I have a very basic requirement: deploy files (could be .NET binaries, configuration, assets…) to an on-premise server, using an Azure DevOps YAML pipeline.

We have pipelines that are mostly started manually, and the user can set a various options:

I have the issue with Azure DevOps pipeline parameters.
I have this code:

I’m using two different build servers, one for builds with static code analysis, one without, to build some large Windows solutions.

When manually queuing a multi-stage YAML pipeline, you can specify which stages to include/exclude by deselecting them in Stages. Similarly, the Azure DevOps REST API allows you to accomplish the same thing by specifying the stagesToSkip in the post BODY..

Restrictions on which variables that can be set by a step.

If tried to use a loop variable in an if statement but it does not work.

YAML pipelines do not support pre- and post-deploy approvals that can be dynamically added. I’ve found a way of partially achieving this, see final update to my previous SO question. In summary; I created a YAML template that has 3 jobs; the first and last jobs are conditional jobs that use a ManualValidation@0 depending on a variable in a variable group, and the second job is the actual deployment of a web application.

The company I’m at is investigating whether we can migrate from classic Azure DevOps Builds and Releases towards YAML Pipelines. Using these pipelines we want to deploy to four four different environments (dev, test, acc, prod). On a regular basis we need to validate a feature that has not made it into the main branch, i.e. we deploy a feature branch to dev and/or test. Whenever the main branch is updated, the latest version of main is automatically deployed to dev and test, which is problematic when we’re in the process of testing the feature branch. Our solution with the classic pipelines is to temporary add a pre-deploy approval.

At my job, we recently converted some pipelines to be “all-in-one.” So when a merge to main happens, the pipeline has multiple stages for building –> deploy to lower environments –> deploy to production. The production deployment requires manual approval. As a result, builds will often sit at this stage as we only deploy on a certain cadence.