for api changes, what if we move the trigger pipeline code to shared?

Moving the trigger pipeline code to a shared location in Azure Data Factory (ADF) could have several implications, especially in the context of a CQRS (Command Query Responsibility Segregation) architecture. Here are some considerations:

1. Reusability: By placing the trigger code in a shared location, you can promote reusability across different features or services. This can reduce duplication and make maintenance easier, as changes to the trigger logic would only need to be made in one place.
2. Version Control: Shared code can be managed more effectively with version control systems. This allows for better tracking of changes and easier rollback if issues arise after an API change.
3. Dependency Management: Ensure that all dependencies required by the shared trigger code are properly managed. If the shared code relies on specific versions of libraries or services, these dependencies need to be documented and maintained.
4. Testing and Validation: Moving to a shared codebase may require additional testing to ensure that the trigger behaves correctly across all features that utilize it. This is especially important in a CQRS architecture where different components may have different requirements.
5. Impact on Existing Features: Consider how existing features that currently use the trigger will be affected. Ensure that the transition to shared code does not disrupt current functionality.
6. Performance: Depending on how the shared trigger is implemented, there may be performance implications. Ensure that the shared code is optimized for the expected load and usage patterns.

In summary, moving the trigger pipeline code to a shared location can enhance maintainability and reusability but requires careful consideration of dependencies, testing, and potential impacts on existing features.

References:

• Plan your migration from Azure Data Factory

Hi @Ashwini Kanjapur

Thank you for contacting to Microsoft QA.

It sounds like you're considering the implications of moving your Azure Data Factory (ADF) trigger pipeline code to a shared library within a CQRS architecture. Here's what you need to know:

Triggers and Pipeline Execution: Triggers in ADF are responsible for automate pipeline executions based on schedules or events. If you move your trigger pipeline code to a shared library, you’ll want to ensure that these triggers are still able to reference the necessary pipelines. The relationship between pipelines and triggers remains important; a trigger must be appropriately defined to facilitate pipeline execution.

Impact of Sharing: In a shared environment, you may encounter dependencies or conflicts if multiple projects or teams are using the same trigger configuration. Make sure that the changes you implement do not impact other pipeline executions negatively.

Deployment Considerations: If the trigger is live while you're making changes, it's a best practice to stop it before publishing updates. This way, you can avoid unexpected executions with potentially outdated pipeline definitions.

Testing: You might also want to conduct thorough testing after the migration to confirm that the shared trigger functions as expected with the common pipeline code.

Performance and Monitoring: After you've made the migration, monitor the execution of the shared trigger to ensure performance and reliability remain intact.

I hope this sheds some light on potential consequences of your migration!

Follow-Up Questions:

1. What specific changes are you planning to make by moving the triggers to a shared library?
2. Have you tested the triggers in a development environment after modifications?
3. Are there any specific concerns you have regarding shared resources or conflicts between teams?
4. What kind of trigger types are you planning to use (schedule, tumbling window, event-based)?

References:

• Trigger Operations and Executions - How To
• Monitor Pipelines
• Troubleshoot Pipeline Triggers
• Applying DataOps to Azure Data Factory