new feature:
I have been spending a lot of time recently investigating the new performance-related features that have rolled out in Fabric Dataflows over the last few months, so expect a lot of blog posts on this subject in the near future. Probably my favourite of these features is Preview-Only steps: they make such a big difference to my quality of life as a Dataflows developer.
The basic idea (which you can read about in the very detailed docs here) is that you can add steps to a query inside a Dataflow that are only executed when you are editing the query and looking at data in the preview pane; when the Dataflow is refreshed these steps are ignored. This means you can do things like add filters, remove columns or summarise data while you’re editing the Dataflow in order to make the performance of the editor faster or debug data problems. It’s all very straightforward and works well.
First up, that feature is pretty interesting, though I could see things break if you only do your testing in the preview pane. Second, what Chris does with this is quite interesting.
Leave a CommentKoen Verbeeck said something bad:
A while ago I blogged about a use case where a pipeline fails during debugging with a BadRequest error, even though it validates successfully. If you’re wondering, this is the helpful error message that you get:
Click through for an image of the 400 Bad Request message, how Koen fixed it originally, and then a different scenario in which that 400 message popped up.
Ultimately, a 400 Bad Request comes down to “You sent me information that doesn’t make sense and I can’t fulfill your request, so fix it, dummy.” 400 status codes are very rude and insulting. Especially 418–that thing has a mouth like a sailor’s.
Leave a CommentKoen Verbeeck glues together several technologies:
Quite the title, so let me set the stage first. You have an Azure Data Factory instance (or Azure Synapse Pipelines) and you have a couple of linked services that point to Fabric artifacts such as a lakehouse or a warehouse. You want to deploy your ADF instance with an Azure Devops build/release pipeline to another environment (e.g. acceptance or production) and this means the linked services need to change as well because in those environments the lakehouse or warehouse are in a different workspace (and also have different object Ids).
When you want to deploy ADF, you typically use the ARM template that ADF automatically creates when you publish (when your instance is linked with a git repo). More information about this setup can be found in the documentation. To parameterize certain properties of a linked service, you can use custom parameterization of the ARM template. Anyway, long story short, I tried to parameterize the properties of the Fabric linked service.
Read on to see how that went, as well as what you need to do to solve this issue.
Leave a CommentAndy Brownsword sends a message:
Whether running Data Factory, Synapse, or Fabric pipelines, things go wrong – and the de facto response is to send an email. We’ve looked at sending emails from pipelines before, but at scale they can become noise and are easy to ignore.
A more effective option is to surface alerts where collaboration already exists, such as Teams.
In this post we’re going to start looking at using Teams and consolidate notifications into a channel. This functionality gives team members visibility, the ability to update in threads, and the option to tag people for a tighter response loop than typical emails bring.
Click through for the process.
Leave a CommentMihir Wagle announces a new preview capability:
Power Query has long been at the center of data preparation across Microsoft products—from Excel and Power BI to Dataflows and Fabric. We’re introducing a major evolution: the ability to execute Power Query programmatically through a public API.
This capability turns Power Query into a programmable data transformation engine that can be invoked on demand through a REST API from notebooks, pipelines, and applications. Whether you’re orchestrating data pipelines, building custom data apps, or integrating Power Query into larger workflows, this API unlocks new flexibility and automation.
Click through for an overview of what’s available.
Leave a CommentMichael Bourgon writes a script:
I hate creating SSIS. I also hate creating ADF via GUI. So here’s a way to do it with python.
There are a couple prereqs (below), specifically an ultra-configurable Linked Service and Dataset.
Click through for an example of how it works.
Leave a CommentLaura Graham-Brown shows another way to use variable libraries:
One of the popular low-code tools within Microsoft Fabric is the Gen2 Dataflow. Power BI report builders already know some Power Query. So armed with this knowledge is a popular starting point to load data into Microsoft Fabric. Adding values from the Variable Library in a Dataflow is an obvious plan to make it more future proof and to work better with Deployment pipelines.
I will confess the first time I tried these I could not get them to work till I read the instructions correctly. So they do work just understand the limitations!
To be fair, following instructions is one of the most challenging things to do, it seems.
Comments closedPaul Hernandez builds a (virtual) network:
Mirroring has been a transformative technology for data integrations tasks since the early Microsoft Fabric days. Moreover, this feature has been called “pain killer as a service” in community posts. In many projects, data sources to be mirrored are behind private networking and for security reasons they are not accessible using public internet. If you want to mirror, for example, an Azure SQL database, you’ll need a data gateway. According to the official docs: “If your Azure SQL Database is not publicly accessible and doesn’t allow Azure services to connect to it, you can set up virtual network data gateway or on-premises data gateway to mirror the data”.
In this post I’ll show you step-by-step how to set up connectivity to be able to use mirroring when Azure SQL allows only private access.
There are several steps involved, but the end result is worth it compared to not having the data at all or needing to make it accessible over the Internet.
Comments closed