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Category: Containers

Customizing a Docker Container

Grant Fritchey shows how you can take a Docker container and save modifications:

There are much more sophisticated ways to get this done using Docker Files. However, this illustrates the point quite simply. You can customize your servers and then use those customizations. You don’t have to re-customize every time. Again, this is just a small slice of why containers are so powerful.

This method is great when you want to build out a sample data set, like when you’re running through automated testing and want to start from the same known point each time.

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Creating Containers and Volumes

Grant Fritchey continues a dive into containers. First up is running a Docker container:

Let’s break this down a bit so you know what you just did. The two ‘-e’ statements are setting environment variables. The first is accepting Microsoft’s end user license agreement, EULA. The second is setting the SA password. By default, we’re running a Developer Edition of SQL Server here. If you want to, you can change to a version that you have a specific license for using the MSSQL_PID environment variable. Documentation for that is located here.

Next is using volumes:

Now, let’s create a new container, but, let’s use the same volume:
docker run -e 'ACCEPT_EULA=Y' ` -e 'SA_PASSWORD=$cthulhu1988' ` -p 1450:1433 ` --name DockerDemo19 ` -v sqlvol:/var/opt/mssql ` -d mcr.microsoft.com/mssql/server:2019-CTP2.5-ubuntu

What happens next is marvelous. 

It’s an exciting time to get into containers and if you’re feeling a little trepidatious, they’re containers—the worst thing you can do is mess one up and then you just blow it away and start over.

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Pulling Docker Images

Grant Fritchey starts us off slowly with containers:

The first command you have to learn is ‘docker pull’. You then have to supply something for it to pull, an image that will be used to create your containers. I’m using Powershell for the commands I’m posting this week. Here’s how you get an image with SQL Server 2017:

docker pull mcr.microsoft.com/mssql/server:2017-latest

Click through to learn more.

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SQL Server and Terraform

Andrew Pruski continues a series on using Terraform to deploy to Azure Container Instances:

In a previous post I went through how to deploy SQL Server running in an Azure Container Instance using Terraform.

In that post, I used hardcoded variables in the various .tf files. This isn’t great to be honest as in order to change those values, we’d need to update each .tf file. It would be better to replace the hardcoded values with variables whose values can be set in one separate file.

So let’s update each value with a variable in the .tf files.

Click through for a demo.

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Persisting SQL Server Databases on Kubernetes

Anthony Nocentino walks us through persistent volumes and Kubernetes:

One of the key principals of Kubernetes is the ephemerality of Pods. No Pod is every redeployed, a completely new Pod is created. If a Pod dies, for whatever reason, a new Pod is created in its place there is no continuity in the state of that Pod. The newly created Pod will go back to the initial state of the container image defined in the Pod’s spec. This is very valuable for stateless workloads, not so much for stateful workloads like SQL Server.

This means that for a stateful workload like SQL Server we need to store both configuration and data externally from the Pod to maintain state through the recreation of a Pod. Kubernetes give us constructs two constructs to do that, environment variables and Persistent Volumes. 

Read on for a good bit of background and a few scripts to help you get started.

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Deploying SQL Server Containers to Azure with Terraform

Andrew Pruski has a post covering deployment of SQL Server containers to Azure using Terraform:

What this is going to do is create an Azure Container Instance Group with one container it in, running SQL Server 2019 CTP 2.5. It’ll be publicly exposed to the internet on port 1433 (I’ll cover fixing that in a future post) so we’ll get a public IP that we can use to connect to.

Notice that the location and resource_group_name are set using variables that retrieve the values of the resource group are going to create.

Cool! We are ready to go!

Fun stuff, and Andrew promises more.

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Using Powershell Core in Containers

Anthony Nocentino shows us how we can run Powershell Core in containers:

Now, with that last technique, we’ve encapsulated the entire lifecycle of the execution of that script into one line of code. It’s like this script execution never happened…or did it 😉 All kidding aside, we effectively have a serverless computing platform now. Using this technique in our data centers, we can spin up a container, on any version of PowerShell on any platform, run some workload/script and when the workload finishes, the container just goes away. For this to work well, we will need something to drive that process. In an upcoming blog post, we’ll talk more about how we can automate the running of PowerShell containers in Kubernetes.
 
In this post, we covered a lot, we looked at how you can interactively run PowerShell Core in a container, how you can pass cmdlets into a container at runtime, running different versions of PowerShell Core and also how you can persistently store scripts outside of containers in volumes and run those scripts in your containers. We also looked at how you can encapsulate the whole execution of a script and the containers life cycle into one line of code. Really giving you the ability to run PowerShell Core anywhere on any platform.

Check it out for sure. Containers today are where VMs were about a decade ago: becoming more common but still a bit “out there” for administrators. It’s not a stretch to say that within a few years, containers will be as ubiquitous as VMs were by 2012, if not more so.

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Building an AKS Cluster with Azure DevOps

Rob Sewell shows how to use Azure DevOps to build an AKS cluster with Terraform:

In the last few posts I have moved from building an Azure SQL DB with Terraform using VS Code to automating the build process for the Azure SQL DB using Azure DevOps Build Pipelines to using Task Groups in Azure DevOps to reuse the same Build Process and build an Azure Linux SQL VM and Network Security Group. This evolution is fantastic but Task Groups can only be used in the same Azure DevOps repository. It would be brilliant if I could use Configuration as Code for the Azure Build Pipeline and store that in a separate source control repository which can be used from any Azure DevOps Project.

Luckily, you can

And Rob shows us how it’s done.

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Centralized Kubernetes Management with Rancher

Praveen Sripati shows us how we can use Rancher to create a Kubernetes cluster anywhere, using AWS as an example:

In the previous blog  we explored on setting up an K8S Cluster on the AWS Cloud without using any additional softwares or tools. The Cloud Providers make it easy to create a K8S Cluster in the Cloud. The tough part is securing, fine tuning, upgradation, access management etc. Rancher provides a centralized management of the different K8S Clusters, these can be in any of the Cloud (AWS, GCP, Azure) or In-Prem. More on what Rancher has to offer on top of K8S here. The good thing about Rancher is that’s it’s 100% Open Source and there is no Vendor Lock-in. We can simply remove Rancher and interact with the K8S Cluster directly.

I like this kind of tooling because it reduces cloud lock-in. For something like Kubernetes, where the whole point is orchestration of ephemeral containers, there’s a lot of benefit in being able to shift between services as needed.

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Custom kubectl Plugin: Connect to SQL Server

Andrew Pruski shows how to create custom kubectl plugins:

When I deploy SQL Server to Kubernetes I usually create a load balanced service so that I can get an external IP to connect from my local machine to SQL running in the cluster. So how about creating a plugin that will grab that external IP and drop it into mssql-cli?

Let’s have a go at creating that now.

Click through for two demos including the appropriately-named kubectl prusk.

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