[ENH] Execution Pipeline for Deterministic Cache Invalidation on Workflow Definition Events

[sfmskywalker]

Currently, to ensure that triggers are indexed on "fresh" workflow definitions, cache invalidation occurs during "publishing" / "retracting" / "deleting" events. This is done to ensure that the trigger indexer accesses the most up-to-date workflow definition from the cache.

However, this approach relies on the timing of these events, which can seem arbitrary. To improve this process, we should consider implementing an execution pipeline for publishing / retracting / deleting events. This pipeline would allow for deterministic control over the steps executed during these events, ensuring a more reliable and maintainable cache invalidation process.

Goals:

• Introduce a structured execution pipeline for publishing, retracting, and deleting events.
• Ensure deterministic cache invalidation timing.
• Improve deterministic processing of the workflow definition update process.

Benefits:

• Consistent and predictable cache invalidation + trigger indexing.
• Clear separation of concerns and more structured event handling.
• Allows additional steps to be added to the pipeline, increasing extensibility.

Additional Comments

What if publishing fails and triggers have already been stored; how do we ensure data integrity? Perhaps we need a separate issue concerning atomic operations.

[glime-ai[bot]]

To address the goals outlined in the question, you can implement an execution pipeline for publishing, retracting, and deleting workflow definitions in Elsa Workflows. Here's a high-level approach to achieve this:

1. Define the Pipeline Stages: Identify the stages that should be part of the pipeline, such as validation, pre-processing, cache invalidation, trigger indexing, and post-processing.

2. Create Pipeline Handlers: For each stage, create handlers that perform the necessary actions. Handlers should be designed to be independent and reusable.

3. Implement the Pipeline Executor: Develop a pipeline executor that runs the handlers in the defined order. The executor should manage the execution context and pass it to each handler.

4. Integrate with Workflow Events: Hook the pipeline executor into the workflow definition's lifecycle events (publishing, retracting, deleting). Ensure that the executor is called whenever these events occur.

5. Cache Invalidation: Include a handler in the pipeline specifically for cache invalidation. This handler should clear the relevant cache entries to ensure that trigger indexing operates on the latest workflow definitions.

6. Trigger Indexing: After cache invalidation, run the trigger indexing handler to update the trigger information based on the latest workflow definitions.

7. Error Handling: Implement robust error handling within the pipeline to manage exceptions and ensure that the pipeline can gracefully handle failures.

8. Logging and Monitoring: Add logging and monitoring capabilities to the pipeline to track its execution and performance.

9. Testing: Thoroughly test the pipeline to ensure that it behaves as expected and that cache invalidation and trigger indexing are deterministic.

10. Documentation: Document the pipeline, its stages, and how to extend it. This will help future developers understand and maintain the system.

By implementing such a pipeline, you can achieve deterministic control over the cache invalidation and trigger indexing process, leading to a more reliable and maintainable system. Additionally, this structured approach allows for easier extension and integration of new steps in the future.

This comment was generated by Glime.