A Fine Slice Of SQL Server
Grant Fritchey gives us the low-down on learning about DevOps:
If you’re attempting to implement automation in and around your deployments, you’re going to find there is quite a steep learning curve for DevOps and DevOps-style implementations. Since adopting a DevOps-style release cycle does, at least in theory, speed your ability to deliver better code safely, why would it be hard?
Click through for an idea, including tools to use and some first steps.
Comments closedMartin Schoombee walks us through changing data source credentials on deployment with Power BI:
The method we need to use here is the Patch method. Why is it Patch and not Post like we did with the parameters? Great question, and the “devil is in the details”…the method dictates how the underlying resource or attribute is modified, and the Patch method in this case means that there are partial (and in-place) modifications to an existing resource. Read more about the differences between Post, Put and Patch here.
This is one of those areas where Power BI can be quite a letdown if you only use the UI.
Comments closedKevin Chant has some frequently asked questions:
5: Have you moved from various services into Azure DevOps?
Yes, I have. In fact, one team used various services and applications and we went all in with Azure DevOps. Organizing our work using the boards, using the Git repos and using Azure Pipelines a lot.
Click through for additional questions, as well as answers.
Comments closedDavid Smith explains MLOPS and GitHub actions in a talk:
In the talk, I demonstrate the process in action (the demo starts at the 14:30 mark in the video below). I used Visual Studio Code to edit the
app.Rfile in repository, and then pushed the changes to GitHub. That immediately triggered the action to deploy the updated file via SSH to the Shiny Server, running in a remote VM. Similarly, changes to the data file or to the R script files implementing the logistic regression model would trigger the model to be retrained in the cluster, and re-deploy the endpoint to deliver new predictions from the updated model.
Click through for a quick summary, link to the repo, and embedded video of the talk.
Comments closedIf we rollback with kubectl rollout undo the pods in the newest replicaset are deleted, and pods in an older replicaset are spun back up, rolling back the upgrade.
But there’s a potential problem here. What happens if that old replicaset is deleted?
If that happens, we wouldn’t be able to rollback the upgrade. Well we wouldn’t be able to roll it back with kubectl rollout undo, but what happens if we’re using Helm?
Read on to learn how the whole thing works.
Comments closedGavin Campbell shows how you can pull secrets out of an Azure DevOps Pipeline:
For secrets created in the Azure DevOps UI, whether pipeline-scoped or in a variable group, it is not so simple to retrieve the variables after creation. This might be required for a number of reasons, most often troubleshooting. The need to do this is often an indicator that the project should have been using an Azure Key Vault in the first place.
Previously it was necessary to jump through some hoops to access secret variables, but it turns out this is no longer required. It also appears the recommended approach of mapping secrets to environment variables is currently not working for secret variables from variable groups.
I second the notion of using Key Vault for secrets management.
Comments closedKamil Nowinski has part two on a series about releasing Azure Data Factory code:
Struggling with #ADF deployment? adf_publish branch doesn’t suit your purposes? Don’t have skills with PowerShell? I have good news for you. There is a new tool in the market. It’s a task for Azure DevOps Release Pipeline to deploy whole ADF from code (JSON files) to ADF instance in Azure. Behind the scenes, it runs the PowerShell module which does all job for you.
Sounds unbelievable? But it’s real! Check it out for yourself.
Click through for the video.
Comments closedKamil Nowinski shares how to deploy Azure Data Factory flows via Azure DevOps:
Struggling with #ADF deployment? adf_publish branch doesn’t suit your purposes? Don’t have skills with PowerShell? I have good news for you. There is a new tool in the market. It’s a task for Azure DevOps Release Pipeline to deploy whole ADF from code (JSON files) to ADF instance in Azure. Behind the scenes, it runs the PowerShell module which does all job for you.
Sounds unbelievable? But it’s real! Check it out for yourself.
Click through for a video.
Comments closedSheldon Hull takes us through using Pester to automate operations tasks:
In my example, let’s start small and say you just have PowerShell, and some servers.
What I’ve discovered is that to actual validate DevOps oriented work is completed, you typically go through the equivalent of what a Cucumber test would have. This “checklist” of validations is often manually performed, lacking consistency and the ability to scale or repeat with minimal effort.
Consider an alternative approach to helping solve this issue, and expanding your ability to automate the tedious testing and validation of changes made.
Read on for an example as well as some additional thoughts from Sheldon.
Comments closedSheldon Hull has an essay on site reliability engineering in practice:
I’ve always been focused on building resilient systems, sometimes to my own detriment velocity wise. Balancing the momentum of delivery features and improving reliability is always a tough issue to tackle. Automation isn’t free. It requires effort and time to do correctly. This investment can help scaling up what a team can handle, but requires slower velocity initially to do it right.
How do you balance automating and coding solutions to manual fixes, when you often can’t know the future changes in priority?
This is personal experience rather than prescriptive guidance. Very interesting personal experience.
Comments closed