Realtime log streaming (Supabase)

[ralyodio]

📋 Product Requirements Document

PRD: Realtime log streaming (Supabase)

Issue: #164
Milestone: Phase 6: Observability
Labels: logging, hacktoberfest

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PRD: Realtime Log Streaming (Supabase) for MeshHook

1. Overview

Purpose

The implementation of realtime log streaming using Supabase Realtime represents an essential enhancement to the MeshHook workflow engine's observability features. By providing users with live feedback on their workflow executions, this functionality is pivotal in improving the debugging experience, optimizing workflow performance, and maintaining the system's reliability and user trust.

Alignment with Project Goals

This feature directly supports MeshHook's core goals by leveraging Postgres-native capabilities through Supabase for real-time data streaming. It ensures the platform remains webhook-first, deterministic, and secure while enhancing its observability and user experience without compromising on performance or simplicity.

2. Functional Requirements

1. Real-time Streaming: Implement a mechanism to stream workflow execution logs to the user interface in real-time, ensuring minimal latency.
2. User Interface Integration: Develop a user-friendly interface for viewing, filtering, and searching through the log stream in real-time.
3. Multi-tenancy and Security Compliance: The streaming mechanism must comply with MeshHook's existing multi-tenant RLS security model, ensuring users only access logs they are authorized to view.
4. Error and Warning Highlighting: Implement logic to automatically identify and highlight errors and warnings within the log stream, aiding users in quickly spotting and addressing issues.

3. Non-Functional Requirements

• Performance: The feature must be optimized to handle high volumes of log data with minimal impact on the database and application performance.
• Scalability: Designed to efficiently scale with the increased workload and number of concurrent users without degradation in performance.
• Reliability: Aim for 99.9% uptime for the log streaming feature, ensuring robustness and fault tolerance.
• Security: Adhere to strict security protocols for data transmission and access, ensuring compliance with MeshHook's security guidelines.

4. Technical Specifications

Architecture Context

The MeshHook system utilizes SvelteKit for the frontend and Supabase for backend services, including database management, real-time data streaming, and multi-tenant security. This feature's integration will extend the existing Supabase Realtime setup to include the streaming of log data to authenticated users.

Implementation Approach

1. Review Existing Systems: Analyze the current logging and Supabase Realtime configurations to identify any required adjustments or optimizations.
2. Configure Supabase Realtime for Logs: Enable and configure Realtime subscriptions for the logs table in Supabase, ensuring data changes are published and accessible in real-time.
3. Develop Client-side Subscription Logic: Implement subscription logic in the SvelteKit frontend to receive real-time log updates, utilizing Supabase Realtime's capabilities.
4. UI Development: Design and implement the user interface for log streaming, incorporating features for real-time data display, filtering, searching, and error/warning visualization.
5. Performance Optimization and Testing: Conduct thorough testing to ensure feature reliability and performance, making necessary adjustments for optimization.
6. Documentation: Update the project documentation to include details on the new feature's configuration, usage, and integration points.

Data Model Changes

No significant changes to the existing data model are required. However, ensure the logs table is optimized for real-time streaming, considering indexing and partitioning strategies for efficient data access and updates.

API Endpoints

No new API endpoints are required for this feature. It leverages existing Supabase Realtime subscriptions for data streaming.

5. Acceptance Criteria

• Real-time streaming of workflow logs is operational, with updates reflected in the user interface immediately.
• Logs are streamed securely, adhering to MeshHook's multi-tenant RLS security model.
• The user interface supports effective real-time filtering, searching, and error/warning highlighting within the log stream.
• Performance benchmarks are achieved, confirming the feature does not negatively impact the system's performance.
• Comprehensive testing verifies the feature's reliability, scalability, and security compliance.

6. Dependencies

• Supabase Realtime: Existing configuration must support additional subscriptions for the logs table.
• Existing Logging Infrastructure: Must be compatible with real-time streaming requirements and optimized for performance and security.

7. Implementation Notes

Development Guidelines

• Follow the project's existing coding standards, leveraging modern JavaScript and Svelte features for clean and efficient code.
• Adhere to TDD principles, prioritizing the creation of unit and integration tests early in the development process.
• Ensure code quality and consistency by adhering to the project's ESLint and Prettier configurations.

Testing Strategy

• Unit Tests: Cover new functionality related to real-time log streaming and UI updates.
• Integration Tests: Focus on the integration with Supabase Realtime and the existing logging system, ensuring seamless operation and security compliance.
• E2E Tests: Simulate user interactions with the log streaming feature to validate its functionality in real-world scenarios.

Security Considerations

• Ensure encrypted data transmission and comply with MeshHook's security guidelines and RLS policies.
• Regularly review and update security measures to safeguard against new vulnerabilities.

Monitoring & Observability

• Incorporate monitoring tools to track the feature's performance and reliability, setting up alerts for any anomalies or downtime affecting log streaming.

This PRD outlines the framework for implementing real-time log streaming in MeshHook, ensuring the feature enhances the platform's observability, user experience, and overall value proposition.

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This PRD was AI-generated using gpt-4-turbo-preview from GitHub issue #164
Generated: 2025-10-10

📎 Generated Documentation

• 📄 PRD Document: 164-realtime-log-streaming-supabase.md
• 🎨 PlantUML Diagram: 164-realtime-log-streaming-supabase.puml
• 🖼️ Diagram Image: 164-realtime-log-streaming-supabase.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