Engineering fundamentals checklist for Power Platform enterprise development

This Checklist follows the best practices outlined in the Microsoft Solutions Playbook's Engineering Fundamentals Checklist. It helps development teams implement essential engineering principles for enterprise development on the Power Platform. By adhering to these guidelines, teams can effectively build and deliver high-quality solutions.

Source Control


  • [ ] A build and release pipeline/workflow is established for each Power Platform solution aimed at a production environment.
  • [ ] Commits to the primary development branch are validated via automatic build pipeline/workflow.
  • [ ] Commits to the primary testing branch trigger solution deployment via automatic build pipeline/workflow.
  • [ ] Commits to the production branch trigger solution deployment via automatic build/release pipeline/workflow.
  • [ ] Consider adopting the ALM accelerator for Power Platform as described in Configure the ALM accelerator manually.


  • [ ] Automated tests for supported components are integrated into build pipelines. For components that don't support automated tests, a thorough manual testing strategy is devised and documented.



Developing Canvas Apps & Power Automate Cloud flows


  • [ ] For project team, assign an appropriate Power Platform license for the development team during the project development.
  • [ ] Before UAT and go-live, it is crucial to comprehend the Power Platform license requirements for the different elements used in the target solution. The elements include Power Apps, Power Automate, Power Virtual Agent, Power Pages, and Dataverse storage requirements. Understanding these licensing aspects is essential for the target end-user groups.
  • [ ] Assist procurement team and Microsoft representatives, if necessary, in determining the correct license SKUs for production.
  • [ ] Consider Performance profiles for Power Automate, determine the required licensing accordingly.
  • [ ] Take into account the Requests limits and allocations when dealing with bulk data operations and integration requirements. These limits are crucial to consider while working on the solution.