AWS Testing, please disregard

I understand that you are conducting User Acceptance Testing (UAT) for AWS services. When performing tests in AWS environments, it's important to follow proper procedures to ensure that your test activities do not interfere with production systems or trigger unnecessary responses from support teams.

For AWS Managed Services (AMS) specifically, when testing incident reports or service requests, you should include the flag "AMSTestNoOpsActionRequired" in the subject line of your test submissions. This indicates to the AMS operations engineers that the incident or request is for testing purposes only, and they will not respond to these test cases.

In the context of a multi-account AWS architecture for enterprise machine learning platforms, there is typically a dedicated Testing/UAT account. This account is used by MLOps engineers to build and train ML models using automated pipelines, leveraging services like AWS CodePipeline and AWS CodeBuild. It's important to note that data scientists and ML engineers usually do not have change access to this Testing/UAT account, though they may be granted read access to view model training metrics or logs if necessary.

For other AWS services, like Amazon Lex, there are built-in testing tools such as the "Test workbench" that allow for automated testing of chatbots and conversational interfaces.

Remember that thorough testing in appropriate environments is crucial before moving any changes or new features to production. Ensure that your development and QA teams have performed sufficient testing to meet your organization's requirements and that any discovered bugs have been resolved through proper channels (e.g., a bugfix branch) before proceeding to staging or production environments.
Sources
AWS accounts - Build a Secure Enterprise Machine Learning Platform on AWS
Testing a service request in AMS - AMS Advanced User Guide
lex automated tests | AWS re:Post
Testing environment - AWS Prescriptive Guidance