Passed Exam Today Development-Lifecycle-and-Deployment-Architect

 D is the correct answer, as utilizing automated source control, test, and build systems to test and deploy to production can help to maintain quality and reduce the risk of bugs being introduced to production. Automated systems can ensure that the code is consistent, version-controlled, tested, and validated before deploying to production. A is incorrect, as requiring developers to deploy completed code and unit tests directly to production can introduce errors and conflicts, as well as bypass the testing and validation stages. B is incorrect, as deploying all functionality together can create complexity and dependency issues, as well as delay the release of completed features. C is incorrect, as using a spreadsheet to track approved changes that should be released with change sets can be prone to human errors and inconsistencies, as well as lack of automation and integration. You can learn more about this topic in the Continuous Integration and Continuous Delivery module on Trailhead.

The architect should suggest the following actions to help UC discover the failing unit tests earlier: Train the administrators to make their changes in a special “admin changes” sandbox, and then promote to production, and ensure a metadata backup is committed to version control every day and a diff published to the release team. Training the administrators to use a sandbox can help prevent direct changes to production that can break the code or the unit tests. Ensuring a metadata backup and a diff can help identify any changes that have been made to production and compare them with the source of truth.

 The success criteria for data migration and the manual and automated data validation approaches are two key areas of UC’s data migration test plan that should be included. The success criteria define the expected outcomes and quality standards for the data migration process. The data validation approaches ensure that the data is accurate, complete, and consistent after the migration.

This is the correct answer because a partial copy sandbox can provide a subset of production data that is refreshed every 5 days. This way, the user acceptance and functional teams can test independently in isolation, and on current production data that was modified within the last week. A developer pro sandbox has a limited data storage and cannot store enough data for testing. A developer sandbox has no data and is only suitable for development and testing of code. A full sandbox can provide a complete copy of production data, but it can only be refreshed every 29 days, which may not meet the requirement of testing on data that was modified within the last week.