## Technical Requirements and Specifications
Provide the comprehensive technical requirements and specifications for product development, translating functional needs into detailed technical architecture, implementation guidelines, and development standards. It aims to provide a robust foundation for engineering teams, ensuring the product is built to deliver functional requirements, maintain scalability, and adhere to security and performance benchmarks.
### Prerequisites
Before proceeding, ensure the following are completed and validated:
- **Functional requirements**: Clearly defined and approved.
- **Technical constraints**: Identified from initial requirements gathering.
- **Performance and scalability needs**: Thoroughly understood.
- **Integration requirements**: Explicitly defined.
- **Team technical capabilities**: Assessed and considered.
- **Budget and timeline**: Established and aligned with technical scope.
- **Compliance and regulatory requirements**: Fully understood.
### 1. Technical Architecture Overview
**Objective**: Define the high-level technical architecture and foundational principles.
**Required Elements**:
- **Architecture Philosophy**: The overall approach to technical architecture and design principles.
- **Architecture Patterns**: Key architectural patterns (e.g., microservices, monolithic, serverless, event-driven, layered) with rationale for selection.
- **System Components**: Major system components and their relationships.
- **Technology Stack**: Core technologies and frameworks used across frontend, backend, database, infrastructure, and DevOps.
- **Architecture Decisions**: Key technical decisions and their rationale.
- **Architecture Constraints**: Technical limitations and constraints (e.g., legacy systems, regulations, resource limits).
**Quality Criteria**:
- The architecture supports all functional requirements.
- Technology choices are appropriate, justified, and align with team expertise.
- The architecture is scalable, maintainable, and designed for future evolution.
- Constraints are realistic and well-documented, with potential workarounds or phased implementations considered.
### 2. System Architecture Diagram
**Objective**: Provide a visual representation of the system architecture.
**Required Elements**:
- **High-Level Architecture**: A visual (e.g., ASCII diagram or description) of system components and their relationships.
- **Component Descriptions**: Purpose, responsibilities, and technologies for each major component.
- **Data Flow**: How data moves through the system.
- **Communication Patterns**: How components interact (e.g., synchronous, asynchronous, message queues).
- **External Dependencies**: Identification of all third-party services and APIs.
### 3. Technology Stack Specification
**Objective**: Detail the specific technologies to be used.
#### 3.1 Frontend Technologies
- **Framework**: Specific framework (e.g., React, Vue, Angular), version, and rationale.
- **Language**: Programming language (e.g., JavaScript, TypeScript), version, and rationale.
- **Build Tools**: (e.g., Webpack, Vite, Parcel) and configuration approach.
- **Styling**: (e.g., CSS, Sass, Styled Components) approach and standards.
- **State Management**: (e.g., Redux, Vuex, Context API) pattern and rationale.
- **Testing**: (e.g., Jest, Cypress, Testing Library) strategy.
- **Package Manager**: (e.g., npm, yarn, pnpm) choice and rationale.
#### 3.2 Backend Technologies
- **Framework**: Specific framework (e.g., Express, Django, Spring Boot), version, and rationale.
- **Language**: Programming language (e.g., Node.js, Python, Java), version, and rationale.
- **Database Integration**: Libraries or ORMs used for database interaction.
- **API Design**: (e.g., REST, GraphQL, gRPC) approach and standards.
- **Authentication**: (e.g., JWT, OAuth, SAML) method and implementation.
- **Caching**: (e.g., Redis, Memcached, CDN) strategy and implementation.
- **Message Queue**: (e.g., RabbitMQ, Apache Kafka, AWS SQS), if required, with rationale.
#### 3.3 Infrastructure & DevOps
- **Cloud Provider**: (e.g., AWS, Google Cloud, Azure) services and rationale.
- **Containerization**: (e.g., Docker, Kubernetes) strategy and orchestration.
- **CI/CD**: (e.g., GitHub Actions, Jenkins, GitLab CI) pipeline design.
- **Monitoring**: (e.g., Prometheus, DataDog, New Relic) strategy.
- **Logging**: (e.g., ELK Stack, Splunk, CloudWatch) approach.
- **Infrastructure as Code (IaC)**: (e.g., Terraform, CloudFormation) strategy.
**Technology Selection Criteria**:
- Team expertise and learning curve.
- Community support and ecosystem.
- Performance and scalability characteristics.
- Security and compliance features.
- Long-term maintenance and support.
- Integration capabilities.
- Cost considerations.
### 4. Database Design
**Objective**: Define technical data requirements and database architecture.
#### 4.1 Data Model
- **Database Type**: (e.g., Relational, NoSQL, Graph, Time-series) choice and rationale.
- **Schema Design**: Detailed tables/collections and their relationships.
- **Data Types**: Specific data types for each field.
- **Indexing Strategy**: Performance optimization approach.
- **Data Relationships**: Foreign keys, references, and join requirements.
- **Data Validation**: Constraints and validation rules.
#### 4.2 Data Storage Strategy
- **Primary Database**: Main data storage solution.
- **Caching Layer**: Performance optimization caching.
- **File Storage**: Strategy for images, documents, and media storage.
- **Backup Strategy**: Data backup and recovery approach.
- **Data Archival**: Long-term data retention strategy.
- **Data Migration**: Strategy for existing data migration and schema changes.
**Database Considerations**:
- ACID compliance requirements.
- Scalability and sharding strategies.
- Data consistency and integrity.
- Query performance optimization.
- Data privacy and encryption.
### 5. API Design & Integration
**Objective**: Specify technical integration requirements.
#### 5.1 API Specification
- **API Style**: (e.g., REST, GraphQL, gRPC) chosen style.
- **Base URL**: API endpoint structure.
- **Authentication**: API authentication method.
- **Rate Limiting**: Request throttling strategy.
- **Versioning**: API version management approach.
- **Documentation**: API documentation approach (e.g., OpenAPI).
- **Core Endpoints**: Method, path, purpose, and request/response format for key API endpoints.
#### 5.2 Third-Party Integrations
- **Integration**: Service name and purpose.
- **API Details**: Endpoint, authentication, and rate limits for external APIs.
- **Data Exchange**: What data is sent/received.
- **Error Handling**: How integration failures are managed.
- **Fallback Strategy**: What happens if an integration fails.
- **Monitoring**: How integration health is monitored.
**API Design Principles**:
- RESTful design patterns, consistent naming conventions, proper HTTP status codes.
- Comprehensive error handling, input validation and sanitization.
- Response format standardization.
### 6. Security Architecture
**Objective**: Define security and privacy requirements.
#### 6.1 Security Framework
- **Security Model**: (e.g., Zero-trust, defense-in-depth).
- **Authentication**: User verification approach (e.g., SSO, MFA).
- **Authorization**: Access control implementation (e.g., RBAC, ABAC).
- **Data Encryption**: At-rest and in-transit encryption requirements.
- **Network Security**: Firewall, VPN, and network segmentation.
- **Application Security**: Input validation, XSS prevention, etc.
- **Security Standards**: Security standards and frameworks to follow (e.g., ISO 27001, NIST).
#### 6.2 Security Implementation
- **Identity Management**: User identity and access management.
- **Session Management**: Session handling and security.
- **Data Protection**: PII protection and privacy measures.
- **Audit Logging**: Security event logging and monitoring.
- **Vulnerability Management**: Security testing and patching.
- **Incident Response**: Security incident handling procedures.
**Security Considerations**:
- OWASP Top 10 vulnerability prevention.
- Data privacy regulations compliance (e.g., GDPR, CCPA, HIPAA).
- Secure coding practices.
- Regular security audits and penetration testing.
- Security monitoring and alerting.
### 7. Performance & Scalability
**Objective**: Specify performance expectations and constraints.
#### 7.1 Performance Requirements
- **Response Time Targets**: Maximum acceptable load time for pages, API calls, search results, and transactions.
- **Throughput Targets**: Expected transaction volumes and rates (e.g., concurrent users, requests per second, data processing capacity).
- **Resource Utilization**: Target CPU and memory usage, storage capacity, and I/O requirements.
#### 7.2 Scalability Strategy
- **Horizontal Scaling**: How to add more servers/instances.
- **Vertical Scaling**: How to increase server capacity.
- **Auto-scaling**: Automatic scaling triggers and policies.
- **Load Balancing**: Traffic distribution strategy.
- **Caching Strategy**: Performance optimization through caching at multiple layers.
- **Database Scaling**: Database performance and scaling approach (e.g., sharding, replication).
- **Geographic Scaling**: Multi-region or global scaling needs.
**Performance Optimization Techniques**:
- Content Delivery Network (CDN) usage.
- Database query optimization.
- Asynchronous processing.
- Code optimization and profiling.
- Resource compression and minification.
### 8. Development Standards & Guidelines
**Objective**: Establish development standards and workflow.
#### 8.1 Coding Standards
- **Code Style**: Formatting, naming conventions, and structure.
- **Documentation**: Code documentation requirements.
- **Testing Requirements**: Unit, integration, and end-to-end testing standards.
- **Code Review Process**: Review procedures and criteria.
- **Version Control**: Git workflow and branching strategy.
- **Quality Gates**: Code quality metrics and thresholds.
#### 8.2 Development Workflow
- **Development Environment**: Local development setup.
- **Build Process**: Compilation and build procedures.
- **Testing Pipeline**: Automated testing workflow.
- **Deployment Process**: Staging and production deployment.
- **Monitoring & Debugging**: Development monitoring tools.
- **Documentation**: Technical documentation requirements (e.g., operational runbooks).
**Development Best Practices**:
- Test-driven development (TDD).
- Continuous integration/continuous deployment (CI/CD).
- Code review and pair programming.
- Automated testing and quality assurance.
- Knowledge sharing.
### 9. Deployment & Operations
**Objective**: Specify infrastructure, hosting, and operational requirements.
#### 9.1 Deployment Architecture
- **Hosting Strategy**: Cloud, on-premise, or hybrid approach.
- **Environment Strategy**: Development, staging, and production environments.
- **Deployment Method**: (e.g., blue-green, rolling, canary deployments).
- **Infrastructure**: Server specifications and configurations.
- **Monitoring**: System and application monitoring setup.
- **Backup & Recovery**: Data backup and disaster recovery procedures.
- **Maintenance**: System maintenance and update procedures.
#### 9.2 Operational Procedures
- **Health Monitoring**: System health checks and alerting.
- **Performance Monitoring**: Performance metrics and dashboards.
- **Error Handling**: Error tracking and resolution procedures.
- **Capacity Planning**: Resource planning and scaling procedures.
- **Security Operations**: Security monitoring and incident response.
### Cross-Reference and Validation
#### Must Reference:
- Functional requirements and their technical implications.
- User experience requirements and performance expectations.
- Business objectives and scalability needs.
- Compliance and regulatory requirements.
#### Must Support:
- Implementation planning and effort estimation.
- Testing and quality assurance strategy.
- Deployment and operations planning.
- Monitoring and maintenance requirements.
#### Validation Checkpoints (Before Finalizing):
- **Architecture Feasibility**: Technical approach is achievable with available resources and team capabilities.
- **Requirements Coverage**: All product and functional requirements are technically addressed.
- **Scalability**: Architecture supports required growth and performance.
- **Security**: Comprehensive security measures are specified and meet compliance requirements.
- **Maintainability**: Code and architecture are easy to maintain and extend.
- **Reliability**: System is robust and handles failures gracefully.
- **Performance**: System meets specified performance and efficiency requirements.
- **Integration Feasibility**: All required integrations are technically feasible.
- **Cost Analysis**: Infrastructure and technology costs fit within the budget.
### Common Pitfalls to Avoid
- **Over-engineering**: Building more complexity than needed or solutions that are overly complex for simple problems.
- **Under-engineering**: Not planning for scale and growth, or choosing solutions that won't scale.
- **Technology Bias/Chasing**: Choosing technologies based on preference rather than fit, or selecting new technologies without clear benefits.
- **Vendor Lock-in**: Creating dependencies that are difficult to change.
- **Ignoring Constraints**: Not considering team capabilities, budget limits, or existing technical debt.
- **Security Afterthought**: Not considering security from the beginning of the design process.
- **Unrealistic Expectations**: Setting impossible performance targets or not validating performance assumptions.
- **Tight Coupling**: Creating dependencies that make changes difficult.
- **Inadequate Error Handling**: Not planning for failure scenarios.
### Edge Case Considerations
- **Severe Technical Constraints**: Document constraints, identify workarounds, plan technical debt reduction, and consider phased implementation.
- **Aggressive Performance Requirements**: Validate requirements with user research, plan early and frequent performance testing, consider caching and optimization strategies, and build performance monitoring from the start.
- **High Integration Complexity**: Plan thorough integration testing, build robust error handling and retry logic, consider integration patterns like circuit breakers, and plan for integration partner changes.
- **Legacy System Integration**: Assess legacy system capabilities, plan data migration and synchronization, design abstraction layers, consider gradual migration strategies, and plan for legacy system retirement.
- **Regulatory Compliance**: Research applicable technical regulations, design compliance into core architecture, plan for audit trails, consider data residency, and include compliance validation in testing.
- **Resource Constraints**: Prioritize technical features by business impact, consider phased implementation, plan for technical debt management, design for future extensibility, and consider open-source alternatives.
### Success Indicators
Successful technical requirements and specifications should:
- Provide clear technical direction for development teams.
- Enable accurate effort estimation and resource planning.
- Support scalable, maintainable, and reliable system architecture.
- Address all security and compliance requirements.
- Facilitate effective testing and quality assurance.
- Enable smooth deployment and operations.
- Ensure the technical approach aligns with business objectives and user experience goals.