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Category: Containers

Using the DAC with Dockerized SQL Server

Joey D’Antoni needed to use the Dedicated Administrator Connection:

Because as shown in the image above, the table in question is a system_table, in order to query it directly, you need to use the dedicated administrator connection (DAC) in SQL Server. The DAC is a piece of SQL Server that dedicates a CPU scheduler, and some memory for a single admin session. This isn’t designed for ordinary use–you should only use it when your server is hosed, and you are trying to kill a process, or when you need to query a system table to answer a twitter post. The DAC is on by default, with a caveat–it can only be accessed locally on the server by default. This would be connected to a server console or RDP session on Windows, or in the case of a container, by shelling into the container itself. However, Microsoft gives you the ability to turn it on for remote access (and you should, DCAC recommends this as a best practice), by using the following T-SQL.

Read on to see how, as well as what else you’d need to do to get it working.

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Deploying SQL Server via AKS

Rajendra Gupta needs to deploy a SQL Server container:

This article uses Azure Kubernetes Service (AKS) to deploy and manage the Kubernetes cluster. It is a fully managed service that offers serverless Kubernetes with integrated CI/CD solutions, enterprise-grade security, and governance.

You can navigate to https://azure.microsoft.com/en-in/services/kubernetes-service/#overview and try Azure Kubernetes Service (AKS).

Read on for an overview of Azure Kubernetes Service and how you can get a SQL Server on Linux container running atop it.

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A Primer on Azure Arc-Enabled Data Services

Warwick Rudd has a four-parter on Azure Arc-Enabled Data Services. Part 1 sets the stage:

Utilising Azure Arc-enabled data services provides you the ability to take advantage of the Azure data services (SQL Server, Azure SQL Managed Instance, PostgreSQL) in a hybrid environment. This offering provides you with reduced administrative efforts in managing and maintaining your data services while giving you the same look and feel as if you were running in the Azure Cloud.

Part 2 looks at the Data Controller:

The Azure Arc Data Controller is a Kubernetes operator that performs all of the orchestration to ensure you achieve your desired state. This is the main component in the Azure Arc infrastructure that links the data services with the Arc-enabled hardware located either in your On-premises, Azure, or any other public cloud data center and your azure subscription.

The Arc data controller allows you to deploy, manage, secure, and monitor your deployed data services estate using Azure Data Studio or the Azure Portal (only for directly connected mode deployments) but giving you the same experience as if you were managing your data services from inside of the Azure Portal.

Part 3 deploys a Data Controller:

As previously mentioned there are 2 types of deployment available for your Arc Data Controller. In this post, we are going to have a look at deploying in the Arc Data Controller using the directly connected mode.

For a directly connected Arc Data Controller, we have direct connectivity to our Azure subscription. With this in mind, there are several options as we previously discussed on how to deploy the data controller. For this post, we are using the portal deployment method.

Finally, Part 4 covers management options:

With ADS open and running you can create connections to Arc Data Controllers the same as you can with Instances of SQL Server. In ADS we have under the connections area a section specific for Arc Data Controllers.

Check out all four posts.

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SQL Server Container Images and RHEL/Ubuntu Versions

Amit Khandelwal announces a change:

To make this approach scalable & manageable, we will publish SQL Server container images to MCR based on the distribution’s most recent version, rather than publishing it for all versions of both RHEL and Ubuntu. Here’s an example to help you understand: 

SQL Server 2017 supports Ubuntu 18.04 as the most recent distribution; thus, going forward SQL Server 2017 container images based on the Ubuntu 18.04 image will only be published to MCR and we will not publish the SQL Server 2017 container images for Ubuntu 16.04.

This seems fine to me. They focus on image support for the most recent fully-supported version and hopefully make it a bit better. I do wonder if that will change their overall Linux policy around version support, as that could be trickier to sell.

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Stopping Azure Kubernetes Service Nodes

Andrew Pruski wants to shut the whole thing down:

A while back I wrote a post on Adjusting Pod Eviction Timings in Kubernetes. To test the changes made in that post I had to shut down nodes in an Azure Kubernetes Service cluster.

This can be done easily in the Azure portal: –

However I did a presentation recently and didn’t want to have to keep jumping into the portal from VS Code…so I wanted to be able to shut down the nodes in code.

So here’s how to use the azure-cli to shut down a node in an Azure Kubernetes Service cluster.

Read on to see how but also read Andrew’s warning / disclaimer so you don’t mess anything up in a production environment.

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Creating a SQL Server 2022 Learning Environment

Marlon Ribunal gets us started with a Docker container:

Maybe you want to get your hands dirty with the bells and whistles of the latest iteration of SQL Server, but you don’t have an extra bare metal or Azure or GCP based VM. Well, you’re in luck because Microsoft just released container images for SQL Server 2022.

Here are few steps to get you started with SQL Server 2022:

At this point, it’s quite easy to give new versions of SQL Server a try, even when they’re in preview. That said, some of the features make it to containers later so you might want to spin up a virtual machine and install it if there’s something you can’t get right now in the container.

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Running Kubernetes Clusters on Windows

Boemo Mmopelwa shows off Kubernetes Kind:

Kubernetes production clusters are typically run on cloud platforms. However, running and deploying Kubernetes applications on cloud platforms such as Google Kubernetes Engine is costly. These high costs can restrict the Kubernetes learning process for beginners. However, running Kubernetes clusters locally helps you efficiently test applications without disrupting the production environment or paying for cloud services. 

To make things easier, the Kubernetes team developed two tools,  Minikube and Kind, that allow Kubernetes users to run clusters locally without spending a dollar. This article will cover how to do it with Kind. Kind is a command-line tool used to run Kubernetes clusters locally on your computer using Docker containers. Kind works with Docker by loading Docker containers into Kind clusters. A Kubernetes cluster is a group of nodes used to run containerized applications.

Read the whole thing.

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Kubernetes for the R User

Roel M. Hogervorst provides an introduction to Kubernetes for R users:

Many R users come from an academic background, statistics and social sciences. That makes you an excellent problem solver with a deep knowledge of problems and a nuanced understanding of the world. You actually know what you are talking about!

But there is a different world, a world where the most important thing is showing an advertisement to as many people as possible. I’m joking, but the computer science world is where ideas like kubernetes were born. And like every other group specific words are used that can be hard to understand without context. That means that you have to use those words to find answers on your questions. This post will introduce some of those words and I have a list at the bottom. And now it is available to all of us, through a cloud provider in your area.

Read on for a light introduction to using Kubernetes.

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Monitoring Kubernetes in Production

Samir Behara provides some guidance:

Kubernetes is an open-source container orchestration system for automating the deployment and management of containerized applications. Kubernetes provides capabilities like service discovery, horizontal autoscaling, and load balancing, while ensuring that application configurations are declarative and that systems are self-healing.

In this article, I will explain how to monitor your Kubernetes cluster and implement automated health checks, and discuss the various monitoring tools available.

Read on for some thoughts. In addition to Samir’s links and ideas, I’d also throw in some tools like Rancher to make management a little easier.

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Running MSDTC on Linux Containers in Kubernetes

Amit Khandelwal reminds us that MSDTC exists:

It’s been a while since I’ve had the opportunity to write and share a blog post about SQL Server containers and Linux. Today, I’d like to show you how to set up and use MSDTC (Microsoft Distributed Transaction Coordinator) to execute distributed transactions for SQL Server containers running on a Kubernetes platform.

Please see the following documentation for more information on DTC and SQL Server on Linux. How to configure MSDTC on Linux – SQL Server | Microsoft Docs.

I kid (sort of) but it is good to see as much parity between the Windows and Linux versions of SQL Server as possible.

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