Senior Architect

Architecture design and analysis tools for making informed technical decisions.

Table of Contents

• Quick Start
• Tools Overview
• Architecture Diagram Generator
• Dependency Analyzer
• Project Architect
• Decision Workflows
• Database Selection
• Architecture Pattern Selection
• Monolith vs Microservices
• Reference Documentation
• Tech Stack Coverage
• Common Commands

Quick Start

bash
# Generate architecture diagram from project
python scripts/architecture_diagram_generator.py ./my-project --format mermaid

# Analyze dependencies for issues
python scripts/dependency_analyzer.py ./my-project --output json

# Get architecture assessment
python scripts/project_architect.py ./my-project --verbose

Tools Overview

1. Architecture Diagram Generator

Generates architecture diagrams from project structure in multiple formats.

Solves: "I need to visualize my system architecture for documentation or team discussion"

Input: Project directory path Output: Diagram code (Mermaid, PlantUML, or ASCII)

Supported diagram types:

• component - Shows modules and their relationships
• layer - Shows architectural layers (presentation, business, data)
• deployment - Shows deployment topology

Usage:

bash
# Mermaid format (default)
python scripts/architecture_diagram_generator.py ./project --format mermaid --type component

# PlantUML format
python scripts/architecture_diagram_generator.py ./project --format plantuml --type layer

# ASCII format (terminal-friendly)
python scripts/architecture_diagram_generator.py ./project --format ascii

# Save to file
python scripts/architecture_diagram_generator.py ./project -o architecture.md

Example output (Mermaid):

mermaid
graph TD
    A[API Gateway] --> B[Auth Service]
    A --> C[User Service]
    B --> D[(PostgreSQL)]
    C --> D

2. Dependency Analyzer

Analyzes project dependencies for coupling, circular dependencies, and outdated packages.

Solves: "I need to understand my dependency tree and identify potential issues"

Input: Project directory path Output: Analysis report (JSON or human-readable)

Analyzes:

• Dependency tree (direct and transitive)
• Circular dependencies between modules
• Coupling score (0-100)
• Outdated packages

Supported package managers:

• npm/yarn (package.json)
• Python (requirements.txt, pyproject.toml)
• Go (go.mod)
• Rust (Cargo.toml)

Usage:

bash
# Human-readable report
python scripts/dependency_analyzer.py ./project

# JSON output for CI/CD integration
python scripts/dependency_analyzer.py ./project --output json

# Check only for circular dependencies
python scripts/dependency_analyzer.py ./project --check circular

# Verbose mode with recommendations
python scripts/dependency_analyzer.py ./project --verbose

Example output:

Dependency Analysis Report
==========================
Total dependencies: 47 (32 direct, 15 transitive)
Coupling score: 72/100 (moderate)

Issues found:
- CIRCULAR: auth → user → permissions → auth
- OUTDATED: lodash 4.17.15 → 4.17.21 (security)

Recommendations:
1. Extract shared interface to break circular dependency
2. Update lodash to fix CVE-2020-8203

3. Project Architect

Analyzes project structure and detects architectural patterns, code smells, and improvement opportunities.

Solves: "I want to understand the current architecture and identify areas for improvement"

Input: Project directory path Output: Architecture assessment report

Detects:

• Architectural patterns (MVC, layered, hexagonal, microservices indicators)
• Code organization issues (god classes, mixed concerns)
• Layer violations
• Missing architectural components

Usage:

bash
# Full assessment
python scripts/project_architect.py ./project

# Verbose with detailed recommendations
python scripts/project_architect.py ./project --verbose

# JSON output
python scripts/project_architect.py ./project --output json

# Check specific aspect
python scripts/project_architect.py ./project --check layers

Example output:

Architecture Assessment
=======================
Detected pattern: Layered Architecture (confidence: 85%)

Structure analysis:
  ✓ controllers/  - Presentation layer detected
  ✓ services/     - Business logic layer detected
  ✓ repositories/ - Data access layer detected
  ⚠ models/       - Mixed domain and DTOs

Issues:
- LARGE FILE: UserService.ts (1,847 lines) - consider splitting
- MIXED CONCERNS: PaymentController contains business logic

Recommendations:
1. Split UserService into focused services
2. Move business logic from controllers to services
3. Separate domain models from DTOs

Decision Workflows

Database Selection Workflow

Use when choosing a database for a new project or migrating existing data.

Step 1: Identify data characteristics | Characteristic | Points to SQL | Points to NoSQL | |----------------|---------------|-----------------| | Structured with relationships | ✓ | | | ACID transactions required | ✓ | | | Flexible/evolving schema | | ✓ | | Document-oriented data | | ✓ | | Time-series data | | ✓ (specialized) |

Step 2: Evaluate scale requirements

• <1M records, single region → PostgreSQL or MySQL
• 1M-100M records, read-heavy → PostgreSQL with read replicas
• >100M records, global distribution → CockroachDB, Spanner, or DynamoDB
• High write throughput (>10K/sec) → Cassandra or ScyllaDB

Step 3: Check consistency requirements

• Strong consistency required → SQL or CockroachDB
• Eventual consistency acceptable → DynamoDB, Cassandra, MongoDB

Step 4: Document decision Create an ADR (Architecture Decision Record) with:

• Context and requirements
• Options considered
• Decision and rationale
• Trade-offs accepted

Quick reference:

PostgreSQL → Default choice for most applications
MongoDB    → Document store, flexible schema
Redis      → Caching, sessions, real-time features
DynamoDB   → Serverless, auto-scaling, AWS-native
TimescaleDB → Time-series data with SQL interface

Architecture Pattern Selection Workflow

Use when designing a new system or refactoring existing architecture.

Step 1: Assess team and project size | Team Size | Recommended Starting Point | |-----------|---------------------------| | 1-3 developers | Modular monolith | | 4-10 developers | Modular monolith or service-oriented | | 10+ developers | Consider microservices |

Step 2: Evaluate deployment requirements

• Single deployment unit acceptable → Monolith
• Independent scaling needed → Microservices
• Mixed (some services scale differently) → Hybrid

Step 3: Consider data boundaries

• Shared database acceptable → Monolith or modular monolith
• Strict data isolation required → Microservices with separate DBs
• Event-driven communication fits → Event-sourcing/CQRS

Step 4: Match pattern to requirements

| Requirement | Recommended Pattern | |-------------|-------------------| | Rapid MVP development | Modular Monolith | | Independent team deployment | Microservices | | Complex domain logic | Domain-Driven Design | | High read/write ratio difference | CQRS | | Audit trail required | Event Sourcing | | Third-party integrations | Hexagonal/Ports & Adapters |

See references/architecture_patterns.md for detailed pattern descriptions.

Monolith vs Microservices Decision

Choose Monolith when:

• ] Team is small (<10 developers)
• ] Domain boundaries are unclear
• ] Rapid iteration is priority
• ] Operational complexity must be minimized
• ] Shared database is acceptable

Choose Microservices when:

• ] Teams can own services end-to-end
• ] Independent deployment is critical
• ] Different scaling requirements per component
• ] Technology diversity is needed
• ] Domain boundaries are well understood

Hybrid approach: Start with a modular monolith. Extract services only when:

1. A module has significantly different scaling needs
2. A team needs independent deployment
3. Technology constraints require separation

Reference Documentation

Load these files for detailed information:

| File | Contains | Load when user asks about | |------|----------|--------------------------| | references/architecture_patterns.md | 9 architecture patterns with trade-offs, code examples, and when to use | "which pattern?", "microservices vs monolith", "event-driven", "CQRS" | | references/system_design_workflows.md | 6 step-by-step workflows for system design tasks | "how to design?", "capacity planning", "API design", "migration" | | references/tech_decision_guide.md | Decision matrices for technology choices | "which database?", "which framework?", "which cloud?", "which cache?" |

Tech Stack Coverage

Languages: TypeScript, JavaScript, Python, Go, Swift, Kotlin, Rust Frontend: React, Next.js, Vue, Angular, React Native, Flutter Backend: Node.js, Express, FastAPI, Go, GraphQL, REST Databases: PostgreSQL, MySQL, MongoDB, Redis, DynamoDB, Cassandra Infrastructure: Docker, Kubernetes, Terraform, AWS, GCP, Azure CI/CD: GitHub Actions, GitLab CI, CircleCI, Jenkins

Common Commands

bash
# Architecture visualization
python scripts/architecture_diagram_generator.py . --format mermaid
python scripts/architecture_diagram_generator.py . --format plantuml
python scripts/architecture_diagram_generator.py . --format ascii

# Dependency analysis
python scripts/dependency_analyzer.py . --verbose
python scripts/dependency_analyzer.py . --check circular
python scripts/dependency_analyzer.py . --output json

# Architecture assessment
python scripts/project_architect.py . --verbose
python scripts/project_architect.py . --check layers
python scripts/project_architect.py . --output json

Getting Help

1. Run any script with --help for usage information
2. Check reference documentation for detailed patterns and workflows
3. Use --verbose flag for detailed explanations and recommendations