Good design patterns that make sense and can scale out ad infinitum. Automating all that can be automated — lower the bar of knowledge that lets a dev or operations engineer take advantage of the system.
This blog series focuses on presenting complex DevOps projects as simple and approachable via plain language and lots of pictures. You can do it!
I’ve written in the past about my trials and tribulations designing and running a terraform and general CI/CD platform that’s used by 10+ teams to run ~130 terraform pipelines to deploy to 50+ environments across Azure and AWS.
When designing the system, I knew that’d it’d need to scale up and out to a great degree — any pattern and solution we chose would be stressed both by upward growth (running terraform and other deploys hundreds of times per day) and outward (scaling out to hundreds or maybe thousands of pipelines and workflows). Because of that, I’m extremely sensitive to:
I’ve also had to train all the users on this system and good patterns, and for every single person, I’ve stressed that they need to read the pull request validation before approving a PR. That pull request validation runs tflint as well as terraform init + validate + plan.
And for every single person I’ve trained, I’ve had to include the caveat that on the “terraform plan” stage there will be dozens and probably HUNDREDS of trash lines that they need to ignore and scroll past to get to the real information — what terraform plan says it’s going to do based on the PR.
In this article, see if there are any differences between software developers and software engineers. What you’re about to read mostly revolves around my personal thoughts, deductions, and offbeat imagination. If you have different sentiments, add them in the comment section, and let’s dispute! So, today’s topic…
We are going to build a continuous integration pipeline with Azure Pipelines to automate the build and verification process for a TodoService.
DevOps is supposed to help streamline the process of taking code changes and getting them to production for users to enjoy. But what exactly does it mean for the process to be "streamlined"? One way to answer this is to start measuring metrics.
You can set up the Continuous Delivery with Azure DevOps directly from Azure VMs. Azure DevOps provides us a robust mechanism for Continuous Integration and Continuous Delivery. Azure DevOps also simplifies the setting up a deployment for Azure VMs where you wanted to have your code hosted as an IaaS environment.
How to create, build, deploy and configure an Azure Function using Azure DevOps, Azure CLI and Powershell.