Resource limits configuration

Inizia leggendo il PRD, quindi esamina le impostazioni di amministrazione di SvelteKit, schema.sql, l’Orchestrator e l’Executor e i resource-limits API endpoints elencati. Confronta i pattern esistenti di sicurezza multi-tenant ed esecuzione dei workflow prima di determinare l’ambito. Il lavoro è completato quando UI, modello dei dati, enforcement, notifiche, test e documentazione soddisfano i criteri di accettazione.

📋 Product Requirements Document

PRD: Resource limits configuration

Issue: #199
Milestone: Phase 9: Deployment & Operations
Labels: production-readiness, hacktoberfest

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PRD: Resource Limits Configuration

Overview

The implementation of configurable resource limits within MeshHook, as outlined in Issue #199, is a critical feature aimed at enhancing the platform's operational efficiency, reliability, and cost-effectiveness in production environments. This feature aligns with MeshHook's Phase 9 milestone, Deployment & Operations, focusing on production readiness. By introducing resource limits, MeshHook ensures equitable resource distribution among tenants, prevents system overloads, and upholds its commitment to performance, reliability, and multi-tenant security.

Objectives

• To implement a flexible and configurable system for managing resource limits within MeshHook, ensuring stable and efficient operation.
• To provide administrators with tools to prevent resource overuse, thereby maintaining system performance and reducing the risk of outages.
• To support MeshHook's scalability and multi-tenant architecture by ensuring fair resource usage across all tenants.

Functional Requirements

1. Configuration Interface: Develop a user-friendly UI within the MeshHook admin settings for setting resource limits.
2. Resource Limits Scopes:
   • Execution Time: Cap the maximum duration a workflow can run.
   • Memory Usage: Limit the memory footprint of each workflow execution.
   • Storage: Set maximum storage quotas per tenant.
   • Concurrent Executions: Restrict the number of workflows that can run simultaneously per tenant.
3. Default and Custom Limits: Provide sensible defaults and enable customization of limits for individual tenants or projects.
4. Enforcement Mechanism: Implement real-time monitoring and enforcement of resource limits, including proactive termination of over-limit executions.
5. Notifications: Alert administrators and users via UI and email when resource usage approaches or exceeds set limits.

Non-Functional Requirements

• Performance: The configuration and enforcement of resource limits should introduce negligible overhead to the system.
• Reliability: The system must handle limit breaches gracefully, ensuring continuous and reliable operation.
• Security: Resource limit configurations must be securely managed, preventing unauthorized access or tampering.
• Maintainability: The feature should be implemented with clean, well-commented code, adhering to the project's existing architectural patterns.

Technical Specifications

Architecture Context

• Integration with SvelteKit for the resource limits configuration UI.
• Use of Supabase for storing and monitoring resource limit configurations.
• Extension of Worker components to include resource limit checks in the Orchestrator and Executor.

Implementation Approach

1. UI Design: Extend the admin settings in SvelteKit to include a new section for resource limits configuration.
2. Schema Update: Modify schema.sql to introduce a resource_limits table, including columns for each type of limit and relations to the tenants and projects tables.
3. Enforcement Logic:
   • Adapt Workflow Executor to monitor and enforce memory and execution time limits.
   • Develop a background service for tracking and enforcing storage and concurrent execution limits.
4. Integration Testing: Validate the integration with existing multi-tenant security models and performance benchmarks.
5. Documentation: Update the project documentation to cover the new resource limits feature comprehensively.

Data Model Changes

• New table: resource_limits with fields id, tenant_id, project_id, execution_time_limit, memory_usage_limit, storage_limit, concurrent_executions_limit.
• Modifications to workflows and executions to track resource usage metrics.

API Endpoints

• POST /api/resource-limits: Endpoint for creating or updating resource limits.
• GET /api/resource-limits/{tenantId}: Endpoint for fetching the resource limits of a specific tenant.

Acceptance Criteria

• Administrators can define and edit resource limits via a dedicated UI section.
• Workflow executions that exceed any of the defined resource limits are appropriately throttled or terminated.
• Administrators and users receive notifications when resource usage is near the set limits.
• The system's performance remains unaffected by the monitoring and enforcement of resource limits.
• The feature's implementation adheres to MeshHook's code quality standards and passes all defined tests.

Dependencies

• Existing MeshHook development environment and access to the codebase.
• Supabase for data storage and monitoring setup.

Implementation Notes

Development Guidelines

• Follow MeshHook's coding standards, emphasizing readability, maintainability, and comprehensive test coverage.
• Ensure all new code is reviewed by at least one other team member familiar with MeshHook's architecture.

Testing Strategy

• Unit tests for individual components handling resource limits.
• Integration tests to ensure seamless operation with existing features, especially multi-tenant RLS security.
• Performance testing to evaluate the overhead introduced by resource limit enforcement.

Security Considerations

• Secure the resource limits configuration UI with robust authentication and authorization checks.
• Validate all input data in API endpoints related to resource limits to prevent injection attacks.

Monitoring & Observability

• Extend MeshHook's monitoring to track resource usage metrics, including memory, execution time, and storage usage.
• Configure alerts for administrators when resource usage approaches critical limits.

Implementing these specifications will ensure MeshHook's system stability and operational efficiency by managing resource usage effectively, thereby supporting its scalability and multi-tenant architecture.

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This PRD was AI-generated using gpt-4-turbo-preview from GitHub issue #199
Generated: 2025-10-10

📎 Generated Documentation

• 📄 PRD Document: 199-resource-limits-configuration.md
• 🎨 PlantUML Diagram: 199-resource-limits-configuration.puml
• 🖼️ Diagram Image: 199-resource-limits-configuration.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