End-to-end workflow tests

docs/PRDs/178-end-to-end-workflow-tests.md から始め、既存のユニットテストおよび統合テストのカバレッジを確認してください。実装ファイルやテストのエントリポイントが指定されていないためです。分離したシナリオを定義する前に、SvelteKit/Supabase/Postgres スタックに対して Cypress または TestCafe を評価してください。主要なワークフロー、CI/CD の実行、および実行/拡張に関するドキュメントが、記載された受け入れ基準を満たせば完了です。

📋 Product Requirements Document

PRD: End-to-end workflow tests

Issue: #178
Milestone: Phase 7: Testing
Labels: integration-tests, hacktoberfest

---

PRD: End-to-end Workflow Tests for MeshHook

1. Overview

End-to-end (E2E) testing is a critical phase in ensuring the robustness and reliability of the MeshHook workflow engine. This PRD focuses on the development and implementation of an E2E testing suite designed to validate the entire workflow process, from webhook trigger to task execution and logging. The primary goal is to simulate real-world scenarios, providing confidence that MeshHook will perform as expected in production environments. This aligns with MeshHook's commitment to delivering a deterministic, Postgres-native workflow engine that is secure, efficient, and user-friendly.

2. Functional Requirements

1. Comprehensive Test Coverage: Develop an E2E test suite that covers all key functionalities of MeshHook, including:

   • Webhook trigger functionality and signature verification.
   • Task execution within workflows, including error handling and retries.
   • Visual DAG builder operations, ensuring workflows are correctly constructed and modified.
   • Event sourcing and replay capabilities, confirming historical data is accurately captured and can be replayed.
   • Real-time logging, verifying that log data is correctly streamed and stored.
   • Multi-tenant RLS security, ensuring data isolation and security across different tenants.

2. Real-World Scenario Simulation: The test suite must include scenarios that mimic real-world usage, including:

   • Various webhook payload types and sizes.
   • Complex DAG configurations with multiple branches and loops.
   • Failure and retry mechanisms within workflows.
   • Multi-tenant operations, ensuring RLS policies are enforced.

3. Automated Regression Testing: The suite should be capable of running automatically to detect regressions and ensure new features do not break existing functionalities.

3. Non-Functional Requirements

• Performance: Tests should be optimized to run efficiently, minimizing impact on overall system performance.
• Reliability: Test outcomes should be consistent across runs, with mechanisms in place to quickly identify and address flakiness.
• Security: Ensure that testing processes do not compromise system security or expose sensitive data.
• Maintainability: The test suite should be structured and documented in a way that allows for easy updates and additions by the development team.

4. Technical Specifications

Architecture Context

MeshHook's architecture, utilizing SvelteKit for the frontend and Supabase for backend services (including Postgres and Realtime), requires an E2E testing framework that integrates seamlessly with these technologies. The testing framework should be capable of simulating user interactions with the DAG builder and verifying backend processes like webhook handling and task execution.

Implementation Approach

1. Assessment: Conduct a thorough review of MeshHook functionalities and current test coverage to identify E2E testing needs.
2. Tool Selection: Choose tools (e.g., Cypress, TestCafe) that support both frontend interactions and backend verifications, and integrate well with MeshHook's stack.
3. Test Environment Setup: Configure isolated testing environments that mirror production settings without affecting live data.
4. Test Development: Incrementally develop tests, starting with critical workflows. Use mock services and data where necessary.
5. CI/CD Integration: Automate test execution as part of the CI/CD pipeline, running the suite on pull requests and merges to main branches.
6. Monitoring and Maintenance: Regularly review test results, updating and expanding the test suite to cover new features and use cases.

Data Model

No changes to the existing data model are anticipated for the implementation of the E2E tests. Tests will operate on isolated instances or schemas to prevent interference with production data.

API Endpoints

Existing API endpoints will be utilized for testing. No additional endpoints are required for the E2E test suite itself.

5. Acceptance Criteria

• E2E test suite covers all major MeshHook functionalities.
• Tests accurately simulate real-world usage scenarios, including complex DAGs and multi-tenant operations.
• Test suite is fully integrated into the CI/CD pipeline, running automatically on specified triggers.
• Documentation is provided on how to run and extend the E2E test suite.
• All tests consistently pass, demonstrating system reliability and functionality.

6. Dependencies and Prerequisites

• Access to isolated testing environments that replicate the production setup.
• Selection of E2E testing tools compatible with MeshHook's technology stack.
• Existing unit and integration tests are passing, ensuring system stability for E2E testing.

7. Implementation Notes

Development Guidelines

• Adhere to MeshHook's coding standards and architectural patterns.
• Write clear, maintainable tests with descriptive names and comments explaining the purpose and expected outcomes.
• Prioritize critical paths and functionalities for initial test development, expanding coverage over time.

Testing Strategy

• Employ a mix of real and mocked data to thoroughly test system behaviors under various conditions.
• Ensure tests cover both successful operations and error handling, including retries and fallbacks.
• Regularly review and update tests to reflect changes in MeshHook's features and functionalities.

Security Considerations

• Use secure, isolated environments for E2E testing, ensuring no risk to production data or operations.
• Handle all test data, especially simulated user and webhook data, securely and in compliance with privacy regulations.
• Regularly audit test processes and environments for potential security vulnerabilities or misconfigurations.

Monitoring & Observability

• Implement logging and monitoring within the test execution environment to track performance and identify issues promptly.
• Analyze test execution patterns and durations to optimize the suite for efficiency and effectiveness.

By following this PRD, MeshHook aims to establish a robust E2E testing framework that ensures the platform's reliability, security, and usability, aligning with its overarching goals of providing a dependable workflow engine for a wide range of applications.

---

This PRD was AI-generated using gpt-4-turbo-preview from GitHub issue #178
Generated: 2025-10-10

📎 Generated Documentation

• 📄 PRD Document: 178-end-to-end-workflow-tests.md
• 🎨 PlantUML Diagram: 178-end-to-end-workflow-tests.puml
• 🖼️ Diagram Image: 178-end-to-end-workflow-tests.png

---

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