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Category: Deployment

A Primer on SSIS Package Deployment

Andy Brownsword gives us a blast from the past:

Configurations for Integration Services packages allow us to tailor their execution without needing to redeploy. There are two main ways to manage these configurations – Package Configuration and Project Configuration. In this post we’ll look at the Package Configuration approach.

Package deployment was the original approach, though as Andy points out, it’s no longer the default.

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Building an Elastic Job with Bicep

Josephine 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.

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Deploying Power Apps as Solutions or Apps

Deborah Melkin explains deployment:

One of the big challenges I had was how to move the app from different environments. Following best software development practices, we have a development environment in our Power Platform that uses a development database as well as a production environment that points to a different production database. This has been a multi-step process with hurdles along the way.

Read on for Deborah’s thoughts and some of the issues she hit along the way.

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CI/CD in GitHub

I have a new video:

In this video, I explain what continuous integration (CI) is, disambiguate continuous delivery from continuous deployment (CD), and see how you can perform CI/CD operations using GitHub Actions.

Read on to see what these terms mean and an example of how it all works with .NET projects.

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Infrastructure as Code in GitHub

I have a new video:

In this video, we look at how to perform Infrastructure as Code in GitHub. We take a Bicep script and generate new Azure resources using it and GitHub Actions.

The video includes a very brief primer on Azure Resource Manager (ARM) and Bicep, and then gets into how you can use GitHub Actions to keep your Azure resources configured the way you expect.

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DBCC CLONEDATABASE and Production Deployments

Madhumita Tripathy takes a step back:

DBCC CLONEDATABASE command generates a schema-only copy of a database. Effective March 1, 2025, Microsoft will discontinue support for the use of the DBCC CLONEDATABASE command as a tool to copy database to production environment. The command is intended for diagnostic and troubleshooting purposes only. Any use of the command for purposes other than those specified will not be supported by Microsoft from the aforementioned date. All editions of Microsoft SQL Server 2016 and later versions are affected by this change.

Now I’m a bit curious about the why behind this post.

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Learning about GitHub Actions

I have a new video:

In this video, we dig into GitHub’s process for executing code: GitHub Actions workflows. We’ll learn what Actions and workflows are, how we can create them from scratch, and how to incorporate Actions from the GitHub Marketplace into our own workflows.

Along the way, I describe what GitHub Actions workflows are and we build a simple one. I’ll have more videos coming up that expand on GitHub Actions and show you more of what you can do with them.

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Using Feature Flags with Data Projects

Ben Johnston builds out feature flags:

My motivation for writing this summary was an interaction with a project owner that didn’t understand why we couldn’t use feature flags directly in Power BI to control the user interface. This was different from our other deployments, so it took a few rounds of explanations to convince them that our use case didn’t support feature flags. It’s an oversimplification to say they can’t be used in data projects. They can be used in Power BI and other reporting tools, but the implementation is different from coding languages and their usage is limited in comparison. Feature flags can also be used in ETL tools, data engines, ETL tools, and other data tools, but with some caveats. Sometimes those caveats are severe enough that you will want to carefully consider how you use feature flags in your data projects.

Read the whole thing. The way Ben lays things out reminds me of why I historically haven’t been the biggest fan of feature flags, though they can be quite useful for application development purposes.

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Against Publishing Power BI Model Changes from PBI Desktop

Soheil Bakhshi has some thoughts:

In a previous post, I shared a comprehensive guide on implementing Incremental Data Refresh in Power BI Desktop. We covered essential concepts such as truncation and load versus incremental load, understanding historical and incremental ranges, and the significant benefits of adopting incremental refresh for large tables. If you missed that post, I highly recommend giving it a read to get a solid foundation on the topic.

Now, let’s dive into Part 2 of this series where we will explore tips and tricks for implementing Incremental Data Refresh in more complex scenarios. This blog follows up on the insights provided in the first part, offering a deeper understanding of how Incremental Data Refresh works in Power BI. Whether you’re a seasoned Power BI user or just getting started, this post will provide valuable information on optimising your data refresh strategies. So, let’s begin.

Read on for plenty of detail, including your available options and how to use them.

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