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Category: Containers

Another Way to Upgrade SQL Server 2017 Containers to 2019

Published 2019-11-25 by Kevin Feasel

Anthony Nocentino gives us another option for upgrading SQL Server on containers:

Yesterday in this post I described a method to correct permissions when upgrading a SQL Server 2017 container using Data Volumes to 2019’s non-root container on implementations that use the Moby or HyperKit VM. My friend Steve Jones’ on Twitter wondered if you could do this in one step by attaching a shell (bash) in the 2017 container prior to shutdown. Absolutely…let’s walk through that here in this post.  I opted to use an intermediate container in the prior post out of an abundance of caution so that I was not changing permissions on the SQL Server instance directory and all of the data files while they were in use. Technically this is a-ok, but again…just being paranoid there.

Click through for that process. The good news is that with upgrading from SQL Server 2019 to SQL Server 202x, I wouldn’t expect that we’d need to go through this again, as the process would stay non-root forevermore.

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Upgrading SQL Server 2017 Containers to 2019

Published 2019-11-21 by Kevin Feasel

Anthony Nocentino takes us through one of the big changes to SQL Server containers:

When you start up the 2017 container, the SQL Server (sqlservr) process is running as root (uid 0). Any files created by this process will have the user and group ownership of the root user. Now when we come along later and start up a 2019 container, the sqlservr process is running as the user msssql (uid 10001 by default). This new user doesn’t have permission to open the database files and other files used by SQL Server.

Read on to see how Anthony fixed this.

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Named Volumes in Docker with SQL Server 2019

Published 2019-11-20 by Kevin Feasel

Andrew Pruski takes us through one of the biggest changes with SQL Server 2019 in containers:

I’ve seen a few people online asking how to use docker named volumes with the new SQL Server 2019 RTM images. Microsoft changed the way SQL runs within a container for the RTM versions, SQL no longer runs as the root user.

This is a good thing but does throw up some issues when mounting volumes to create databases on.

Let’s run through what the issue is and how to overcome it.

Click through to see what you need to add to your DOCKERFILE to get things working.

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Deploying a Big Data Cluster with Azure Data Studio

Published 2019-11-15 by Kevin Feasel

Mohammad Darab shows how you can deploy a Big Data Cluster to Azure Kubernetes Service using Azure Data Studio:

A few months ago I posted a blog on deploying a BDC using the built-in ADS notebook. This blog post will go a bit deeper into deploying a Big Data Cluster on AKS (Azure Kubernetes Service) using Azure Data Studio (version 1.13.0). In addition, I’ll go over the pros and cons and dive deeper into the reasons why I recommend going with AKS for your Big Data Cluster deployments.

AKS does make it pretty easy. The toughest part for me was figuring out which instance types were supported—I tried a few which would save me money and they weren’t available. I do like that they added a check to view availability before completing the notebook; that wasn’t in the preview version.

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SQL Server Trends Worth Watching

Published 2019-11-13 by Kevin Feasel

Grant Fritchey follows up on a Kevin Hill tweet:

There are a million things to learn about in our rapidly shifting technological landscape, but I think this assessment, especially the way it was put, “no longer justify ignoring” really nails some of the fundamentals.

Let’s talk about why you can no longer ignore Docker, Git and DBATools either.

If you’re a DBA and aren’t familiar with Docker, Git, or DBATools, that’s a pretty good trio of things to spend some time learning. You can survive without them, but you’re more likely to thrive if you know them.

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Deploying a Container Instance in Azure

Published 2019-10-24 by Kevin Feasel

Anibal Kolker takes us through container deployment in Azure:

As derived from the title, the objective of this post is to help you deploy a container instance inside Azure.

However, we’ll extend the typical scenario and make a slightly more extensive use of networking capabilities, by placing the container group inside a private subnet.

Note: For this example, and for simplicity only, we’ll use NGINX as our container of choice. Of course, you’re welcome to try with any other image.

There are a few pieces in play, but Anibal does a good job putting it all together.

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Storing Container Images in GitHub Package Registry

Published 2019-10-24 by Kevin Feasel

Andrew Pruski shows how we can use GitHub Package Registry to store private container images:

The GitHub Package Registry is available for beta testing and allows us to store container images in it, basically giving us the same functionality as the Docker Hub.

However the Docker Hub only allows for one private repository per free account whereas the Github package registry is completely private! Let’s run through a simple demo to create a registry and upload an image.

It’s pretty easy to set up, so check it out.

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Installing Kubernetes

Published 2019-10-08 by Kevin Feasel

Anthony Nocentino has an updated version of his Kubernetes installation guide:

Kubernetes is a distributed system, you will be creating a cluster which will have a master node that is in charge of all operations in your cluster. In this walkthrough we’ll create three workers which will run our applications. This cluster topology is, by no means, production ready. If you’re looking for production cluster builds check out Kubernetes documentation. Here and here. The primary components that need high availability in a Kubernetes cluster are the API Server which controls the state of the cluster and the etcd database which persists the state of the cluster. You can learn more about Kubernetes cluster components here. If you want to dive into Kubernetes more check out my Pluralsight Courses here! Where I have a dedicated course on Installation and Configuration.

In our demonstration here, the master is where the API Server, etcd, and the other control plan functions will live. The workers/nodes, will be joined to the cluster and run our application workloads. 

Read the whole thing.

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Configuring Memory Limits for SQL Server in Kubernetes

Published 2019-09-30 by Kevin Feasel

Anthony Nocentino doesn’t have all the RAM in the world:

With that Pod deployed, I loaded up a HammerDB TPC-C test with about 10GB of data and drove a workload against our SQL Server. Then while monitoring the workload…boom HammerDB throws connection errors and crashes. Let’s look at why.

First thing’s first, let’s check the Pods status with kubectl get pods. We’ll that’s interesting I have 13 Pods. 1 has a Status of Running and the remainder have are Evicted. 

Anthony does a great job of explaining the problem and showing you the solution.

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