I think Capistrano is a good example. Their homepage snippet shows you what a DSL is. Source: about 1 year ago

I think it's something like https://capistranorb.com/. Source: over 1 year ago

That should give you lots of stuff to research but I'll leave you with a final point: Every project is going to be different. Use the right tool for the right job; for a small application you definitely don't need Kubernetes, you might be fine without any pipeline at all. For example, Ruby on Rails projects can use a tool called capistrano to script deploys and you can run that from your local machine any time you... Source: over 1 year ago

I personally consider Jenkins a Task Runner that has a massive collection of CI plugins. Anyone can do deployments/delivery from a task runner, but any deployments I had to do in Jenkins ended up needing custom code written to do the actual work. This isn't unique to Jenkins; before the days of kubernetes, we had tools like capistrano or Config Management tools like Chef and Puppet that were capable of doing... Source: almost 2 years ago

Two deployment techs I use for non-containerized apps work in roughly the same way. Capistrano And Deployer. Source: about 2 years ago

Before updating Api Platform, you should make sure that your Api Platform routes are fully covered by tests. You can define integration tests with PHPUnit, Behat or Pest, depending on the tool you’re most comfortable with. - Source: dev.to / 7 months ago

Behat: https://docs.behat.org/en/latest/ Following: Behaviour Driven Development. Source: over 1 year ago

^ That's an example of the type of behavioral test I use. I use Behat (beha[vioral]t[est]) to run these, and it does so by opening a headless Chrome / Firefox and does the actual clicking through the real live website. Super useful to get set up - it's saved my bacon many times. Source: over 2 years ago

TLDR; Our company dockerized pretty much everything, as such to tackle long waiting time of the CI pipeline, we split the big list of behat files into chunks and process it using docker in parallel using python multiprocessing. - Source: dev.to / over 2 years ago