In Vlocity, how are changes to a DataRaptor managed?

In Vlocity, how are changes to a DataRaptor managed?

• A. By versioning its configuration
• B. By creating backup files manually
• C. By maintaining a single configuration file
• D. By requiring user approval on changes

Answer: (A)

In Vlocity, DataRaptors utilize a versioning system to manage changes to their configuration. This allows developers to create different versions of a DataRaptor for various use cases, ensuring that older versions remain intact and can be reverted to if necessary. Versioning provides a structured approach to track modifications, differentiate between development stages, and facilitate collaboration among teams, as multiple versions can coexist and be tested independently. This methodology of versioning supports best practices in software development, enabling smoother updates and ensuring that any alterations do not disrupt existing functionalities or integrations. The ability to version control is crucial for maintaining the integrity of complex data operations and allows developers to implement changes without affecting the live environment immediately.

In Vlocity, DataRaptors utilize a versioning system to manage changes to their configuration. This allows developers to create different versions of a DataRaptor for various use cases, ensuring that older versions remain intact and can be reverted to if necessary. Versioning provides a structured approach to track modifications, differentiate between development stages, and facilitate collaboration among teams, as multiple versions can coexist and be tested independently.

This methodology of versioning supports best practices in software development, enabling smoother updates and ensuring that any alterations do not disrupt existing functionalities or integrations. The ability to version control is crucial for maintaining the integrity of complex data operations and allows developers to implement changes without affecting the live environment immediately.