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

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Quick Start

# 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

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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:

# 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):

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

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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Analyzes project dependencies for coupling, circular dependencies, and outdated packages.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• Outdated packages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:

# 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

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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:

# 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

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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

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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.

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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

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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?"

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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

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Common Commands

# 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

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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