Grpc Integration

Grpc Integration

Skill Profile

(Select at least one profile to enable specific modules)

• DevOps
• Backend
• Frontend
• AI-RAG
• Security Critical

Overview

gRPC (Google Remote Procedure Call) is a high-performance, open-source universal RPC framework using Protocol Buffers for serialization, ideal for microservices communication with efficient binary serialization, streaming capabilities, and built-in code generation.

gRPC consists of:

• HTTP/2: High-performance transport protocol
• Protocol Buffers: Efficient binary serialization format
• Code Generation: Auto-generate client and server code
• Streaming: Support for unary, server streaming, client streaming, bidirectional
• Multi-Language: Support for multiple programming languages
• Strong Typing: Type-safe contracts with .proto files

Why This Matters

• Enhance Performance: gRPC can enhance performance by 5-10x compared to REST
• Reduce Latency: HTTP/2 multiplexing reduces latency
• Reduce Bandwidth: Protocol Buffers reduce payload size by up to 70%
• Increase Developer Productivity: Code generation reduces boilerplate code
• Improve Type Safety: Strong typing reduces runtime errors

Core Concepts & Rules

1. Core Principles

• Follow established patterns and conventions
• Maintain consistency across codebase
• Document decisions and trade-offs

2. Implementation Guidelines

• Start with the simplest viable solution
• Iterate based on feedback and requirements
• Test thoroughly before deployment

Inputs / Outputs / Contracts

• Inputs:
  • Proto file definitions
  • Service requirements
  • Authentication requirements
  • Streaming requirements
• Entry Conditions:
  • Node.js 16+ is available
  • gRPC is installed
  • Proto files are defined
  • Services are available
• Outputs:
  • Proto files
  • Server implementation
  • Client implementation
  • Interceptors
• Artifacts Required (Deliverables):
  • Proto file definitions
  • Server implementation
  • Client implementation
  • Authentication interceptors
  • TLS configuration
• Acceptance Evidence:
  • RPCs work correctly
  • Streaming works correctly
  • Authentication is enforced
  • TLS is configured
• Success Criteria:
  • Services communicate efficiently
  • Streaming works
  • Authentication is secure
  • Performance is high

Skill Composition

• Depends on: error-handling
• Compatible with: express-rest, nodejs-api
• Conflicts with: None
• Related Skills: service-design, service-discovery

Quick Start / Implementation Example

1. Review requirements and constraints
2. Set up development environment
3. Implement core functionality following patterns
4. Write tests for critical paths
5. Run tests and fix issues
6. Document any deviations or decisions

# Example implementation following best practices
def example_function():
    # Your implementation here
    pass

Assumptions / Constraints / Non-goals

• Assumptions:
  • Development environment is properly configured
  • Required dependencies are available
  • Team has basic understanding of domain
• Constraints:
  • Must follow existing codebase conventions
  • Time and resource limitations
  • Compatibility requirements
• Non-goals:
  • This skill does not cover edge cases outside scope
  • Not a replacement for formal training

Compatibility & Prerequisites

• Supported Versions:
  • Python 3.8+
  • Node.js 16+
  • Modern browsers (Chrome, Firefox, Safari, Edge)
• Required AI Tools:
  • Code editor (VS Code recommended)
  • Testing framework appropriate for language
  • Version control (Git)
• Dependencies:
  • Language-specific package manager
  • Build tools
  • Testing libraries
• Environment Setup:
  • .env.example keys: API_KEY, DATABASE_URL (no values)

Test Scenario Matrix (QA Strategy)

Technical Guardrails & Security Threat Model

1. Security & Privacy (Threat Model)

• Top Threats: Injection attacks, authentication bypass, data exposure

• Data Handling: Sanitize all user inputs to prevent Injection attacks. Never log raw PII
• Secrets Management: No hardcoded API keys. Use Env Vars/Secrets Manager
• Authorization: Validate user permissions before state changes

2. Performance & Resources

• Execution Efficiency: Consider time complexity for algorithms
• Memory Management: Use streams/pagination for large data
• Resource Cleanup: Close DB connections/file handlers in finally blocks

3. Architecture & Scalability

• Design Pattern: Follow SOLID principles, use Dependency Injection
• Modularity: Decouple logic from UI/Frameworks

4. Observability & Reliability

• Logging Standards: Structured JSON, include trace IDs request_id
• Metrics: Track error_rate, latency, queue_depth
• Error Handling: Standardized error codes, no bare except
• Observability Artifacts:
  • Log Fields: timestamp, level, message, request_id
  • Metrics: request_count, error_count, response_time
  • Dashboards/Alerts: High Error Rate > 5%

Agent Directives & Error Recovery

(ข้อกำหนดสำหรับ AI Agent ในการคิดและแก้ปัญหาเมื่อเกิดข้อผิดพลาด)

• Thinking Process: Analyze root cause before fixing. Do not brute-force.
• Fallback Strategy: Stop after 3 failed test attempts. Output root cause and ask for human intervention/clarification.
• Self-Review: Check against Guardrails & Anti-patterns before finalizing.
• Output Constraints: Output ONLY the modified code block. Do not explain unless asked.

Definition of Done (DoD) Checklist

• Tests passed + coverage met
• Lint/Typecheck passed
• Logging/Metrics/Trace implemented
• Security checks passed
• Documentation/Changelog updated
• Accessibility/Performance requirements met (if frontend)

Anti-patterns / Pitfalls

• ⛔ Don't: Log PII, catch-all exception, N+1 queries
• ⚠️ Watch out for: Common symptoms and quick fixes
• 💡 Instead: Use proper error handling, pagination, and logging

Reference Links & Examples

• Internal documentation and examples
• Official documentation and best practices
• Community resources and discussions

Versioning & Changelog

• Version: 1.0.0
• Changelog:
  • 2026-02-22: Initial version with complete template structure

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