A Fine Slice Of SQL Server
A Fabric Pipeline uses JSON as source code. They are also saved in repositories as JSON.
We first idea we get is editing the pipeline in JSON format. We can copy the JSON and create new pipelines with small variations, making changes directly on the JSON.
However, at first sight we get disappointed, because the pipeline doesn’t allow the JSON to be edited. We have the option to view the JSON, but nothing else.
Read on to see how to tell the Fabric pipeline who’s boss.
Comments closedPaul Andrew makes a comparison:
Microsoft SQL Server and Azure Databricks over the many years I’ve been working in the data/IT industry have easily become my two favourite data processing tools. When Databricks became a first-class resource in Microsoft Azure, it was a big moment for the evolution of the data platform architectures I’ve designed and built (but architecture isn’t the focus for this blog). That said, rather than considering the tooling and technology as an evolution, I find a lot of people drawing comparisons between the products. This often leads to confusion and friction, as they are ultimately offering a lot of different capabilities, with only some common areas where comparisons could be made.
Read on for Paul’s thoughts. Spoilers: I agree with pretty much all of it.
Comments closedJosephine Bush flexes some muscles:
Bicep is an open-source Domain-Specific Language (DSL) that simplifies the process of deploying Azure resources. It is an abstraction layer on top of Azure Resource Manager (ARM) templates, making it easier to write and understand infrastructure code. Bicep lets you describe your Azure infrastructure using a cleaner and more concise syntax than traditional ARM templates.
It’s definitely easier to read and work with Bicep than directly with ARM template JSON. Larger Bicep scripts can still be pretty confusing, but it’s definitely easier to write and maintain.
Comments closedMicrosoft has released a new learning path yesterday, Build AI Apps with Azure Database for PostgreSQL. I had the good fortune to write two of these modules:
Click through for direct links for the two modules. The way we wrote these, you can do the modules in any order and they’re self-contained, so you can pick and choose which ones you’d like to do.
Comments closedAfter a lengthy period in Public Preview it seems, the boffins at Microsoft have finally pushed Elastic Jobs for SQL Azure DB to general availability. Hooray!
But what are Elastic Jobs? And why would I want to use them in SQL Azure DB?
That’s one of the things you’ll learn in this post.
Comments closedAndrew Pruski shows off Docker Build Cloud:
In a previous blog post we went through how to build a Docker container image from a remote (Github) repository.
Here we’re going to expand on that by actually building the image itself remotely, using Docker Build Cloud.
What we can do with Docker Build Cloud is instead of building the image locally and then having to push to a remote container registry (for example the Docker Hub), we can build remotely and then immediately push that image to the registry so that it is available for immediate use by say, our team members or deployment/testing pipelines.
Read on to see how it works.
Comments closedScott Klein performs a migration:
So, back to our customer. They essentially lifted and shifted their on-premises databases to Azure SQL Managed Instance and have been using it successfully for nearly two years. Again, this is awesome.
Last week they came to us and asked about reporting with Managed Instance. They were looking at data marts and data warehouses, but we needed more information. It turns out they have some people that just want the ability to query the databases, and potentially hook up Excel to these databases for data analysis.
The caveat is that the people I was talking to didn’t want to give the other group direct access to the production environment. Toootally get that. Yeah, like 100% get it. So, what are the options?
Read on for the solution Scott came up with.
Comments closedMartin Schoombee continues a series on orchestration in Azure Data Factory:
Before we dive into the details of the Data Factory pipelines, it is worth explaining the conceptual structure of my framework and its components. How it all fits together is important, and after reading the post on the metadata as well the pieces of the puzzle will hopefully start falling into place.
When I started thinking about what I’d like the framework to do, three conceptual layers started to emerge and we’ll review them from the bottom up:
Click through for the description of each layer.
Comments closedSam Garth troubleshoots an issue:
On a recent case, a customer was trying to restore a database from a storage account using a SAS token when they received the below error.
An exception occurred while executing a Transact-SQL statement or batch.
(Microsoft.SqlServer.ConnectionInfo)Additional information:
Cannot open backup device
‘https://storage.blob.core.windows.net/container/dbbackup_2024_03_21_121901.bak‘
Operating system error 86(The specified network password is not correct.).
RESTORE HEADERONLY is terminating abnormally. (Microsoft SQL Server, Error: 3201)
Read on for the troubleshooting steps Sam followed to solve the problem.
Comments closedKoen Verbeeck has a public service announcement:
Today I was having a nice discussion with some colleagues about Fabric and pricing/licensing came up. I mentioned an F2 is only around €250 a month, but a colleague said “no no, it’s over €300”.
There can be significant differences in prices for services based on region, not just for Microsoft Fabric, but also for a variety of services. This will depend on how new the hardware is, how much demand there is in the region, and a few other factors. Cloud Price does a good job of keeping track of VM pricing by region, and even tells you the cheapest region for each class of VM. For other services, you may have to trawl through Azure APIs and pricing pages to get the best deal.
Comments closed