Who has written an Argo Workflow spanning hundreds, if not thousands, of lines of YAML in a single file? And how much of it was unit tested? Integration tested? System tested only?! When extending the workflow, how was navigation through that YAML file? As we iterate on our Workflows and they grow into behemoths, we become less secure making changes and progress slows down, not to mention that working with YAML can hinder, rather than help, us.

Hera introduces native Python-functions-as-templates for your Workflows. Writing Workflows in Python is more intuitive and reflects the YAML spec of Argo through the use of context managers, so you’ll find yourself right at home coming from YAML! Hera offers a range of benefits over YAML, from all the natural benefits of Python modularization and packaging, to unit testing for individual functions and end-to-end tests of Workflows themselves.

Come learn how creating DAGs, loops, and more out of Python functions is made simpler by using Hera!