A dash of Yaml, it’s the perfect dressing in Azure DevOps

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Much has been said about how important version control is when working in application development. And certainly, I am not going to subtract anything, rather on the contrary, I am going to provide a new source to control as the adoption of good DevOps practices. In this case, I am going to refer to the yaml files.

This type of file is especially relevant in the creation of Azure DevOps pipelines. When we are faced with the creation of a new deployment pipeline, we have the option of doing it in a visual way, selecting the parts or elements that help us in the task or also, we have the possibility of using an .yml file, whatever that allows us to go a little faster and even reuse part of the previously implemented code.

In the image above, we can see the pipelines editor using the manual option to include the different steps to complete in our deployment. While in the following image, we see the same but as a .yml file. As you can see, the difference is obvious, but the most important thing here is that, in this second mode, the option of versioning and reusing part of the code makes special sense in order to improve the quality of our work.

That is, we could have pieces of code in .yml format that in turn were included in the global pipeline file and it would continue to work. This opens the door for us to work in a tremendously efficient way, which results in time optimization and high quality of work. So start thinking about jumping from the visual editor to the exciting world of Yaml, and soon you will begin to feel the benefits of that adventure.

Starting to integrate these .yml file templates as before with the ARM Templates, allow us to continue improving in the follow-up of good DevOps practices.

Alberto Alonso Marcos

About

My name is Alberto Alonso. Actually I work with Sogeti Spain in Business Intelligence Department with Microsoft Technologies. My profile is very orientated to customer, and how the DATA can improve the organization. My first steps in the data management were in the Pharmaceutical Sector. (I´m pharmaceutical too). I worked hard to extract and built procedures for gathering all the information across the organization. Measurement all kind of events. Aggregating different sources like ERP, LIMS, HVAC, OEE tools, and productivity machine reports.

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