simplerick0/software-architecture

Software Architecture

Design scalable, maintainable software systems through sound architectural principles.

System Design Process

1. Requirements Analysis

   • Functional requirements (features)
   • Non-functional requirements (performance, scale, security)
   • Constraints (budget, timeline, team skills)

2. High-Level Design

   • Component identification
   • Data flow mapping
   • Integration points
   • Technology selection

3. Detailed Design

   • API contracts
   • Data models
   • Sequence diagrams
   • Error handling

4. Validation

   • Review against requirements
   • Identify trade-offs
   • Document decisions

Architectural Patterns

Monolith

Best for: Early-stage products, small teams
Trade-offs: Simple to develop, harder to scale independently

Microservices

Best for: Large teams, independent scaling needs
Trade-offs: Complex operations, better team autonomy

Event-Driven

Best for: Decoupled systems, async workflows
Trade-offs: Eventual consistency, good scalability

Layered (N-Tier)

Best for: Clear separation of concerns
Trade-offs: Simple structure, potential performance overhead

API Design

REST Guidelines

• Use nouns for resources: /users, /orders
• HTTP verbs for actions: GET, POST, PUT, DELETE
• Version APIs: /v1/users
• Consistent error responses

GraphQL Guidelines

• Single endpoint
• Client-specified queries
• Strong typing with schema
• Batch requests naturally

Data Modeling

Relational

• Normalize to 3NF by default
• Denormalize for read performance
• Index query patterns
• Consider partitioning for scale

NoSQL Selection

| Type | Use Case | |------|----------| | Document (MongoDB) | Flexible schema, nested data | | Key-Value (Redis) | Caching, sessions | | Column (Cassandra) | Time-series, high write throughput | | Graph (Neo4j) | Relationships, social networks |

Scalability Patterns

Horizontal Scaling

• Stateless services
• Load balancing
• Database sharding
• Caching layers

Vertical Scaling

• Increase resources
• Optimize algorithms
• Database tuning
• Limited ceiling

Common Bottlenecks

1. Database queries (add indexes, cache, read replicas)
2. Network latency (CDN, regional deployment)
3. CPU-bound operations (async processing, workers)
4. Memory (cache eviction, pagination)

Technology Selection

Decision Criteria

• Team expertise
• Community support
• Maturity and stability
• Performance characteristics
• Licensing and cost

Documentation Template

## Decision: [Title]
**Date**: [Date]
**Status**: [Proposed/Accepted/Deprecated]

### Context
[Why is this decision needed?]

### Options Considered
1. [Option A] - [Pros/Cons]
2. [Option B] - [Pros/Cons]

### Decision
[What was decided and why]

### Consequences
[What are the implications?]

Security Considerations

Authentication

• OAuth2/OIDC for third-party auth
• JWT for stateless tokens
• Session cookies for web apps

Authorization

• RBAC for role-based access
• ABAC for attribute-based rules
• Principle of least privilege

Data Protection

• Encrypt at rest and in transit
• Sanitize inputs
• Audit sensitive operations

Documentation Outputs

Architecture Decision Records (ADRs)

• One decision per record
• Include context and alternatives
• Track status over time

System Diagrams

• C4 model (Context, Container, Component, Code)
• Sequence diagrams for flows
• Data flow diagrams

API Documentation

• OpenAPI/Swagger for REST
• GraphQL schema with descriptions
• Example requests/responses