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Category: Deployment

Deploying ADS Database Projects Manually

Elizabeth Noble continues a series of videos on database projects in Azure Data Studio:

This week, we’ll talk about one of the easier ways to deploy your database changes. One of the benefits of database projects is that they can generate data-tier applications (DAC). The data-tier applications can be bundled into what is called a DACPAC. This is a collection of files that can be used to deploy your database.

Click through for the video.

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Issues Deploying Azure Synapse Analytics via ARM Template

Paul Andrew hits on some growing pains:

Just last week we heard the announcement from Microsoft that Azure Synapse Analytics is now generally available (GA)… A full year on, plus a few weeks, since first seeing Synapse at the big USA conferences in November 2019.

Today I’ve been attempting to use the resource with a view to implementing it for several customer projects. Although GA, it would seem that many part of the technology are far from ready.

In this brief blog I’m exposing some of the pain I’ve faced so far in simply trying to deploy a second instance of Azure Synapse Analytics using ARM templates.

Click through for three that Paul found. I’d expect that most of these will be tidied up in the next few months.

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Deploying to Multiple SQL Server SKUs with Azure DevOps

Kevin Chant wants to deploy to all of the SQL Servers:

To give the above pipeline a bit more context the below types of SQL Server databases were updated after being unit tested (initial unit testing yaml courtesy of Sander):

– Three SQL Server 2019 instances in three Docker containers. Representing Integration, Staging and Production environments.
– At the same time the Git repository in Azure Repos would sync with a GitHub Repo. Which would then start a GitHub Action to update another database.
– An Azure SQL Database.
– Finally, a Synapse Analytics SQL Pool was also updated.

Read on to learn how.

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Automating Database Deployments: Why Not?

Grant Fritchey asks a question:

Building out processes and mechanisms for automated code deployments and testing can be quite a lot of work and isn’t easy. Now, try the same thing with data, and the challenges just shot through the roof. Anything from the simple fact that you must maintain the persistence of the data to data size to up time, and you have real problems in front of you.

However, adopting database deployment automation and testing has enormous benefits. Faster, safer, production deployment enhances the protection built around your production systems. Whether we want to use the loaded term of DevOps or not, the benefits of this style of development and deployment are easily documented and measured.

So, why are so few people doing it?

Grant gives some of the outline and lays out one response. I am seeing a lot more automation over time, but one underappreciated facet in this is a lack of trust for automated processes from humans. I think a good percentage of DBAs don’t trust that the automated process will get things correct, especially when dealing with complex chains of dependencies. An automated process may be less likely to make a mistake in a step, but it will also be unable to reason through an ambiguity and could perform an undesirable action in the event of unexpected circumstances. That’s a pretty big risk for DBAs who are concerned about their data. I can see a few other reasons as well, but this is one which I don’t hear often enough in these discussions.

Also, Grant asks people to fill out the State of Database DevOps survey, especially those people who are not automating database deployments.

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Deploying to Azure SQL Database via GitHub Actions

Kevin Chant shows us how to use GitHub Actions to deploy updates to Azure SQL Database:

After my last post I wanted to test deploying to Azure SQL Database using GitHub Actions. To check that it all runs smoothly.

By the end of this post you will have some ideas about how you can deploy Azure SQL Databases using GitHub Actions. Both for a basic test and more complex deployments.

In my last post here I showed you how you can use GitHub Actions to deploy a free monitoring framework called SQLWATCH to on-premises versions of SQL Server. I thought I would test using the same Azure SQL Deploy Action for Azure SQL database deployments.

Click through for the process.

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Deploy Reporting Services Projects with Powershell

Aaron Nelson has a pair of new Powershell cmdlets:

I built two new PowerShell commands to deploy SSRS projects, and they have finally been merged into the ReportingServicesTools module. The commands are Get-RsDeploymentConfig & Publish-RsProject. While the Write-RsFolderContent command did already exist, and is very useful, it does not support deploying the objects in your SSRS Project to multiple different folders in your report server. These two new commands can handle deployment to multiple folders.

Click through for details on each.

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Avoid Backup-and-Restore of SSISDB for Deployment

Andy Leonard recommends not using backup-and-restore as an approach of moving SSIS packages around:

First, please do not misunderstand. You should back up SSISDB just like you back up all other databases – especially in Production. You should also conduct Disaster Recovery exercises in which you restore SSISDB from the latest backup, or avail yourself of Always On availability groups and / or Windows Server Failover Clustering.

With that caveat in mind, read on to see why.

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SQL Server Installation Options for Testing Azure DevOps Deployments

Kevin Chant looks at the different options available when trying to set up local testing of SQL Server databases using Azure DevOps deployments:

One way you can work around the above scenario is to install multiple virtual machines. Now the first thing you might realize is that this will also take up a lot of compute and storage.

In reality, I use to use this method myself in the past using Hyper-V. To reduce the amount of storage the virtual machines used in Hyper-V I use to used parenting disks.

Since the introduction of containers and Docker this has become a less popular option. However, you can still read an old post of mine with tips in here.

Click through for additional options.

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