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Best Practices

Overview​

This section provides practical guidance for implementing Q01 Core APIs effectively, covering common use cases, anti-patterns to avoid, performance optimization, security hardening, testing strategies, migration paths, and troubleshooting techniques.

What You'll Learn:

  • ✅ Common implementation patterns and use cases
  • ✅ Anti-patterns and what not to do
  • ✅ Performance optimization strategies
  • ✅ Security best practices and hardening
  • ✅ Testing strategies for Core API integrations
  • ✅ Migration guide from legacy systems
  • ✅ Troubleshooting common issues

Target Audience:

  • Backend developers implementing Core API integrations
  • Frontend developers consuming Core APIs
  • System architects designing Q01-based applications
  • DevOps engineers deploying Q01 services
  • Technical leads reviewing code and architecture

Topics Covered​

Use Cases​

Common implementation patterns:

  • Product catalog management
  • Order processing workflows
  • Customer data management
  • Inventory synchronization
  • Multi-tenant applications
  • Real-time dashboards
  • Data migration projects
  • External system integration

Learn practical patterns for real-world scenarios with complete code examples.

Anti-Patterns​

What not to do:

  • ❌ Bypassing metadata validation
  • ❌ Hardcoding field names
  • ❌ Ignoring context chain
  • ❌ Direct TREC manipulation
  • ❌ Skipping COD_ON_OFF checks
  • ❌ Not using OUTBOX pattern
  • ❌ Storing business logic in clients
  • ❌ Mixing up center_dett values

Learn from common mistakes and avoid costly pitfalls.

Performance Tips​

Optimization strategies:

  • Query optimization techniques
  • Efficient pagination patterns
  • Caching strategies
  • Connection pooling
  • Batch processing
  • N+1 query prevention
  • Database indexing
  • API response compression

Practical tips to maximize performance and minimize latency.

Security Tips​

Security best practices:

  • JWT token management
  • Grant-based authorization
  • Tenant isolation patterns
  • Input validation and sanitization
  • SQL injection prevention
  • XSS protection
  • Rate limiting implementation
  • Audit trail compliance

Harden your Core API integrations against security threats.

Testing Strategies​

Testing Core API integrations:

  • Unit testing API clients
  • Integration testing with test data
  • Mock vs real API testing
  • Test data management
  • CI/CD pipeline integration
  • Performance testing
  • Security testing
  • Contract testing

Build confidence in your Core API integrations with comprehensive testing.

Migration Guide​

Migrating to Core APIs:

  • Assessment and planning
  • Data migration strategies
  • Incremental migration patterns
  • Dual-write pattern
  • Rollback strategies
  • Zero-downtime migration
  • Data validation and reconciliation
  • Post-migration monitoring

Successfully migrate from legacy systems to Q01 Core APIs.

Troubleshooting​

Common issues and solutions:

  • Permission denied errors
  • Field visibility issues
  • Context chain problems
  • Performance bottlenecks
  • OUTBOX event delays
  • Connection timeout errors
  • Data inconsistencies
  • API error codes

Diagnose and resolve common Core API issues quickly.

Quick Reference​

Essential DO's​

✅ Always:

  1. Validate tokens - Every request must include valid JWT token
  2. Check grants - Verify user has required permissions (TB_MENU)
  3. Use metadata - Leverage TB_DIM, TB_VAR, TB_COST, TB_MENU
  4. Apply context - Include source, peso, ambiente, centro_dett
  5. Respect COD_ON_OFF - Check field visibility flags
  6. Use OUTBOX - Leverage event sourcing for consistency
  7. Handle errors - Implement proper error handling and retry logic
  8. Monitor performance - Track query times and optimize bottlenecks

Essential DON'Ts​

❌ Never:

  1. Bypass validation - Don't skip token or grant checks
  2. Hardcode fields - Use metadata-driven field access
  3. Ignore context - Always pass full context chain
  4. Manipulate TREC - Use proper lifecycle operations
  5. Skip OUTBOX - Don't bypass event sourcing
  6. Store secrets - Never hardcode credentials or tokens
  7. Block on sync ops - Use async for external calls
  8. Ignore errors - Always handle and log errors properly

Development Workflow​

1. Planning Phase​

Before writing code:

  • Review dimension metadata (TB_DIM, TB_VAR, TB_COST)
  • Identify required grants (TB_MENU)
  • Understand context requirements (source, peso, ambiente)
  • Check field visibility (COD_ON_OFF flags)
  • Plan error handling strategy
  • Design test data and scenarios

2. Implementation Phase​

While writing code:

  • Use metadata-driven field access
  • Implement proper authentication (JWT)
  • Apply authorization checks (TB_MENU)
  • Include full context chain
  • Handle errors gracefully
  • Log operations for debugging
  • Write unit and integration tests

3. Testing Phase​

Before deployment:

  • Test with realistic data
  • Verify permission enforcement
  • Test error scenarios
  • Check performance under load
  • Validate OUTBOX events
  • Test rollback scenarios
  • Review security vulnerabilities

4. Deployment Phase​

During deployment:

  • Use environment-specific configuration
  • Enable monitoring and logging
  • Set up alerts for errors
  • Configure rate limiting
  • Enable audit trail
  • Test in staging first
  • Plan rollback strategy

5. Monitoring Phase​

After deployment:

  • Monitor API response times
  • Track error rates
  • Review OUTBOX event processing
  • Monitor database performance
  • Check security alerts
  • Analyze usage patterns
  • Gather user feedback

Code Quality Checklist​

✅ Core API Client Implementation​

Required:

  • JWT token authentication implemented
  • Token refresh logic in place
  • Grant checking before operations
  • Context chain included in all requests
  • Error handling with retry logic
  • Request/response logging
  • Unit tests for all operations
  • Integration tests with test data
  • Performance optimization applied
  • Security review completed

✅ Data Operations​

Required:

  • Metadata-driven field access
  • COD_ON_OFF flags respected
  • TREC lifecycle followed
  • Cascade operations configured
  • OUTBOX events processed
  • Transaction boundaries defined
  • Idempotency implemented
  • Bulk operations optimized

✅ Security​

Required:

  • Input validation on all fields
  • SQL injection prevention
  • XSS protection
  • CSRF protection
  • Rate limiting configured
  • Audit trail enabled
  • Secrets stored securely
  • Regular security audits

✅ Performance​

Required:

  • Query optimization applied
  • Appropriate indexes created
  • Caching strategy implemented
  • Connection pooling configured
  • Batch operations used
  • N+1 queries prevented
  • Response compression enabled
  • Load testing completed

Architecture Patterns​

Microservice Integration​

// ✅ Good - Core API client as shared service
class CoreAPIService {
  constructor(config) {
    this.client = new CoreAPIClient(config);
  }

  // Metadata-driven operations
  async getRecords(dimension, filters) {
    return this.client.get(`/api/v4/core/${dimension}`, {params: filters});
  }

  async createRecord(dimension, data) {
    return this.client.post(`/api/v4/core/${dimension}`, data);
  }
}

// Use in microservices
const coreAPI = new CoreAPIService({
  baseURL: process.env.CORE_API_URL,
  token: process.env.CORE_API_TOKEN
});

module.exports = coreAPI;

Event-Driven Architecture​

// ✅ Good - Subscribe to OUTBOX events
class ProductEventHandler {
  async handleProductCreated(event) {
    // Update search index
    await elasticsearch.index({
      index: 'products',
      id: event.data.PRD_ID,
      body: event.data
    });

    // Invalidate cache
    await redis.del(`product:${event.data.PRD_ID}`);

    // Send notification
    await notificationService.send({
      type: 'product_created',
      product: event.data
    });
  }
}

Frontend Integration​

// ✅ Good - Metadata-driven form generation
class DynamicForm {
  async loadFormFields(dimension) {
    // Fetch field metadata
    const fields = await coreAPI.get(`/api/v4/core/${dimension}/fields`);

    // Filter by COD_ON_OFF (N flag = visible in new form)
    const formFields = fields.filter(field =>
      field.COD_ON_OFF.includes('N')
    );

    // Generate form
    return this.renderForm(formFields);
  }
}

Performance Benchmarks​

Expected Response Times​

Read Operations:

  • Single record (GET by ID): < 50ms
  • List (10 records): < 100ms
  • List (100 records): < 200ms
  • Search with filters: < 300ms
  • Complex query with joins: < 500ms

Write Operations:

  • Single insert (POST): < 100ms
  • Single update (PUT): < 100ms
  • Batch insert (100 records): < 1000ms
  • Batch update (100 records): < 1000ms

Note: Times measured at 95th percentile, excluding network latency.

Optimization Targets​

If response times exceed benchmarks:

  1. Check database indexes
  2. Review query complexity
  3. Enable caching
  4. Optimize batch sizes
  5. Use connection pooling
  6. Profile slow queries

Common Pitfalls​

1. Context Chain Issues​

Problem: Missing context fields cause permission errors

Solution: Always include full context:

const context = {
  source: 'tenant_123',
  peso: 3,
  ambiente: 'P',
  centro_dett: 'HQ',
  modulo: 'sales',
  lingua: 'IT'
};

2. Field Visibility Errors​

Problem: Fields not visible due to COD_ON_OFF flags

Solution: Check field visibility first:

const fields = await coreAPI.getFields(dimension);
const visibleFields = fields.filter(f => f.COD_ON_OFF.includes('L'));

3. Performance Degradation​

Problem: Slow queries due to missing indexes

Solution: Analyze with EXPLAIN and add indexes:

EXPLAIN SELECT * FROM TB_ANAG_PRD00 WHERE XPRD05 = 5;
CREATE INDEX idx_prd_category ON TB_ANAG_PRD00(XPRD05);

4. Event Processing Delays​

Problem: OUTBOX events not processed timely

Solution: Monitor RabbitMQ and scale subscribers:

# Check queue depth
rabbitmqctl list_queues

# Scale subscribers
kubectl scale deployment search-indexer --replicas=3

Getting Help​

Documentation Resources​

  • Core Concepts: Understanding fundamental concepts
  • API Operations: Detailed API reference
  • Query Patterns: Advanced querying techniques
  • Write Patterns: CRUD operation patterns
  • Security: Authentication and authorization
  • Advanced Topics: Specialized features
  • Troubleshooting: Common issues and solutions

Support Channels​

  • GitHub Issues: Report bugs and request features
  • Documentation: Browse comprehensive guides
  • Community Forum: Ask questions and share knowledge
  • Technical Support: Enterprise support for production issues

Next Steps​

  1. Read Use Cases - Learn common implementation patterns
  2. Review Anti-Patterns - Avoid common mistakes
  3. Apply Performance Tips - Optimize your implementation
  4. Implement Security Tips - Harden your integration
  5. Follow Testing Strategies - Build confidence
  6. Use Migration Guide - Migrate from legacy systems
  7. Consult Troubleshooting - Resolve issues quickly

Summary​

  • ✅ Best practices ensure successful Core API implementations
  • ✅ Follow DO's and avoid DON'Ts
  • ✅ Use metadata-driven patterns
  • ✅ Implement proper security and performance optimizations
  • ✅ Test comprehensively before deployment
  • ✅ Monitor continuously after deployment
  • ✅ Learn from common use cases and anti-patterns

Key Takeaways:

  1. Metadata-driven development reduces maintenance
  2. Context chain is critical for permissions
  3. OUTBOX pattern ensures consistency
  4. Performance optimization requires monitoring
  5. Security is multi-layered (authentication, authorization, validation)
  6. Testing prevents production issues
  7. Monitoring enables proactive problem resolution