The DORA organization is dedicated to helping others build software better and faster, at a higher quality, and in a way that is more efficient. They continue to compile and publish the Accelerate State of DevOps report every year, which is a fascinating read.
As a part of the report, they have identified four key metrics that identify high performing organizations in terms of software. These are divided into two areas: throughput and stability. Throughput measures are change lead time and deployment frequency. Stability measures are the change fail percentage and failed deployment recovery time.
For a long time, as I chatted with various people doing database work, it seemed that most people deployed relatively infrequently. They might deploy a couple times a week for software changes, but database changes were often less than once a week. There have always been people moving faster or slower, but that felt like the pace for a majority of people. These days, in the 2024-2025 timeframe, many people seem to be able to deploy database changes every week, often multiple times a week.
Lots of people have moved to more throughput, with more frequent deployments and less change lead time. Most of us can’t get more work out of people, so if we deploy more often, their completed work gets released quicker. Those two metrics make some sense, and I think those are good measures, but not goals. What I find is that people often need to make changes quicker either to respond to changing needs of their organization or to fix bugs they’ve introduced. I wonder what the ratio is of the former to the latter? I suspect it might be less than one, if most of your deployments are fixing bugs. I don’t mind deploying software quicker, but the design, modeling, and testing can’t be shortened.
The stability metrics are often high for most people I speak with about deployments. I don’t see a lot of failures at deployment time as code usually compiles and deploys. It’s often a day (or week) later that someone notices the code doesn’t do what they expect. Is that a deployment failure? I think not. What’s the MTTR if it’s fixed an hour after being reported a day after the deployment? Is the MTTR an hour or a day plus an hour? I don’t know how these metrics apply to databases, especially if data gets mangled and has to be corrected manually over hours/days/weeks. Is that in the MTTR? Can you even track it?
Metrics are good ways to measure you progress or health, as long as the metric doesn’t become the goal. I’ve run into a lot of customers using these metrics to measure their development, and it does help most for a period of time. Whether this continues to help them improve often depends on whether they keep focusing on their goals of delivering better quality software faster, or they focus on the metrics.
I had to demo the Flyway Autopilot system recently and created a GitHub Actions runner as a part of that. This post documents how this went.
First, if you go to the settings in a repo and click the Actions area, you see a Runners item. Click that. Notice I have no runners.
In the upper right corner, I can click a button to create one.
This gives me the instructions to get a new one. Note, these are PowerShell commands, and the first command doesn’t quite work right. Still, this is what I need.
I opened a CMD window and stared running these. Note, I need to repeat the change directory.
Now start PowerShell as the next commands are PoSh ones. When I copy the next command, it starts downloading a zip file. As of this writing, this is a 600-ish MB file.
Once this is done, you can run the next commands, which unzip and configure this. For the config, I just hit enter as I don’t have multiple groups or tags, and I leave it named as my machine. I also don’t bother to run this as a service.
The last command runs the runner agent.
If I go back to the Runner screen in Settings, I see I have an idle agent set up.
And that’s it. If I pick one of my workflows in the Actions tab, I can run it and I’ll see the job started in my runner folder. Here are my actions with the Run workflow button on the right.
If I click this, I see the job start in the CLI.
If I get back to the Actions, I’ll see things in progress. As you can see, I was slow here.
That’s about it. Now I can run local automations in my repo that connect to things like local databases, which can be handy.
Video Walkthrough
I’ve got a video of this process if you want to watch it.
The Solutions Engineers at Redgate recently released an Introduction to Redgate Flyway Autopilot course on our Redgate University. They’ve been working on this for quite some time to help people get started with Flyway in their own environment. It’s gotten smooth and slick, so I’m going to set this up in 10 minutes in this post and video, but with a twist. I’m using my schema to show you how easy this is.
I’ve been working with Flyway Desktop for work more and more as we transition from older SSMS plugins to the standalone tool. This series looks at some tips I’ve gotten along the way.
Having a SQL Server or PostgreSQL server (I’ll use SQL Server)
You will also get a Redgate Token and set up a local runner. I won’t detail those steps here, but I will have them in another post. The video will also skip those steps.
Creating a Repository
I’m working in GitHub, but you can do this in Azure DevOps. Others work, but those aren’t in the course. The main thing to do is go to the official Redgate repo at: https://github.com/red-gate/Flyway-AutoPilot-FastTrack
This brings you to this site:
From there, don’t clone or fork, but use as a template. This is in the upper right corner.
When you click this, you get the Create a new repository page, that looks like this. If you’re familiar with GitHub, this looks like any other repo. Give it a name, which must be unique in your org. I added FWAutopilot as I already have an “Autopilot” repo that is public.
You can make this public or private, but just be aware of this from the standpoint of your org, especially if you add internal schemas. You can also set a description.
Once this is created, you’ll see the repo in your org. Here’s my Autopilot repo:
This is a copy of the template all set up. Now, on to Flyway Desktop.
Creating a Project
In Flyway Desktop, I’ll click the drop down by Open Project and select Open from Version Control.
Here I’ll paste in the URL of my repo. I also check that the folder for the local clone is valid. In my case, I tend to put things in Documents/Git, but you might have your own standard.
Once this clones down, you can see a repo in the path above that looks like the online repo. Flyway Desktop will also refresh the schema, which should give you this error.
This is because the databases don’t exist. As you can see, I’ve filtered to databases with “auto” in the name and I have nothing.
If I use the file | open in SSMS, I can go into the repo and into the Scripts folder, where I see this:
I want to open the CreateAutoPilotDatabases.sql script, which looks like what you see below. This creates 5 databases and adds schema objects to one of them. The goal is for Autopilot to use Database DevOps and Flyway to migrate these changes to other databases.
Run this, and I see different databases. I’ve refreshed things, and you can see Prod has nothing but Dev has objects.
Now that I have a db, let’s refresh Flyway Desktop. Now I see no changes.
Note: If you aren’t doing this on your localhost instance, then you can edit the connections to the dev database (and other databases).
Adding Our Own Schema
Don’t start deleting schema objects yet, but you can add your own. I’ll do that. I have a script that contains a schema for baseball data. The beginning is shown below, but I’ll run this in my AutopilotDev database.
After I do this, I’ll refresh Flyway Desktop again and I see my tables. This is a partial list as the full list scrolls off the screen.
I’ll select all these from the checkbox at the top next to Object Name and then click “Save to project” in the upper right. This writes the CREATE scripts for all objects to the schema model, as you can see below in the update message.
The next step (shown at the bottom) is to generate a migration script. I’ll click that.
I get the screen below, which shows me all the changes that have been made to objects. I can select one or more of these to put into a migration script (deployment script). If I don’t select them all, then I will see those I haven’t selected re-appear here and I can add them to a different script. To keep this simple, I’ve selected them all.
When I click “Generate script” in the upper right, Flyway will create a script containing all the objects I’ve selected with the appropriate create/alter/drop code inside. Here is my one large script. You can see the start of the script below. If we scrolled, we’d see the CREATE for all the tables in here.
This project is configured to automatically generate an undo script, so below the above part, there is the undo script. Again, this is just the beginning of the script. However, you can see before we drop tables, we need to remove constraints.
Once I’m happy, I can click save and this is written as a migration script (and an undo script).
I can click Verify, which essentially runs these scripts against my shadow database, but I don’t do that if I haven’t altered the scripts. You can if you want.
Now that we’ve made some changes, let’s commit those. On the right side of Flyway Desktop is the VCS blade. You can see I have 28 changes in my repo.
If I click the “28”, this opens to the commit tab. I can also click the arrow at the top and select the commit tab. In here, I see my changes and I can include all of them or some of them and write a commit message.
I’ve selected them all and written a message, so I’ll click the drop down by commit and select the combined Commit and Push.
If I check my repo, I see this commit included. You can see this altered the schema-model and migrations folders.
Now we need to keep this Database DevOps flow going and deploy our code.
Setting Up Runners
If I check the Actions tab in my repo, I see there are two workflows configured. They are the same, but one works for Windows and one for Linux. I don’t have any runs yet and I haven’t configured a runner.
If I go to Settings in my repo and the Actions | Runners area, I’ll see this. The runners are the agents that execute your code. In this case, I need to setup a new one. I’ll detail that in another post.
Once I have a runner set up, I should see something like this:
Adding Secrets
Flyway is a licensed product, so I need to tell the runner that it is licensed to use the product. If you don’t have a license, this system can get you a 28-day trial, but if you have one, you can just use that.
Note: I’ve deleted this token, so this code doesn’t work.
Don’t close this, but open a new browser tab for your repo. Go to the Secrets | Actions section under Settings. You should see this. Click New repository secret.
The documentation notes you need to add two secrets: FLYWAY_TOKEN and FLYWAY_EMAIL. These are essentially secret variables picked up by the automation. When I click new, I add the email like this.
I added the token in the same way, pasting in the token from the portal. When I finished, I see two secrets.
Run the Automation
Check your production database (and the test one). There should be no objects, which is what we saw above.
Now, go to the Actions section of your repo. Click the Windows workflow on the left (or Linux if you used that).
Now on the right, click Run workflow, and then Run again in the pop up.
In a minute, your web page should show this running with a yellow circle before the name.
Your CLI window should look like this as well, with a job running.
If you click then name of the run on the web page, you should then see the three tasks. Here my build completed before I could get the screenshot, but yours likely has the yellow on the build database.
If I click any of the tasks, I’ll see the logging as they run. In this shot below, I’ve clicked the running prod deploy, as that was running when I was ready for the screen shot.
The output scrolls along and can be hart to follow, but after any of these are complete, you can click on them and see the task outline. Each of these items below can be expanded by clicking on the angle bracket. You can see I’ve expanded the Migrate Test DB task.
However, most of the time we assume we have a repeatable, reliable execution of our migration, so we don’t care. The proof is in checking the databases.
Here is my refreshed AutoPilotTest database.
and here is the AutopilotProd database.
I moved code from dev –> VCS –> test –> prod without executing it anywhere past Dev. This is the way changes should be made to test them before they hit prod.
We should also have feature branches, PRs, and more, but that’s beyond the 10 minutes to get started. From here, I could easily make other changes in dev and get them deployed by clicking a button in GitHub.
Summary
This process took me ten minutes. To be fair, I’d tested it a few times, but in knowing what things are needed in the docs, it took me ten minutes, which I show in a video below.
Flyway is an incredible way of deploying changes from one database to another, and now includes both migration-based and state-based deployments. You get the flexibility you need to control database changes in your environment. If you’ve never used it, give it a try today. It works for SQL Server, Oracle, PostgreSQL and nearly 50 other platforms.
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