The app is code, the tests are code, server setup (via Puppet/Chef and Docker) is code, and not surprisingly, our delivery process is now code too. Many teams chose a code-over-configuration approach. A pipeline view of the process begins with code changes, includes building, testing, and packaging the app so we always have a 'green' version of our app. The more automated this can be, the faster we can get the feedback.

We still need a reliable way to build/test/package our apps. Once we identify what kind of feedback we need and match that to our development cadence, it's time to start writing tests, yes? Well, that's only part of the process.

Jenkins Pipeline to the Rescue.Not So Fast! How fast can and must these tests run to meet our development cadence?.Which tests do we absolutely need to run, and which can we skip?.How accurate was our implementation of the test case and criteria as code?.How often do tests fail for reasons that aren't because the code isn't working?.How much of the code and it's branches actually get covered by our tests?.There are a number of challenges with test automation that raise the bar on complexity to successfully getting tests to provide us this feedback. Duh.Īs Uncle Bob Martin puts it, responsible developers not only write code that works, they provide proof that their code works. How do we do this? We test.but manual testing is takes time and is error prone, so we write automated unit and functional tests that run quickly and consistently. When we make changes, even small ones, to our codebase, we want to prove that they had no negative impact on the user experience. TL DR: The Goal Is Fast Feedback on Code Changes This article explains how to structure a mobile app pipeline using Jenkins, Docker, and Appium. In practice, however, it's not that simple. In theory, a completely Docker-ized version of an Appium mobile UI test stack sounds great. A Jenkins Pipeline for Mobile UI Testing with Appium and Docker

Appium start appium server from jenkins