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Category: Deployment

Deploying SQL Server via Ansible

Amit Khandelwal gives us another way of deploying SQL Server on Linux:

Today, we’ll look at how to automate SQL Server deployment and configuration on Linux. To automate our deployment, we will use the Ansible system role, which is available here.

Note: The Ansible system role that I use in this blog is a sample system role that is provided as is and for reference only. Microsoft and RedHat do not support this. However, I invite you to provide feedback and suggestions for improving the system role here: Issues linux-system-roles/mssql (github.com).

Read on for the instructions and a demonstration.

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Deploying Azure Policies via Terraform

Jonathan D’Aloia shows how you can use Terraform to work with Azure Policies:

As you may all know Terraform serves a great purpose in deploying resources and infrastructure into your Azure environment, however, Terraform can also be used to automate and consistently deploy Azure Policies which can be defined prior to any resources being generated. In this blog, I will cover how you can import policies into your Terraform State to then deploy into an Azure Resource Group in order to secure your landing zone prior to deploying any resources.

Click through for an example.

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Content Sharing with Power BI

Marc Lelijveld continues a series on going from small-scale to enterprise with Power BI:

Let’s start with the most important feature of the Power BI Service, sharing content! At the same time, this can be one of the most challenging ones. Especially since there are many ways to share content in Power BI. In my experience in enterprise organizations, I have seen a various ways of sharing content. Below I explain the different options there are, leading to a conclusion of my personal best practice.

But why is the way how we share content so important in relation to large enterprise solutions? Well, I believe that all centrally managed solutions should match (organizational) best practices. The way how the content is made available to the users is one of these best practices. It will help end users to find the content they are looking for, always at the same consistent location.

Read on for several techniques.

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Data Platform Deployments via Azure Test Plan

Kevin Chant shows off the power of Azure Test Plans:

In this post I want to cover using Azure Test Plans for Data Platform deployments. Because using it to manage test plans can be very useful.

By the end of this post, you will know what Azure Test Plans are and how they can be useful for data Platform deployments.

Click through to see how this feature in Azure DevOps works and how you can use it to test your deployments.

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Renaming a YAML Pipeline in Azure DevOps

Hamish Watson figures out what’s in a name:

I had created a pipeline using YAML – which was called InfrastructureAsCode as the YAMP file was in the root directory.

However I wanted to move it into a folder .\InfrastructureAsCode\pipelines\… and run the YAML file from there – as I would have a non-prod and PROD version of them (as the schedule was different for each).

Click through to see how Hamish was able to resolve this.

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Creating a dacpac for a Dedicated SQL Pool

Kevin Chant shows how to use Azure DevOps to create a dacpac for an Azure Synapse Analytics dedicated SQL pool:

By the end of this post, you will know how to create a dacpac for a dedicated SQL Pool within Azure Pipelines for your CI/CD deployments. Plus, how you can synchronize a database project created in Azure Data Studio with a Git repository in Azure DevOps.

In a previous post I covered how you can create a dacpac for an Azure Synapse Analytics dedicated SQL Pool using Azure Data Studio. In that post I stated that you could create a dacpac for the database project using Azure DevOps.

With this in mind, I will use the same database project that I created in that post.

Click through for the process.

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The Value of a Working Dev Environment

Tim Mitchell wants to talk about dev environments:

Let’s talk about your development environment.

Specifically, I’d like to chat with you about the virtual space where your data architecture team, software developers, and information curators do their development and testing work. A proper development environment is logically separated from the production environment, and is often further partitioned into different realms for initial development, data or functional validation, and user acceptance testing. For mature enterprise-ready environments, there is also usually a build and deployment process that automates the movement of code from one environment to the next, reducing the chance for human error when moving code through its paces and ultimately into the production environment.

I’d like optimistically to say that Tim is using strawmen here, but I’ve worked in (and sometimes created) pretty much each one of these.

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Integrating Power BI Deployment Pipelines with Azure DevOps

Marc Lelijveld shows how you can combine Power BI deployment pipelines with Azure DevOps:

Looking at the Power BI release plan, dataflow support for Deployment Pipelines is coming up shortly! Currently it is scheduled for June 2021 to reach the public preview state. Versioning and DevOps integration go hand-in-hand to our opinion. With Azure DevOps Git integration, we can overcome the versioning challenge while integrating with Azure DevOps at the same time, as described in the previous blog in 2019. Today, we release a new version of the DevOps implementation which uses native Power BI functionality. Stay tuned!

As we really like the metadata deployment and the ease of setup a pipeline in the Power BI Service, Ton and I decided to setup an Azure DevOps extension based on the recently released Power BI REST APIs for Deployment Pipelines. Although Microsoft promised to come-up with a native DevOps extension over time, we decided to go for it. Time to bridge the gap!

Read on for more details.

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Creating a dacpac for a Dedicated SQL Pool

Kevin Chant shows us how to build out a dacpac file for an Azure Synapse Analytics dedicated SQL Pool:

In reality, you can create a dacpac for a database that’s inside an Azure Synapse Analytics dedicated SQL Pool using a lot of the methods that you use to create them for SQL Server databases.

Azure Data Studio can be an appealing alternative SQL Server Data Tools (SSDT) for tasks like this. Due to various reasons. For instance, it’s a multi-platform solution that is easy to install.

With this in mind, I decided in this post to cover how to create a dacpac for an Azure Synapse Analytics dedicated SQL Pool using Azure Data Studio.

Click through to see how.

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