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Backend Architecture Standards

This document outlines Bayat's standards and best practices for designing, implementing, and maintaining backend systems across all projects.

Table of Contents

Architectural Styles

Supported Architectural Patterns

Select the most appropriate architectural style based on project requirements:

  • Microservices Architecture

    • Preferred for large-scale applications with multiple teams
    • Follow our \1\2)
    • Consider service boundaries based on business domains

  • Monolithic Architecture

    • Appropriate for smaller applications or initial MVPs
    • Follow our \1\2)
    • Design for potential future decomposition

  • Serverless Architecture

    • Consider for event-driven workloads and variable scaling needs
    • Implement stateless functions with clear single responsibilities
    • Address cold start and state management challenges

  • Event-Driven Architecture

    • Use for systems with asynchronous workflows
    • Implement reliable message delivery and processing
    • Define clear event schemas and versioning strategy

Architecture Decision Records

  • Document architectural decisions using Architecture Decision Records (ADRs)
  • Include context, decision, status, consequences, and alternatives considered
  • Store ADRs with project documentation

Design Principles

Core Principles

  • Separation of Concerns: Clearly separate different functional aspects
  • Single Responsibility: Components should have one reason to change
  • Don't Repeat Yourself (DRY): Avoid duplication through proper abstraction
  • Interface Segregation: Prefer many specific interfaces over one general interface
  • Dependency Inversion: Depend on abstractions, not concrete implementations
  • Command Query Responsibility Segregation (CQRS): Separate read and write operations when beneficial
  • Domain-Driven Design: Align system architecture with business domains

Quality Attributes

Prioritize these quality attributes in backend systems:

  • Reliability: Systems should function correctly under normal and adverse conditions
  • Scalability: Ability to handle growth in load and data
  • Security: Protection against unauthorized access and attacks
  • Maintainability: Ease of modification and extension
  • Performance: Responsiveness and efficiency
  • Observability: Ability to understand internal state from external outputs
  • Testability: Ease of testing at different levels

Service Design

Service Boundaries

  • Define service boundaries using business domain concepts
  • Implement bounded contexts to isolate domain models
  • Minimize coupling between services
  • Design for independent deployment

Communication Patterns

  • Synchronous Communication:

    • REST for standard CRUD operations
    • gRPC for high-performance internal service communication
    • GraphQL for flexible data fetching requirements

  • Asynchronous Communication:

    • Event-based communication for loose coupling
    • Message queues for reliable delivery
    • Publish-subscribe for one-to-many communication

State Management

  • Prefer stateless services where possible
  • Externalize session state
  • Use distributed caching for shared state
  • Implement proper concurrency control mechanisms

API Design

REST API Standards

  • Follow REST architectural principles
  • Use resource-oriented URLs
  • Implement proper HTTP method semantics
  • Use standard HTTP status codes
  • Implement consistent error responses
  • Version APIs appropriately
  • Support filtering, pagination, and sorting

GraphQL Standards

  • Define clear schema with appropriate types
  • Implement proper resolver patterns
  • Address N+1 query problems
  • Set appropriate depth and complexity limits
  • Version through schema evolution
  • Implement proper caching strategies

API Security

  • Require authentication for all non-public endpoints
  • Implement proper authorization checks
  • Validate all inputs
  • Implement rate limiting
  • Consider using API gateways for cross-cutting concerns

API Documentation

  • Document all APIs using OpenAPI (Swagger) or GraphQL schemas
  • Include example requests and responses
  • Document error conditions
  • Keep documentation in sync with implementation

Data Architecture

Data Storage Selection

Select appropriate data storage technology based on:

  • Data structure (relational, document, key-value, graph, etc.)
  • Query patterns
  • Consistency requirements
  • Scalability needs
  • Performance requirements

Relational Database Standards

  • Follow normalization principles (typically 3NF) unless performance requires otherwise
  • Design appropriate indexes
  • Implement proper constraints
  • Use migration tools for schema evolution
  • Follow naming conventions

NoSQL Database Standards

  • Select appropriate NoSQL type for specific use cases
  • Design with query patterns in mind
  • Plan for eventual consistency where used
  • Implement proper sharding/partitioning strategy
  • Document data models explicitly

Data Access Patterns

  • Use repository pattern to abstract data access
  • Implement unit of work pattern for transaction management
  • Consider CQRS for complex applications
  • Use appropriate ORM or data access libraries
  • Optimize for common query patterns

Data Integration

  • Define clear data ownership
  • Implement proper data synchronization mechanisms
  • Use change data capture (CDC) for data integration where appropriate
  • Consider event sourcing for critical data

Authentication and Authorization

Authentication Standards

  • Follow \1\2)
  • Implement token-based authentication (JWT, OAuth)
  • Support multi-factor authentication
  • Secure credential storage
  • Implement proper session management

Authorization Models

  • Implement role-based access control (RBAC)
  • Consider attribute-based access control (ABAC) for complex permissions
  • Enforce principle of least privilege
  • Centralize authorization logic
  • Audit access decisions

Identity Management

  • Use centralized identity providers
  • Implement single sign-on where appropriate
  • Support federation standards
  • Provide self-service account management
  • Implement proper user provisioning/deprovisioning

Error Handling and Logging

Error Handling

  • Use consistent error handling patterns
  • Return appropriate HTTP status codes
  • Provide meaningful error messages
  • Don't expose sensitive information in errors
  • Include correlation IDs for request tracing

Logging Standards

  • Use structured logging
  • Include contextual information (user, request ID, etc.)
  • Define appropriate log levels
  • Don't log sensitive information
  • Centralize log collection and analysis

Exception Management

  • Handle exceptions at appropriate levels
  • Don't catch generic exceptions without specific handling
  • Log exceptions with stack traces
  • Implement circuit breakers for external dependencies
  • Return user-friendly error responses

Performance and Scalability

Performance Standards

  • Define performance SLAs for key operations
  • Implement caching at appropriate levels
  • Optimize database queries
  • Use asynchronous processing for long-running tasks
  • Implement pagination for large result sets

Caching Strategy

  • Cache at multiple levels (application, database, HTTP)
  • Define appropriate cache invalidation strategies
  • Use distributed caching for scaled applications
  • Consider read-through and write-through caching
  • Document cache behavior

Scalability Patterns

  • Design for horizontal scaling
  • Implement database sharding where needed
  • Use load balancing
  • Implement proper connection pooling
  • Design for statelessness

Resource Management

  • Implement proper connection pooling
  • Close resources appropriately
  • Manage thread usage
  • Monitor memory consumption
  • Implement backpressure mechanisms

Security

Security by Design

  • Follow \1\2) standards
  • Implement security in all phases of development
  • Conduct regular security reviews
  • Stay updated on security threats
  • Use automated security scanning

Data Protection

  • Follow \1\2) standards
  • Encrypt sensitive data at rest and in transit
  • Implement proper key management
  • Apply data minimization principles
  • Follow retention and deletion policies

API Security

  • Validate all inputs
  • Implement rate limiting
  • Use TLS for all endpoints
  • Implement proper CORS policies
  • Prevent common API vulnerabilities (injection, CSRF, etc.)

Secrets Management

  • Use dedicated secrets management solutions
  • Don't store secrets in code or configuration files
  • Rotate secrets regularly
  • Restrict access to secrets
  • Audit secrets access

Testing

Testing Strategy

  • Implement comprehensive unit tests
  • Create integration tests for service interactions
  • Use contract testing for service boundaries
  • Conduct end-to-end testing
  • Implement performance testing

Testing Standards

  • Achieve high unit test coverage (minimum 80%)
  • Automate testing in CI/CD pipeline
  • Use test doubles (mocks, stubs) appropriately
  • Create repeatable tests
  • Test error conditions and edge cases

Test Data Management

  • Create appropriate test data sets
  • Don't use production data for testing
  • Reset test state between tests
  • Implement data generation tools
  • Document test data requirements

DevOps Integration

CI/CD Integration

  • Follow \1\2) standards
  • Automate build and deployment
  • Implement proper environment management
  • Use infrastructure as code
  • Implement feature flags for deployment control

Deployment Standards

  • Use containerization (Docker)
  • Implement orchestration (Kubernetes)
  • Support zero-downtime deployments
  • Implement proper rollback mechanisms
  • Automate deployment verification

Environment Management

  • Maintain consistency across environments
  • Externalize configuration
  • Use environment-specific configurations
  • Implement proper secrets management
  • Document environment differences

Documentation

Required Documentation

  • System architecture diagrams
  • API documentation
  • Data models
  • Deployment architecture
  • Operation runbooks
  • Development guides

Documentation Standards

  • Keep documentation with code
  • Use automated documentation tools where possible
  • Review and update documentation regularly
  • Use standard formats (Markdown, OpenAPI, etc.)
  • Include diagrams (C4 model recommended)

Technology Selection

Technology Evaluation

  • Evaluate technologies based on:
    • Alignment with project requirements
    • Team expertise
    • Community support
    • Performance characteristics
    • Security considerations
    • Licensing
    • Operational complexity

Approved Technologies

For specific approved technologies, see the relevant language and framework standards:

  • \1\2)
  • \1\2)
  • \1\2)
  • \1\2)
  • \1\2)

Technology Lifecycle Management

  • Plan for technology lifecycle management
  • Document upgrade paths
  • Monitor for security vulnerabilities
  • Define deprecation strategy
  • Conduct regular technology reviews

Integration Patterns

API Integration

  • Prefer RESTful APIs for service integration
  • Use GraphQL for complex data requirements
  • Implement proper error handling
  • Document integration points
  • Version APIs appropriately

Event-Based Integration

  • Use message brokers for reliable delivery
  • Implement idempotent consumers
  • Define clear event schemas
  • Version events appropriately
  • Implement dead letter queues

File-Based Integration

  • Define clear file formats and schemas
  • Implement validation for incoming files
  • Process files asynchronously
  • Implement proper error handling
  • Monitor file processing

Legacy System Integration

  • Implement anti-corruption layers
  • Document integration limitations
  • Minimize direct database access
  • Consider service virtualization for testing
  • Implement proper error handling

Monitoring and Observability

Observability Standards

  • Implement the three pillars of observability:
    • Metrics
    • Logging
    • Tracing
  • Use structured logging
  • Implement distributed tracing
  • Define key performance indicators (KPIs)
  • Create dashboards for key metrics

Health Monitoring

  • Implement health check endpoints
  • Monitor service dependencies
  • Set up alerting for critical issues
  • Implement proper incident response procedures
  • Conduct regular health reviews

Performance Monitoring

  • Monitor response times
  • Track resource utilization
  • Set up performance baselines
  • Alert on performance degradation
  • Conduct regular performance reviews

Operational Readiness

  • Create runbooks for common operations
  • Document troubleshooting procedures
  • Implement proper backup and restore processes
  • Conduct disaster recovery drills
  • Train operations staff

References