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Architecture Principles

Owner: Mahdi Moradi
Status: Draft
Version: 0.1.0
Last Updated: 2026-03-16
Applies To: Bornara AI

Overview​

This document defines the core architecture principles that guide technical decision-making across all Bornara AI projects. These principles ensure consistency, scalability, and maintainability of our technical solutions.

Core Principles​

1. Security First​

Principle: Security considerations must be integrated from the beginning of any project, not added as an afterthought.

Guidelines:

  • Implement defense in depth
  • Follow principle of least privilege
  • Encrypt data in transit and at rest
  • Regular security audits and penetration testing
  • Zero trust architecture

Validation:

  • Security review required before production deployment
  • Automated security scanning in CI/CD pipeline

2. Cloud-Native Design​

Principle: Design applications to leverage cloud platform capabilities fully.

Guidelines:

  • Use managed services when available
  • Design for horizontal scalability
  • Implement stateless services
  • Use infrastructure as code
  • Embrace serverless where appropriate

Validation:

  • Architecture review includes cloud-native assessment
  • Cost optimization review quarterly

3. API-First Development​

Principle: Design and document APIs before implementing features.

Guidelines:

  • OpenAPI/Swagger specifications required
  • Versioned APIs with backward compatibility
  • RESTful design patterns
  • Comprehensive API documentation
  • Rate limiting and throttling

Validation:

  • API spec reviewed before implementation
  • API documentation published with release

4. Observability by Default​

Principle: Every service must provide visibility into its operation and health.

Guidelines:

  • Structured logging
  • Distributed tracing
  • Metrics and monitoring
  • Health check endpoints
  • Dashboards for key metrics

Validation:

  • Observability checklist completed before production
  • Runbooks include troubleshooting with observability tools

5. Automation Over Manual Processes​

Principle: Automate repetitive tasks to improve reliability and efficiency.

Guidelines:

  • CI/CD for all code deployments
  • Infrastructure as code
  • Automated testing (unit, integration, E2E)
  • Automated rollback capabilities
  • Self-service deployment tools

Validation:

  • Manual deployment requires exception approval
  • Automation coverage metrics tracked

6. Data Privacy and Compliance​

Principle: Comply with data protection regulations and respect user privacy.

Guidelines:

  • Data classification and handling policies
  • GDPR/CCPA compliance
  • Audit logging for sensitive data access
  • Data retention and deletion policies
  • Privacy by design

Validation:

  • Privacy impact assessment required
  • Compliance checklist signed off

7. Modular and Maintainable​

Principle: Design systems as loosely coupled, highly cohesive modules.

Guidelines:

  • Domain-driven design
  • Microservices where appropriate
  • Clear service boundaries
  • Minimize dependencies
  • Refactor regularly

Validation:

  • Architecture review assesses coupling
  • Technical debt tracked and prioritized

8. Performance and Efficiency​

Principle: Design for optimal performance while being cost-conscious.

Guidelines:

  • Performance requirements defined upfront
  • Load testing before production
  • Caching strategies
  • Database query optimization
  • Resource usage monitoring

Validation:

  • Performance SLAs defined
  • Regular performance testing

9. Resilience and Fault Tolerance​

Principle: Systems must gracefully handle failures and recover automatically.

Guidelines:

  • Circuit breakers and retry logic
  • Graceful degradation
  • Chaos engineering practices
  • Multi-region deployment for critical systems
  • Disaster recovery plans

Validation:

  • Failure mode analysis completed
  • DR plan tested periodically

10. Developer Experience​

Principle: Optimize for developer productivity and satisfaction.

Guidelines:

  • Clear documentation
  • Consistent tooling and patterns
  • Fast feedback loops
  • Local development environments
  • Pair programming and code review

Validation:

  • Developer satisfaction surveys
  • Onboarding time tracked

Architecture Decision Records (ADRs)​

All significant architecture decisions must be documented using ADRs.

ADR Template​

# ADR-XXX: [Title]

## Status

[Proposed | Accepted | Deprecated | Superseded]

## Context

[What is the issue we're seeing that is motivating this decision?]

## Decision

[What is the change we're proposing and/or doing?]

## Consequences

[What becomes easier or more difficult with this change?]

## Alternatives Considered

[What other options were evaluated?]

Technology Selection Criteria​

When evaluating new technologies, consider:

  1. Maturity: Is it production-ready?
  2. Community: Active community and support?
  3. Licensing: Compatible with our needs?
  4. Skills: Do we have internal expertise?
  5. Vendor Lock-in: Can we migrate if needed?
  6. Cost: Total cost of ownership?
  7. Security: Known vulnerabilities?
  8. Compliance: Meets regulatory requirements?

See Approved Technologies for current selections.

Standards Compliance​

All projects must adhere to:

Architecture Review Process​

When Required​

  • New projects or major features
  • Significant technology changes
  • Before production deployment
  • Annual review for existing systems

Review Checklist​

  • Aligns with architecture principles
  • Security review completed
  • Performance requirements defined
  • Observability implemented
  • Cost estimate provided
  • DR plan documented
  • ADR created for key decisions

Exceptions​

Exceptions to these principles require:

  • Technical justification
  • Risk assessment
  • Mitigation plan
  • CTO approval

Updates and Evolution​

These principles are living documents and will evolve based on:

  • Lessons learned
  • Technology advancements
  • Business priorities
  • Industry best practices

Review Cycle: Quarterly

Next Review: 2026-06-16