Back for more I see!! Well glad you’ve come back to round three where we are going to make a few more minor adjustments to our container and run our first shell script.
Make sure your container is running by executing the following command in your command prompt window: docker ps If you don’t see the name of your container you can simple run this command docker start NAMEOFYOURCONTAINER in the command prompt.
So here we are back for Part 2 (I highly recommend you read Part 1 if you haven’t yet). In this post we are going to start configuring our containers and our SQL Instances to make them a little more functional and useful. In the first post, we really just created the containers with all the default settings. That means that all the storage is going to be inside the container. If it is deleted, the storage goes with it. So instead, to make the container more robust and upgradable, we are going to map some local storage on my host machine.
Let’s first take a look at the way I have my disk/folder structure laid out. Again, this is on my personal computer so it’s not a best practice for production and more suitable for development environments.
For each container, I’m creating a separate folder with the MSSQL paths that I need to put my databases, transaction log, and backup files on. Additionally, under the DockerMount folder I have a folder called sqldockershared (which I will put some shared content in later).
Recently, with the help of a colleague at work, I’ve started to dabble a little with containers. I had a customer that requested some specific code to be tested, and I realized that I didn’t have my own local instance of SQL running (always good to have a local one). I decided to try to make this process easier instead of going the traditional route of creating a Virtual Machine and also to help me learn a new technology. In these series of posts, I’m going to document my process of creating a Mini Data Lab for SQL Server on my desktop using Docker. It is intended to be for beginners and in no way is an article for best practices or production deployments.