Introducing the Regression Suite Automation Tool (RSAT)

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When we wrote of the new continuous update model for Dynamics 365 for Finance and Operations, we mentioned a new tool for regression testing—the Regression Suite Automation Tool, or RSAT for short.

RSAT is now in public preview. The goal of this tool is to reduce the amount of manual effort required to test new updates for existing deployments.

To do this, the RSAT tool leverages components you should already have in place from your D365 F&O implementation—Business Process Modeler (BPM) libraries and Azure DevOps (formerly Visual Studio Team Services) project. The diagram below illustrates how these tools link together.

what is an rsat tool

Obviously, a key component of this process is the task recording itself, which makes up a user acceptance test library. For an overview of this, see Microsoft’s documentation on using task guides and creating user acceptance tests.

For information on how to synchronize libraries from LCS to Azure DevOps, please visit Microsoft’s own documentation on the matter.

Check out the recording of Jason Abed’s session from Ignite 2018 for a brief overview:

In the coming weeks we’ll post more detailed content of how to record, build an execute tests.

If you are feeling adventurous, the RSAT tool and user guide are available for download.

Have any questions about the RSAT tool or anything else about Dynamics 365 for Finance and Operations? Please contact us at any time!

This publication contains general information only and Sikich is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or any other professional advice or services. This publication is not a substitute for such professional advice or services, nor should you use it as a basis for any decision, action or omission that may affect you or your business. Before making any decision, taking any action or omitting an action that may affect you or your business, you should consult a qualified professional advisor. In addition, this publication may contain certain content generated by an artificial intelligence (AI) language model. You acknowledge that Sikich shall not be responsible for any loss sustained by you or any person who relies on this publication.

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