Docker

I’m very pleased to announce that I will be speaking at PASS Summit 2019!  This is my second time speaking at PASS Summit and I’m very excited to be doing so! What’s more, is I get to help blaze new ground with an emerging technology,** Kubernetes and how to run SQL Server in Kubernetes**!

My session is “Inside Kubernetes – An Architectural Deep Dive” if you’re a just getting started in the container space and want to learn how Kubernetes works and dive into how to deploy SQL Server in Kubernetes this is the session for you. I hope to see you there!

Let’s get you started on your Kubernetes journey with installing Kubernetes and creating a cluster in virtual machines.

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][1] and [here][2]. The primary components that need high availability in a Kubernetes cluster are the [API Server][3] which controls the state of the cluster and the [etcd][4] database which persists the state of the cluster. You can learn more about Kubernetes cluster components [here][5]. If you want to dive into Kubernetes more check out my Pluralsight Courses [here][6]! Where I have a dedicated course on [Installation and Configuration][7].

So, if you’ve been following my blog you know my love for internals. Well, I needed to find out exactly how something worked at the startup of a SQL Server process running inside a docker container and my primary tool for this is <a href="http://man7.org/linux/man-pages/man1/strace.1.html">strace</a>, well how do you run strace against processes running in a container? I hadn’t done this before and needed to figure this out…so let’s go through how I pulled this off.

A quick post about pulling docker containers (this applies to docker run too)…when specifying the container image, the container image name and tag are case sensitive. We’re not going to discuss how much time troubleshooting it too me to figure this out…but let’s just say it’s more than I care to admit publicly.

In this code you can see I’m specifying the following image and tag server:2019-rc1-ubuntu (notice the lowercase rc in the tag)

In the first two posts in this series we discussed the need for data persistency in containers then we discussed where the data actually lives on our systems. Now let’s look at specifying the location of the data on the underlying file system of the base OS.

This is the third post in a three part series on Persisting SQL Server Data in Docker Containers. The first post introducing Docker Volumes is here. The second post on where Docker actually stores your data is here.

So in my previous post, we discussed Docker Volumes and how they have a lifecycle independent of the container enabling us to service the container image independent of the data inside the container. Now let’s dig into Volumes a little bit more and learn where Docker actually stores that data on the underlying operating system.

This is the second post in a three part series on Persisting SQL Server Data in Docker Containers. The first post introducing Docker Volumes is here. And the third post on mapping base OS directories directly into containers is here.

What’s the number one thing a data professional wants to do with their data…keep it around. Let’s talk about running SQL Server in Containers using Docker Volumes on a Mac

This is the first post in a three part series on Persisting SQL Server Data in Docker Containers. The second post on where Docker actually stores your data is here. And the third post on mapping base OS directories directly into containers is here.