As the mainstream support for Microsoft Dynamics AX 2009 Service Pack 1 (SP1), Dynamics AX 2012, and Dynamics AX 2012 R2 has ended on October 9, 2018, customers using AX ERP are looking to embrace the cloud. Ever since Microsoft Dynamics AX (on-premise) has become Dynamics 365 Finance & Operations (cloud-based), automated testing has turned from “nice to have” to “absolutely mandatory”.
As migration from Dynamics AX to Microsoft Dynamics 365 (“D365”) Finance and Operations is multifaceted and goes beyond a simple technology transition, it is recommended that cloud migration strategy should be focussed on “testing”. Organizations need to test the applications in the cloud to ensure their stability otherwise code breakage could lead to business disruption.
Cloud migration can be a very painful experience if done incorrectly. Testing ensures that cloud migration is executed correctly and applications are performing as per business requirements. With the help of testing, users can ensure that the application is delivering the best User experience, data flow is constant and backend processes are working fine.
In case, organizations fail to perform adequate testing then it may lead to issues like database errors, application/website crashes, or business process disruption that can be extremely costly in terms of time, resources, and customer goodwill.
So, organizations looking to migrate from Dynamic AX to D365 should make their migration strategies with a focus on testing – Build Verification Test, Unit Testing, Regression Testing, and UAT.
Dynamics 365 Automation Testing isn’t a child’s play
Automation Testing of Dynamics 365 is somewhat challenging. As Microsoft is committed to its customers, it regularly deploys updates (Wave 1 & Wave 2) under the OneVersion umbrella to offer new functionality latest features, and improved business processes.
Prior to deployment in the production, these updates need to be tested to analyze their impact on the current processes to prevent business disruption. Since Dynamics 365 is a complex web application consisting of nested iFrames, deep object trees, and dynamic IDs for child windows, automating it with open-source libraries like Selenium is very difficult.
Due to the dynamic nature of elements, testers need to spend a lot of time and effort in identifying the right element in the application to perform the action.
Another test automation challenge with Dynamics 365 Applications is the UI standard that differs from version to version. It means that even a slight change in code can impact the UI i.e. screens, buttons, user flows, or user inputs. So, multiple versions need to be changed in the locator strategy and Object Repository (OR) to maintain tests for each version.
The problem with some of the automation tools is that they use static test scripts that cannot automatically adapt and overcome the UI changes in Dynamics 365 Applications resulting in test failures, flaky/brittle tests, build failures, inconsistent test data, and more.
Conclusion
Cloud adoption has its own benefits like low total cost of ownership, continuous application update, real-time information, mobility, etc.
However, with these benefits, there also come some challenges and responsibilities. Organizations that are looking to migrate from on-prem Dynamics AX to cloud-based Dynamics 365 need to understand that manual testing cannot help them as it is error-prone, fragile, costly, and can put your business to risk.
As Dynamics 365 is an ever-evolving application due to OneVersion Updates, organizations need to prepare themselves for continuous testing in order to embrace continuous innovation. Test automation has its unique perks like quick feedback, accelerated results, low cost, greater efficiency, more accuracy, and broader coverage.
However, leveraging open source libraries like Selenium is of no help in the case of test automation of dynamic applications like Microsoft Dynamics 365 CRM. You need an autonomous test platform that not only helps you during migration but also at regular releases.
The model-based testing approach helps you to seamlessly migrate without any risk while AI-driven Impact Analysis helps you to embrace innovation at an accelerated pace. The use of advanced technologies like machine learning, object-oriented algorithms, and self-healing capabilities will make your test scripts maintenance a breeze.