Event sourcing replay tests

まず docs/PRDs/180-event-sourcing-replay-tests.md と既存の event-sourcing ドキュメントを確認し、その後、現在の integration-test と CI/CD のエントリーポイントを特定します。replay シナリオ、シミュレートされた障害、エッジケース、パフォーマンスチェック、および Supabase/Postgres の動作が自動テストでカバーされ、関連するドキュメントが更新されれば、作業は完了です。

📋 Product Requirements Document

PRD: Event sourcing replay tests

Issue: #180
Milestone: Phase 7: Testing
Labels: integration-tests, hacktoberfest

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PRD: Event Sourcing Replay Tests

1. Overview

In the pursuit of ensuring MeshHook's reliability and robustness, particularly in handling workflows, the implementation of event sourcing replay tests is paramount. This task aims to validate the core functionality of MeshHook's event sourcing mechanism, guaranteeing that workflows can be deterministically replayed following disruptions such as system failures or manual interventions. Through these tests, MeshHook aspires to affirm its commitment to delivering a dependable and resilient workflow engine that aligns with its foundational goals of simplicity, durability, and security.

2. Functional Requirements

1. Comprehensive Test Suite: Develop an exhaustive set of integration tests specifically tailored to assess the event sourcing replay functionality across various scenarios and edge cases.
2. Scenario Coverage:
   • Successful workflow execution replays, ensuring deterministic outcomes.
   • Replays following simulated system failures, such as database disconnections or application crashes.
   • Replays after manual modifications to workflow states, testing the robustness of the recovery process.
3. Failure Injection: Implement tests that artificially induce system failures to rigorously evaluate MeshHook's replay and recovery capabilities.
4. Edge Case Analysis: Systematically identify and test edge cases within the event sourcing logic to ensure comprehensive coverage and system resilience.
5. Automated Test Execution: Seamlessly integrate the test suite into MeshHook's existing CI/CD pipeline, enabling automated execution of tests to safeguard against regressions and ensure consistent system behavior.

3. Non-Functional Requirements

• Performance: The replay functionality should be optimized to prevent any significant impact on system performance, ensuring efficient execution without undue latency.
• Reliability: Establish a high degree of confidence in the event sourcing mechanism's reliability, ensuring it functions correctly under varied and challenging conditions.
• Security: Preserve MeshHook's security standards, ensuring that the test suite does not compromise data integrity or expose sensitive information.

4. Technical Specifications

Architecture Considerations

MeshHook leverages a Postgres-native approach for event sourcing, integrating closely with Supabase Realtime for log streaming and state management. The technical specification for this task includes:

• Integration with Supabase Realtime: Utilize Supabase Realtime to monitor and validate live log outputs during test execution, ensuring accurate reflection of workflow states.
• Focus on Postgres Database: Concentrate testing efforts on the interaction between the event sourcing logic and the Postgres database, particularly the handling and replay of events.

Implementation Approach

1. Document Review: Begin by reviewing existing documentation and understanding the current event sourcing mechanism, focusing on known limitations or documented failure scenarios.
2. Design Test Scenarios: Craft a diverse range of test scenarios that encapsulate both typical and atypical usage patterns, ensuring thorough coverage of both expected and edge case behaviors.
3. Test Suite Development: Employ a reputable testing framework (e.g., Jest) to develop the test suite, adhering to MeshHook's coding standards and best practices for clarity and maintainability.
4. CI/CD Integration: Automate the execution of the test suite within MeshHook's CI/CD pipeline, configuring it to trigger on pull requests and merges to critical branches.
5. Documentation: Update MeshHook's documentation to reflect any new insights, edge cases, or behaviors uncovered during the testing process, enhancing the project's knowledge base.

Data Model and API Endpoints

• Data Model: No immediate changes to the data model are anticipated. Any necessary adjustments identified during testing will follow the project's standard process for schema modifications.
• API Endpoints: This task does not introduce new API endpoints, focusing instead on internal mechanisms.

5. Acceptance Criteria

• A comprehensive integration test suite for event sourcing replay is developed, covering a wide array of scenarios and edge cases.
• All tests within the suite pass, affirming the reliability and correctness of the replay mechanism.
• Performance benchmarks post-integration of the test suite indicate no significant degradation.
• The CI/CD pipeline is configured to execute the test suite automatically, ensuring continuous validation.
• Updated documentation reflects any new findings, providing clear guidance and insights into the event sourcing mechanism's behavior.

6. Dependencies and Prerequisites

• Full access to the MeshHook codebase and CI/CD pipeline.
• A pre-configured testing environment equipped with Supabase and Postgres.
• The event sourcing mechanism is fully implemented and operational, ensuring the test suite has a solid foundation to evaluate.

7. Implementation Notes

Development Guidelines

• Adhere to MeshHook's coding standards, prioritizing code clarity, maintainability, and adherence to project conventions.
• Select a testing framework compatible with MeshHook's technology stack, with a preference for Jest due to its widespread use and support for asynchronous testing.

Testing Strategy

• Integration Testing: Focus on validating the integration between the event sourcing mechanism and the database, ensuring accurate event replays.
• Failure Injection Testing: Employ techniques to simulate various failure states, testing the system's ability to recover and correctly replay events.

Security Considerations

• Ensure that test data and execution processes do not inadvertently expose sensitive information.
• Confirm that replay operations comply with MeshHook's existing security protocols, particularly regarding data isolation and multi-tenancy.

Monitoring and Observability

• Leverage Supabase Realtime to monitor the outcomes of test executions, comparing live log outputs against expected results for validation.
• Observe system performance during test runs to identify any potential impacts on system responsiveness or resource consumption.

By adhering to this PRD, MeshHook aims to solidify its event sourcing mechanism's reliability, ensuring that workflows can be dependably replayed following disruptions, thereby reinforcing the platform's overall robustness and reliability.

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This PRD was AI-generated using gpt-4-turbo-preview from GitHub issue #180
Generated: 2025-10-10

📎 Generated Documentation

• 📄 PRD Document: 180-event-sourcing-replay-tests.md
• 🎨 PlantUML Diagram: 180-event-sourcing-replay-tests.puml
• 🖼️ Diagram Image: 180-event-sourcing-replay-tests.png

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This issue body was auto-generated from the PRD. Original issue content is preserved in the PRD document.
Last updated: 2025-10-10