Using the same Azure DevOps build steps for Terraform with different Pipelines with Task Groups to build an Azure Linux SQL VM

In my last post I showed how to build an Azure DevOps Pipeline for a Terraform build of an Azure SQLDB. This will take the terraform code and build the required infrastructure.

The plan all along has been to enable me to build different environments depending on the requirement. Obviously I can repeat the steps from the last post for a new repository containing a Terraform code for a different environment but

If you are going to do something more than once Automate It

who first said this? Anyone know?

The build steps for building the Terraform are the same each time (if I keep a standard folder and naming structure) so it would be much more beneficial if I could keep them in a single place and any alterations to the process only need to be made in the one place ๐Ÿ™‚

Task Groups

Azure DevOps has task groups. On the Microsoft Docs web-page they are described as


task group allows you to encapsulate a sequence of tasks, already defined in a build or a release pipeline, into a single reusable task that can be added to a build or release pipeline, just like any other tas


https://docs.microsoft.com/en-us/azure/devops/pipelines/library/task-groups?view=azure-devops

If you are doing this with a more complicated existing build pipeline it is important that you read the Before You Create A Task Group on the docs page. This will save you time when trying to understand why variables are not available (Another grey hair on my beard!)

Creating A Task Group

Here’s the thing, creating a task group is so easy it should be the default way you create Azure DevOps Pipelines. Let me walk you through it

I will use the Build Pipeline from the previous post. Click edit from the build page

Then CTRL and click to select all of the steps

Right Click and theres a Create Task Group button to click !

You can see that it has helpfully added the values for the parameters it requires for the location, Storage Account and the Resource Group.

Remember the grey beard hair above? We need to change those values to use the variables that we will add to the Build Pipeline using

Once you have done that click Create

This will also alter the current Build Pipeline to use the Task Group. Now we have a Task Group that we can use in any build pipeline in this project.

Using the Task Group with a new Build Pipeline to build an Azure Linux SQL VM

Lets re-use the build steps to create an Azure SQL Linux VM. First I created a new GitHub Repository for my Terraform code. Using the docs I created the Terraform to create a resource group, a Linux SQL VM, a virtual network, a subnet, a NIC for the VM, a public IP for the VM, a netwwork security group with two rules, one for SQL and one for SSH. It will look like this

The next step is to choose the repository

again we are going to select Empty job (although the next post will be about the Configuration as Code ๐Ÿ™‚

As before we will name the Build Pipeline and the Agent Job Step and click the + to add a new task. This time we will search for the Task Group name that we created

I need to add in the variables from the variable.tf in the code and also for the Task Group

and when I click save and queue

It runs for less than 7 minutes

and when I look in the Azure portal

and I can connect in Azure Data Studio

Altering The Task Group

You can find the Task Groups under Pipelines in your Azure DevOps project

Click on the Task Group that you have created and then you can alter, edit it if required and click save

This will warn you that any changes will affect all pipelines and task groups that are using this task group. To find out what will be affected click on references


which will show you what will be affected.

Now I can run the same build steps for any Build Pipeline and alter them all in a single place using Task Groups simplifying the administration of the Build Pipelines.

The next post will show how to use Azure DevOps templates to use the same build steps across many projects and build pipelines and will build a simple AKS cluster

The first post showed how to build an Azure SQLDB with Terraform using VS Code

The second post showed how to use Azure DevOps Task Groups to use the same build steps in multiple pipelines and build an Azure Linux SQL Server VM

Happy Automating!

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Building Azure SQL Db with Terraform using Azure DevOps

In my last post I showed how to create a Resource Group and an Azure SQLDB with Terraform using Visual Studio Code to deploy.

Of course, I havent stopped there, who wants to manually run code to create things. There was a lot of install this and set up that. I would rather give the code to a build system and get it to run it. I can then even set it to automatically deploy new infrastructure when I commit some code to alter the configuration.

This scenario though is to build environments for presentations. Last time I created an Azure SQL DB and tagged it with DataInDevon (By the way you can get tickets for Data In Devon here – It is in Exeter on April 26th and 27th)

If I want to create the same environment but give it tags for a different event (This way I know when I can delete resources in Azure!) or name it differently, I can use Azure DevOps and alter the variables. I could just alter the code and commit the change and trigger a build or I could create variables and enable them to be set at the time the job is run. I use the former in “work” situations and the second for my presentations environment.

I have created a project in Azure DevOps for my Presentation Builds. I will be using GitHub to share the code that I have used. Once I clicked on pipelines, this is the page I saw

Clicking new pipeline, Azure DevOps asked me where my code was

I chose GitHub, authorised and chose the repository.

I then chose Empty Job on the next page. See the Configuration as code choice? We will come back to that later and our infrastructure as code will be deployed with a configuration as code ๐Ÿ™‚

The next page allows us to give the build a good name and choose the Agent Pool that we want to use. Azure DevOps gives 7 different hosted agents running Linux, Mac, Windows or you can download an agent and run it on your own cpus. We will use the default agent for this process.

Clicking on Agent Job 1 enables me to change the name of the Agent Job. I could also choose a different type of Agent for different jobs within the same pipeline. This would be useful for testing different OS’s for example but for right now I shall just name it properly.

State

First we need somewhere to store the state of our build so that if we re-run it the Terraform plan step will be able to work out what it needs to do. (This is not absolutely required just for building my presentation environments and this might not be the best way to achieve this but for right now this is what I do and it works.)

I click on the + and search for Azure CLI.

and click on the Add button which gives me some boxes to fill in.

I choose my Azure subscription from the first drop down and choose Inline Script from the second

Inside the script block I put the following code

This will create a Resource Group, a storage account and a container and use some variables to provide the values, we will come back to the variables later.

Access Key

The next thing that we need to do is to to enable the job to be able to access the storage account. We don’t want to store that key anywhere but we can use our Azure DevOps variables and some PowerShell to gather the access key and write it to the variable when the job is running . To create the variables I clicked on the variables tab

and then added the variables with the following names TerraformStorageRG, TerraformStorageAccount and location from the previous task and TerraformStorageKey for the next task.

With those created, I go back to Tasks and add an Azure PowerShell task

I then add this code to get the access key and overwrite the variable.

Infrastructure as Code

In my GitHub repository I now have the following folders

The manual folders hold the code from the last blog post. In the Build folder, the main.tf file is identical and looks like this.

The variables.tf folder looks like this.

It is exactly the same except that the values have been replaced by the value name prefixed and suffixed with __. This will enable me to replace the values with the variables in my Azure DevOps Build job.

The backend-config.tf file will store the details of the state that will be created by the first step and use the access key that has been retrieved in the second step.

I need to add the following variables to my Azure DevOps Build – Presentation, ResourceGroupName, SqlServerName, SQLServerAdminUser, SQLServerAdminPassword, SqlDatabaseName, Edition, ServiceObjective . Personally I would advise setting the password or any other sensitive values to sensitive by clicking the padlock for that variable. This will stop the value being written to the log as well as hiding it behind *’s

Because I have tagged the variables with Settable at queue time , I can set the values whenever I run a build, so if I am at a different event I can change the name.

But the build job hasn’t been set up yet. First we need to replace the values in the variables file.

Replace the Tokens

I installed the Replace Tokens Task from the marketplace and added that to the build.

I am going to use a standard naming convention for my infrastructure code files so I add Build to the Root Directory. You can also click the ellipses and navigate to a folder in your repo. In the Target Files I add *”*/*.tf” and “**/*.tfvars” which will search all of the folders (**) and only work on files with a .tf or .tfvars extension (/*.tfvars) The next step is to make sure that the replacement prefix and suffix are correct. It is hidden under Advanced

Because I often forget this step and to aid in troubleshooting I add another step to read the contents of the files and place them in the logs. I do this by adding a PowerShell step which uses

Under control options there is a check box to enable or disable the steps so once I know that everything is ok with the build I will disable this step. The output in the log of a build will look like this showing the actual values in the files. This is really useful for finding spaces :-).

Running the Terraform in Azure DevOps

With everything set up we can now run the Terraform. I installed the Terraform task from the marketplace and added a task. We are going to follow the same process as the last blog post, init, plan, apply but this time we are going to automate it ๐Ÿ™‚

First we will initialise

I put Build in the Terraform Template path. The Terraform arguments are

which will tell the Terraform to use the backend-config.tfvars file for the state. It is important to tick the Install terraform checkbox to ensure that terraform is available on the agent and to add the Azure Subscription (or Service Endpoint in a corporate environment

After the Initialise, I add the Terraform task again add Build to the target path and this time the argument is plan

Again, tick the install terraform checkbox and also the Use Azure Service Endpoint and choose the Azure Subscription.

We also need to tell the Terraform where to find the tfstate file by specifying the variables for the resource group and storage account and the container

Finally, add another Terraform task for the apply remembering to tick the install Terraform and Use Azure checkboxes

The arguments are

This will negate the requirement for the “Only “yes” will be accepted to approve” from the manual steps post!

Build a Thing

Now we can build the environment – Clicking Save and Queue

opens this dialogue

where the variables can be filled in.

The build will be queued and clicking on the build number will open the logs

6 minutes later the job has finished

and the resources have been created.

If I want to look in the logs of the job I can click on one of the steps and take a look. This is the apply step

Do it Again For Another Presentation

So that is good, I can create my environment as I want it. Once my presentation has finished I can delete the Resource Groups. When I need to do the presentation again, I can queue another build and change the variables

The job will run

and the new resource group will be created

all ready for my next presentation ๐Ÿ™‚

This is brilliant, I can set up the same solution for different repositories for different presentations (infrastructure) and recreate the above steps.

The next post will show how to use Azure DevOps Task Groups to use the same build steps in multiple pipelines and build an Azure Linux SQL Server VM

The post after that will show how to use Azure DevOps templates to use the same build steps across many projects and build pipelines and will build a simple AKS cluster

The first post showed how to build an Azure SQLDB with Terraform using VS Code

Building Azure SQL Db with Terraform with Visual Studio Code

I have been using Terraform for the last week or so to create some infrastructure and decided to bring that knowledge back to a problem that I and others suffer from – building environments for presentations, all for the sake of doing some learning.

What is Terraform?

According to the website


HashiCorp Terraform enables you to safely and predictably create, change, and improve infrastructure. It is an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned


https://www.terraform.io/

This means that I can define my infrastructure as code. If I can do that then I can reliably do the same thing again and again, at work to create environments that have the same configuration or outside of work to repeatedly build the environment I need.

Building an Azure SQL Database with Terraform

To understand how to build a thing the best place to start is the documentation https://www.terraform.io/docs . For an Azure SQL Db in the docs you will find a block of code that looks like this

If you read the code, you can see that there are key value pairs defining information about the resource that is being created. Anything inside a ${} is a dynamic reference. So

refers to the name property in the azure_resource_group block called test (or the name of the resource group ๐Ÿ™‚ )

Infrastructure As Code

So I can put that code into a file (name it main.tf) and alter it with the values and “run Terraform” and what I want will be created. Lets take it a step further though because I want to be able to reuse this code. Instead of hard-coding all of the values I am going to use variables. I can do this by creating another file called variables.tf which looks like

and my main.tf then looks like this.

You can find these files in my GitHub Repository here.

Alright – deploy something

To deploy the code that I have written I need to download Terraform from https://www.terraform.io/downloads.html and then extract the exe to a folder in my PATH. (I chose C:\Windows). Then in Visual Studio Code I installed two extensions The Terraform Extension by Mikael Olenfalk which enables syntax highlighting and auto-completion for the tf files and the Azure Terraform extension. You will need also need Node.js from here.

With those in place I navigated to the directory holding my files in Visual Studio Code and pressed F1 and started typing azure terraform and chose Azure Terraform Init

I was then prompted to use Cloud Shell and a browser opened to login. Once I had logged in I waited until I saw this

I press F1 again and this time choose Azure Terraform plan. This is going to show me what Terraform is going to do if it applies this configuration.

You can see the what is going to be created. It is going to create 3 things

Once you have checked that the plan is what you want, press F1 again and choose Azure Terraform Apply

You are then asked to confirm that this is what you want. Only “yes” will be accepted. Then you will see the infrastructure being created

and a minute later

and Jeremy exists in the beardrules resource group

Then once I have finished with using the sqlinstance. I can press F1 again and choose Azure Terraform Destroy. Again there is a confirmation required.

and you will see the progress for 46 seconds

and all of the resources have gone.

Thats a good start. This enables me to create resources quickly and easily and keep the configuration for them safely in source control and easy to use.

In my next post I will create an Azure DevOps pipeline to deploy an AZure SQL Db withTerraform.

The post after will show how to use Azure DevOps Task Groups to use the same build steps in multiple pipelines and build an Azure Linux SQL Server VM

The post after that will show how to use Azure DevOps templates to use the same build steps across many projects and build pipelines and will build a simple AKS cluster

Adding a Folder of Scripts to GitHub with Azure Data Studio

In my last post I showed how to add a folder of scripts to GitHub using Visual Studio Code.

You can do it with Azure Data Studio as well. It’s exactly the same steps!

The blog post could end here but read on for some screen shots ๐Ÿ˜‰

Follow the previous post for details of setting up a new GitHub account

Create a repository in Github


Open the folder in Azure Data Studio with CTRL K CTRL O (Or File –> Open Folder)

Click on the Source Control icon or CTRL + SHIFT + G and then Initialize Repository

Choose the folder

Write a commit message

Say yes to the prompt. Press CTRL + ‘ to open the terminal

Navigate to the scripts folder. (I have a PSDrive set up to my Git folder)

and copy the code from the GitHub page after “โ€ฆor push an existing repository from the command line”

and run it

and there are your scripts in GitHub

Make some changes to a script and it will go muddy brown

and then write a commit message. If you click on the file name in the scource control tab then you can see the changes that have been made, that are not currently tracked

Commit the change with CTRL + ENTER and then click the roundy-roundy icon (seriously anyone know its name ?) click yes on the prompt and your changes are in GitHub as well ๐Ÿ™‚

Realistically, you can use the previous post to do this with Azure Data Studio as it is built on top of Visual Studio Code but I thought it was worth showing the steps in Azure Data Studio.

Happy Source Controlling

Adding a Folder of Scripts to GitHub

Yesterday there was a tweet from Allen White.

Allen wanted to add his scripts folder to source control but didn’t have a how to do it handy. So I thought I would write one. Hopefully this will enable someone new to GitHub and to source control get a folder of scripts under source control

GitHub account

If you do not have a GitHub account go to https://github.com and create a new account

There is a funky are you a human challenge

Then you can choose your subscription

Then answer some questions (Note – you probably want to choose different answers to the what are you interested in question! I’d suggest something technical)

You need to do the email verification

Next is a very important step – Please do not skip this. You should set up 2 factor authentication. Yes even if “It’s just for me there is nothing special here”

Click your user icon top right and then settings

Then click set up two factor authentication

and either set up with an app or via SMS (I suggest the app is better)

OK – Now you have your GitHub account set up. It should have taken you less time than reading this far.

Add a Scripts Folder to GitHub

OK, Now to add a folder of scripts to a repository. Here is my folder of scripts. They can be any type of files. I would recommend copy the folder to a specific Git folder.

Open VS Code – If you don’t have VS Code, download it from
https://code.visualstudio.com/ From the welcome window choose open folder


and open your scripts folder

In VS Code click the Source Control button


and up at the top you will see a little icon – initialise repository


Click that and choose your folder

Which will then show all of the changes to the repository (adding all the new files)

Now we need to add a commit message for our changes. I generally try to write commit messages that are the reason why the change has been made as the what has been changed is made easy to see in VS Code (as well as other source control GUI tools)

Click the tick or press CTRL + ENTER and this box will pop up


I never click Always, I click yes, so that I can check if I am committing the correct files. Now we have created a local repository for our scripts folder. Our next step is to publish it to GitHub

Create a New Repository in GitHub

In Github we need to create a remote repository. Click on the New Button. Give your repository a name and decide if you want it to be Public (available for anyone to search and find) or Private (only available to people you explicitly provide access to).

This will give you a page that looks like this

Copy the code after โ€ฆor push an existing repository from the command line

and paste it into PowerShell in VS Code. Make sure that your prompt is at the root of your scripts folder.

Fill in your username and password and your 2FA

Then you will see a page like this

and if you refresh your GitHub page you will see

Congratulations, your code is source controlled ๐Ÿ™‚

Making Changes

Now you can make a change to a file

Commit your change

Hit the roundy-roundy icon (anyone know its proper name ?)

Press OK and your commit will be pushed to Github ๐Ÿ™‚

Yay – Source Control all the things

How to break a SQL 2019 container on my laptop

Just a very quick post today. At the weekend I blogged about creating SQL 2019 containers with named volumes enabling you to persist your data and yesterday about creating a random workload using PowerShell and a big T-SQL script.

The interesting thing about creating workload is that you can break things ๐Ÿ™‚

When I created a SQL 2019 container with the data files mapped to a directory on my laptops C Drive with a docker-compose like this

restore the AdventureWorks database to use the /var/opt/sqlserver directory and run a workload after a while the container stops and when you examine the logs you find

I had a whole load of these errors

Then some of these

Then it went really bad

But that caused

Master eh? Now what will you do?

Interesting, then back to this.

It did all that again before

failing to capture it’s dump!! Oops ๐Ÿ™‚

I had to recreate the containers without using the named volumes and then I could run my workload ๐Ÿ™‚

Nothing particularly useful about this blog post other than an interesting look at the error log when things go wrong ๐Ÿ™‚

Generating a Workload against AdventureWorks with PowerShell

For a later blog post I have been trying to generate some workload against an AdventureWorks database.

I found this excellent blog post by Pieter Vanhove t https://blogs.technet.microsoft.com/msftpietervanhove/2016/01/08/generate-workload-on-your-azure-sql-database/ which references this 2011 post by Jonathan Kehayias t
https://www.sqlskills.com/blogs/jonathan/the-adventureworks2008r2-books-online-random-workload-generator/

Both of these run a random query in a single thread so I thought I would use PoshRSJob by Boe Prox b | t to run multiple queries at the same time ๐Ÿ™‚

To install PoshRSJob, like with any PowerShell module, you run

I downloaded AdventureWorksBOLWorkload zip from Pieters blog post and extracted to my C:\temp folder. I created a Invoke-RandomWorkload function which you can get from my functions repository in Github. The guts of the function are

which will created $NumberOfJobs jobs and then run $Throttle number of jobs in the background until they have all completed. Each job will run a random query from the query file using Invoke-SqlCmd. Why did I use Invoke-SqlCmd and not Invoke-DbaQuery from dbatools? dbatools creates runspaces in the background to help with logging and creating runspaces inside background jobs causes errors

Then I can run the function with

and create a random workload. Creating lots of background jobs takes resources so when I wanted to run a longer workload I created a loop.

You can get the function here. The full code is below

Persisting databases with named volumes on Windows with docker compose

With all things containers I refer to my good friend Andrew Pruski. Known as dbafromthecold on twitter he blogs at https://dbafromthecold.com

I was reading his latest blog post Using docker named volumes to persist databases in SQL Server and decided to give it a try.

His instructions worked perfectly and I thought I would try them using a docker-compose file as I like the ease of spinning up containers with them.

I created a docker-compose file like this which will map my backup folder on my Windows 10 laptop to a directory on the container and two more folders to the system folders on the container in the same way as Andrew has in his blog.

and then from the directory I ran

This will build the containers as defined in the docker-compose file. The -d runs the container in the background. This was the result.

UPDATE – 2019-03-27

I have no idea why, but today it has worked as expected using the above docker-compose file. I had tried this a couple of times, restarted docker and restarted my laptop and was consistently getting the results below – however today it has worked

So feel free to carry on reading, it’s a fun story and it shows how you can persist the databases in a new container but the above docker-compose has worked!

The command completed successfully but as you can see on the left the container is red because it is not running. (I am using the Docker Explorer extension for Visual Studio C

I inspected the logs from the container using

which returned

This is an evaluation version. There are [153] days left in the evaluation period.
This program has encountered a fatal error and cannot continue running at Tue Mar 26 19:40:35 20
19
The following diagnostic information is available:
Reason: 0x00000006 Status: 0x40000015 Message: Kernel bug check Address: 0x6b643120
Parameters: 0x10861f680
Stacktrace: 000000006b72d63f 000000006b64317b 000000006b6305ca
000000006b63ee02 000000006b72b83a 000000006b72a29d
000000006b769c02 000000006b881000 000000006b894000
000000006b89c000 0000000000000001
Process: 7 – sqlservr
Thread: 11 (application thread 0x4)
Instance Id: e01b154f-7986-42c6-ae13-c7d34b8b257d
Crash Id: 8cbb1c22-a8d6-4fad-bf8f-01c6aa5389b7
Build stamp: 0e53295d0e1704ae5b221538dd6e2322cd46134e0cc32be49c887ca84cdb8c10
Distribution: Ubuntu 16.04.6 LTS
Processors: 2
Total Memory: 4906205184 bytes
Timestamp: Tue Mar 26 19:40:35 2019
Ubuntu 16.04.6 LTS
Capturing core dump and information to /var/opt/mssql/logโ€ฆ
dmesg: read kernel buffer failed: Operation not permitted
No journal files were found.
No journal files were found.
Attempting to capture a dump with paldumper
WARNING: Capture attempt failure detected
Attempting to capture a filtered dump with paldumper
WARNING: Attempt to capture dump failed. Reference /var/opt/mssql/log/core.sqlservr.7.temp/log/
paldumper-debug.log for details
Attempting to capture a dump with gdb
WARNING: Unable to capture crash dump with GDB. You may need to
allow ptrace debugging, enable the CAP_SYS_PTRACE capability, or
run as root.

which told me that …………. it hadn’t worked. So I removed the containers with

I thought I would create the volumes ahead of time like Andrew’s blog had mentioned with

and then use the volume names in the docker-compose file mapped to the system folders in the container, this time the result was

ERROR: Named volume “mssqlsystem:/var/opt/sqlserver:rw” is used in service “2019-CTP23” but no declaration was found in the volumes section.

So that didnt work either ๐Ÿ™‚

I decided to inspect the volume definition using

I can see the mountpoint is /var/lib/docker/volumes/mssqlsystem/_data so I decided to try a docker-compose like this

and then ran docker-compose up without the -d flag so that I could see all of the output

You can see in the output that the system database files are being moved. Thatlooks like it is working so I used CTRL + C to stop the container and return the terminal. I then ran docker-compose up -d and

I created a special database for Andrew.

I could then remove the container with

To make sure there is nothing up my sleeve I altered the docker-compose file to use a different name and port but kept the volume definitions the same.

I ran docker-compose up -d again and connected to the new container and lo and behold the container is still there

So after doing this, I have learned that to persist the databases and to use docker-compose files I had to map the volume to the mountpoint of the docker volume. Except I haven’t, I have learned that sometimes weird things happen with Docker on my laptop!!

Whats a SQL Notebook in Azure Data Studio?

Azure Data Studio is a cross-platform database tool for data professionals using the Microsoft family of on-premises and cloud data platforms on Windows, MacOS, and Linux.

Recently Vicky Harp tweeted

By the way, you can watch a recording from SQLBits of Vicky’s session


So in the interest of learning about something new I decided to give it a try.

Install The Insiders Edition

Unlike Visual Studio Code which has a link to the insiders download on the front page, you will have to visit the GitHub repository for the links to download the insiders release of Azure Data Studio. Scroll down and you will see

Try out the latest insiders build from master:

See theย change logย for additional details of what’s in this release.

Once you have installed you can connect to an instance, right click and choose New Notebook or you can use File – New Notebook

Incidentally, I use the docker-compose file here to create the containers and I map C:\MSSQL\BACKUP\KEEP on my local machine (where my backups are) to /var/opt/mssql/backups on the containers on lines 10 and 17 of the docker-compose so change as required . If you want to follow along then put the ValidationResults.bak in the folder on your local machine.
The Create-Ag.ps1 shows the code and creates an AG with dbatools. But I digress!

Install Notebook Dependencies

Once you click New Notebook you will get a prompt to install the dependencies.

It will show its output

and take a few minutes to run

It took all but 11 minutes on my machine

#

Create a Notebook

OK, so now that we have the dependencies installed we can create a notebook. I decided to use the ValidationResults database that I use for my dbachecks demos and describe here. I need to restore it from my local folder that I have mapped as a volume to my container. Of course, I use dbatools for this ๐Ÿ™‚

I had already got a connection saved to the instance in Azure Data Studio, you may need to create a new one using the new connection icon at the top left and filling in the details. The password is in the code above.



Now I can start with my notebook. I am faced with this



I click on text and provide an intro


Once I had written that and clicked out, I couldn’t see what to do straight away!

Then I saw the code and text buttons at the top ๐Ÿ™‚ Right, lets get on with it ๐Ÿ™‚ I hit the code button and paste in the T-SQL to reset the dates in the database to simulate dbachecks having been run this morning.


There’s a run cell button on the right and when I press it

Cool ๐Ÿ™‚

If the SQL query has results then they are shown as well

This is fun and I can see plenty of uses for it. Go and have a play with SQL notebooks ๐Ÿ™‚

Source Control

I used CTRL K, CTRL O to open a folder and saved my notebook in my local Presentations folder which is source controlled. When I opened the explorer CTRL + SHIFT + E I can see that the folder and the file are colour coded green and have a U next to them marking them as Untracked. I can also see that the source control icon has a 1 for the number of files with changes and in the bottom left that I am in the master branch.

If I click on the source control icon (or CTRL + SHIFT + G) I can see the files with the changes and can enter a commit message

I then press CTRL + ENTER to commit my change and get this pop-up


As I only have one file and it has all the changes for this commit I click yes. If I had changed more than one file and only wanted to commit a single one at a time I would hover my mouse over the file and click the + to stage my change.



If I make a further change to the notebook and save it, I can see that the source control provider recognises the change but this time the folder the file is in and the file are colour coded brown with an M to show that they have been modified.

Unlike Visual Studio Code, when you then click on the source control icon and click on the change it does not show the differences in the notebook although this works with SQL files.

When I have made all my changes and committed them with good commit messages


I can see that there are 3 local changes ready to be pushed to by remote repository (GitHub in this case) and 0 remote commits in this branch by looking at the bottom left

I can click on the “roundy roundy” icon (I dont know its proper name ๐Ÿ˜Š) and synchronise my changes. This comes with a pop-up

Personally I never press OK, Don’t Show Again because I like the double check and to think “Is this really what I want to do right now”. Once I press OK my changes will be synched with the remote repository. Explaining this means that you can find the notebook I have used in my Presentations GitHub Repository which means that you can run the Notebook too using the docker-compose file here and the instructions further up in the post.

Using Docker to run Integration Tests for dbachecks

My wonderful friend Andrรฉ Kamman wrote a fantastic blog post this week SQL Server Container Instances via Cloudshell about how he uses containers in Azure to test code against different versions of SQL Server.

It reminded me that I do something very similar to test dbachecks code changes. I thought this might make a good blog post. I will talk through how I do this locally as I merge a PR from another great friend Clรกudio Silva who has added agent job history checks.

GitHub PR VS Code Extension

I use the GitHub Pull Requests extension for VS Code to work with pull requests for dbachecks. This enables me to see all of the information about the Pull Request, merge it, review it, comment on it all from VS Code

I can also see which files have been changed and which changes have been made

Once I am ready to test the pull request I perform a checkout using the extension

This will update all of the files in my local repository with all of the changes in this pull request

You can see at the bottom left that the branch changes from development to the name of the PR.

Running The Unit Tests

The first thing that I do is to run the Unit Tests for the module. These will test that the code is following all of the guidelines that we require and that the tests are formatted in the correct way for the Power Bi to parse. I have blogged about this here and here and we use this Pester in our CI process in Azure DevOps which I described here.

I navigate to the root of the dbachecks repository on my local machine and run

and after about a minute

Thank you Clรกudio, the code has passed the tests ๐Ÿ˜‰

Running Some Integration Tests

The difference between Unit tests and Integration tests in a nutshell is that the Unit tests are testing that the code is doing what is expected without any other external influences whilst the Integration tests are checking that the code is doing what is expected when running on an actual environment. In this scenario we know that the code is doing what is expected but we want to check what it does when it runs against a SQL Server and even when it runs against multiple SQL Servers of different versions.

Multiple Versions of SQL Server

As I have described before my friend and former colleague Andrew Pruski b | t has many resources for running SQL in containers. This means that I can quickly and easily create fresh uncontaminated instances of SQL 2012, 2014, 2016 and 2017 really quickly.

I can create 4 instances of different versions of SQL in (a tad over) 1 minute. How about you?

Imagine how long it would take to run the installers for 4 versions of SQL and the pain you would have trying to uninstall them and make sure everything is ‘clean’. Even images that have been sysprep’d won’t be done in 1 minute.

Docker Compose Up ?

So what is this magic command that has enabled me to do this? docker compose uses a YAML file to define multi-container applications. This means that with a file called docker-compose.yml like thish

and in that directory just run

and 4 SQL containers are available to you. You can interact with them via SSMS if you wish with localhost comma PORTNUMBER. The port numbers in the above file are 15586, 15587,15588 and 15589

Now it must be noted, as I describe here that first I pulled the images to my laptop. The first time you run docker compose will take significantly longer if you haven’t pulled the images already (pulling the images will take quite a while depending on your broadband speed)

Credential

The next thing is to save a credential to make it easier to automate. I use the method described by my PowerShell friend Jaap Brasser here. I run this code

and then I can create a credential object using

Check The Connections

I ensure a clean session by removing the dbatools and dbachecks modules and then import the local version of dbachecks and set some variables

Now I can start to run my Integration tests. First reset the dbachecks configuration and set some configuration values

Then I will run the dbachecks connectivity checks and save the results to a variable without showing any output

I can then use Pester to check that dbachecks has worked as expected by testing if the failedcount property returned is 0.

What is the Unit Test for this PR?

Next I think about what we need to be testing for the this PR. The Unit tests will help us.

Choose some Integration Tests

This check is checking the Agent job history settings and the unit tests are

  • It “Passes Check Correctly with Maximum History Rows disabled (-1)”
  • It “Fails Check Correctly with Maximum History Rows disabled (-1) but configured value is 1000”
  • It “Passes Check Correctly with Maximum History Rows being 10000”
  • It “Fails Check Correctly with Maximum History Rows being less than 10000”
  • It “Passes Check Correctly with Maximum History Rows per job being 100”
  • It “Fails Check Correctly with Maximum History Rows per job being less than 100”

So we will check the same things on real actual SQL Servers. First though we need to start the SQL Server Agent as it is not started by default. We can do this as follows

Unfortunately, the agent service wont start in the SQL 2014 container so I cant run agent integration tests for that container but it’s better than no integration tests.

This is What We Will Test

So we want to test if the check will pass with default settings. In general, dbachecks will pass for default instance, agent or database settings values by default.

We also want the check to fail if the configured value for dbachecks is set to default but the value has been set on the instance.

We want the check to pass if the configured value for the dbachecks configuration is set and the instance (agent, database) setting matches it.

If You Are Doing Something More Than Once ……

Let’s automate that. We are going to be repeatedly running those three tests for each setting that we are running integration tests for. I have created 3 functions for this again checking that FailedCount or Passed Count is 0 depending on the test.

Now I can use those functions inside a loop in my Integration Pester Test

Write Some Integration Tests

So for this new test I have added a value to the TestingTheChecks array then I can test my checks. The default check I can check like this

Now I need to change the configurations so that they do not match the defaults and run the checks again

Next we have to change the instance settings so that they match the dbachecks configuration and run the checks and test that they all pass.

We will (of course) use dbatools for this. First we need to find the command that we need

and then work out how to use it

There is an example that does exactly what we want ๐Ÿ™‚ So we can run this.

Run the Integration Tests

And then we will check that all of the checks are passing and failing as expected

Integration Test For Error Log Counts

There is another integration test there for the error logs count. This works in the same way. Here is the code

Merge the Changes

So with all the tests passing I can merge the PR into the development branch and Azure DevOps will start a build. Ultimately, I would like to add the integration to the build as well following Andrรฉ‘s blog post but for now I used the GitHub Pull Request extension to merge the pull request into development which started a build and then merged that into master which signed the code and deployed it to the PowerShell gallery as you can see here and the result is

https://www.powershellgallery.com/packages/dbachecks/1.1.164