Technical Design Template

Purpose

The Technical Design Document (TDD) describes the detailed technical solution for a specific component, service, or feature. It serves as a blueprint for development, providing engineers with clear direction on implementation, technology choices, and architectural patterns.

When to Use

Complex feature implementations
New service/component development
Major refactoring or modernization
Performance-critical systems
Integration with external systems
High-risk technical decisions

Template Content

1. Executive Summary

Feature/Component: [Name]

Objective: [What problem does this solve?]

Scope: [What’s included and excluded?]

Key Decision: [Primary technical choice and rationale]

Estimated Effort: [Development time, complexity level]

Timeline: [Start date, milestones, delivery date]

2. Problem Statement

Current State:

[Current implementation or lack thereof]
[Limitations or pain points]
[Performance issues or constraints]

Why Change:

[Business driver or requirement]
[Technical debt or improvements]
[Scalability or reliability concerns]

Success Criteria:

[Measurable outcome 1]
[Measurable outcome 2]
[Measurable outcome 3]

3. Design Approach

Architecture Pattern:

[Pattern name: MVC, CQRS, Event-Driven, etc.]
[Brief explanation]
[ASCII diagram showing pattern]

Example:
        UI Layer
            ↓
    ┌───────────────┐
    │ Controller    │ ← Handles requests
    └────────┬──────┘
             ↓
    ┌────────────────┐
    │ Service Layer  │ ← Business logic
    └────────┬───────┘
             ↓
    ┌────────────────┐
    │ Data Layer     │ ← Database access
    └────────────────┘

Technology Stack:

Layer	Technology	Version	Rationale
Backend	Python 3.11	3.11+	Performance, readability
Framework	Django 4.2	4.2+	Batteries-included, ORM
Database	PostgreSQL	15+	ACID compliance, scaling
Cache	Redis	7+	Fast in-memory, pub/sub
Queue	RabbitMQ	3.12+	Reliability, dead-letter queues
Search	Elasticsearch	8+	Full-text search, analytics
Monitoring	Prometheus	2.4+	Metrics, alerting

4. Component Design

System Components:

External Request
    ↓
┌─────────────────────┐
│   API Gateway       │ (Rate limiting, auth)
└──────────┬──────────┘
           ↓
┌──────────────────────────────────────┐
│  Request Handler / Controller         │
└──────────┬───────────────────────────┘
           ↓
┌──────────────────────────────────────┐
│  Business Logic / Service Layer       │
│  ├─ Validation                        │
│  ├─ Processing                        │
│  └─ Coordination                      │
└──────────┬───────────────────────────┘
           ↓
    ┌──────┴──────┐
    ↓             ↓
[Database]   [External Service]

Component Responsibilities:

1. API Controller/Handler

Parse incoming requests
Validate input
Call appropriate service methods
Return formatted responses
Handle errors gracefully

2. Service Layer

Implement business logic
Coordinate between repositories
Handle transactions
Manage state changes
Validate business rules

3. Data Access Layer

Query/update database
Cache frequently accessed data
Implement query optimization
Handle connection pooling
Manage migrations

4. External Integration

Call external APIs
Handle retries
Timeout management
Error transformation

5. Data Model

Database Schema:

-- Core tables
CREATE TABLE users (
  id BIGSERIAL PRIMARY KEY,
  email VARCHAR(255) UNIQUE NOT NULL,
  name VARCHAR(255) NOT NULL,
  created_at TIMESTAMP DEFAULT NOW(),
  updated_at TIMESTAMP DEFAULT NOW()
);

CREATE TABLE orders (
  id BIGSERIAL PRIMARY KEY,
  user_id BIGINT REFERENCES users(id),
  total_amount DECIMAL(10,2) NOT NULL,
  status VARCHAR(20) NOT NULL,
  created_at TIMESTAMP DEFAULT NOW(),
  updated_at TIMESTAMP DEFAULT NOW()
);

CREATE TABLE order_items (
  id BIGSERIAL PRIMARY KEY,
  order_id BIGINT REFERENCES orders(id),
  product_id BIGINT NOT NULL,
  quantity INT NOT NULL,
  unit_price DECIMAL(10,2) NOT NULL,
  created_at TIMESTAMP DEFAULT NOW()
);

-- Indexes
CREATE INDEX idx_orders_user_id ON orders(user_id);
CREATE INDEX idx_orders_status ON orders(status);
CREATE INDEX idx_orders_created_at ON orders(created_at DESC);
CREATE INDEX idx_order_items_order_id ON order_items(order_id);

Entity Relationships:

User
  ├─ 1:N relationship with Orders
  │   └─ Order
  │       ├─ 1:N relationship with OrderItems
  │       │   └─ OrderItem
  │       │       └─ Product reference
  │       └─ Payment reference
  └─ Profile

6. API Specification

REST Endpoints:

POST /api/v1/orders
  Request:
    {
      "user_id": 123,
      "items": [
        {"product_id": 456, "quantity": 2}
      ]
    }
  Response:
    {
      "id": 789,
      "user_id": 123,
      "total": 99.99,
      "status": "created",
      "created_at": "2025-01-15T10:30:00Z"
    }
  Status: 201 Created
  Errors:
    - 400: Invalid input
    - 401: Unauthorized
    - 409: Conflict (inventory)

GET /api/v1/orders/{order_id}
  Response: Order details
  Status: 200 OK
  Errors:
    - 401: Unauthorized
    - 404: Not found

PUT /api/v1/orders/{order_id}
  Request: Updated order fields
  Response: Updated order
  Status: 200 OK

DELETE /api/v1/orders/{order_id}
  Status: 204 No Content
  Errors:
    - 401: Unauthorized
    - 404: Not found
    - 409: Cannot delete (not allowed state)

7. Code Structure

Directory Layout:

src/
├── api/
│   ├── controllers/
│   │   ├── orders_controller.py
│   │   └── users_controller.py
│   ├── schemas/
│   │   ├── order_schema.py
│   │   └── user_schema.py
│   └── middleware/
│       ├── auth.py
│       └── error_handler.py
├── services/
│   ├── order_service.py
│   ├── user_service.py
│   └── payment_service.py
├── repositories/
│   ├── order_repository.py
│   ├── user_repository.py
│   └── base_repository.py
├── models/
│   ├── order.py
│   ├── user.py
│   └── enums.py
├── utils/
│   ├── validators.py
│   ├── formatters.py
│   └── helpers.py
├── config/
│   ├── settings.py
│   └── database.py
├── migrations/
│   └── versions/
└── tests/
    ├── unit/
    ├── integration/
    └── fixtures/

8. Implementation Details

Key Functions:

def create_order(user_id: int, items: List[OrderItem]) -> Order:
    """
    Create a new order with items.
    
    Args:
        user_id: ID of user placing order
        items: List of order items with product_id and quantity
    
    Returns:
        Created Order object
    
    Raises:
        ValidationError: Invalid input
        NotFoundError: User not found
        InsufficientInventoryError: Not enough stock
    
    Steps:
    1. Validate user exists
    2. Validate items and inventory availability
    3. Calculate total amount
    4. Create order in database (transaction)
    5. Update inventory (decrement)
    6. Publish OrderCreated event
    7. Return order details
    """
    pass

def process_payment(order_id: int, payment_method: str) -> Payment:
    """
    Process payment for an order.
    
    Retries: 3 attempts with exponential backoff
    Timeout: 30 seconds
    """
    pass

9. Error Handling

Error Categories:

Type	Example	Status	Action
Validation	Invalid email format	400	Return error details to client
Authentication	Missing API key	401	Reject request
Authorization	User can’t access resource	403	Reject request
Not Found	Order doesn’t exist	404	Return 404
Conflict	Inventory conflict	409	Return error with reason
Server Error	Database connection failed	500	Log and retry

Error Response Format:

{
  "error": {
    "code": "INSUFFICIENT_INVENTORY",
    "message": "Product 456 has only 2 units available",
    "details": {
      "product_id": 456,
      "requested": 5,
      "available": 2
    }
  },
  "request_id": "req-abc123"
}

10. Performance Considerations

Optimization Strategies:

Database:

Index on frequently queried columns
Connection pooling (10-20 connections)
Query optimization (EXPLAIN ANALYZE)
Caching expensive queries (5-10 min TTL)

Caching:

Order list cache: 2 minute TTL
User profile cache: 5 minute TTL
Product details cache: 1 hour TTL

Invalidation:
- Event-based when data changes
- Time-based automatic expiration

Expected Performance:

Create order: < 200ms
Get order: < 50ms (with cache)
List orders: < 100ms (paginated)
Process payment: < 1 second

11. Testing Strategy

Unit Tests:

def test_create_order_success():
    """Test successful order creation"""
    user = create_test_user()
    items = [create_test_item(product_id=1, qty=2)]
    
    order = create_order(user.id, items)
    
    assert order.id is not None
    assert order.total == 99.99
    assert order.status == 'created'

def test_create_order_invalid_user():
    """Test order creation with invalid user"""
    with pytest.raises(NotFoundError):
        create_order(user_id=99999, items=[])

Integration Tests:

def test_create_order_updates_inventory():
    """Test that creating order updates inventory"""
    product = create_test_product(stock=10)
    
    create_order(user_id=1, items=[OrderItem(product.id, 3)])
    
    product.refresh()
    assert product.stock == 7

Load Tests:

Concurrent order creation: 100 requests/second
Large result set retrieval: 10K+ items
Peak traffic: Black Friday scenario

12. Deployment & Operations

Deployment Steps:

Code review and approval
Run test suite (unit + integration)
Build Docker image
Push to registry
Update deployment manifest
Rolling update (blue-green)
Smoke tests
Monitor metrics for 30 minutes

Rollback Plan:

Automatic if health checks fail
Manual rollback available
Database rollback script (for schema changes)

Monitoring:

Response time P95/P99
Error rate by endpoint
Database connection pool usage
Cache hit ratio
Business metrics (orders per minute)

13. Security Considerations

Authentication:

JWT tokens with 1-hour expiration
Refresh tokens for renewal
API keys for service-to-service

Authorization:

Users can only access their own orders
Admins have elevated access
Verify user ID matches request context

Data Protection:

HTTPS only
Encrypt sensitive data in database
Sanitize user input
Log access to sensitive data

Compliance:

GDPR: User data deletion capability
PCI: Payment data handling
Audit logs for all modifications

14. Dependencies & Risks

Technical Risks:

Risk	Probability	Impact	Mitigation
Database bottleneck	Medium	High	Read replicas, caching
Memory leak	Low	High	Profiling, monitoring
Race condition	Low	Medium	Locking, transactions

15. Future Enhancements

Real-time order notifications (WebSockets)
GraphQL API addition
Recommendation engine integration
Machine learning for fraud detection
Multi-currency support

Status: Complete
Last Updated: November 2025
Contributors: Architecture Practice Team

Solution Architecture Practice

Comprehensive guide to software architecture frameworks, patterns, and best practices

Technical Design Template

Purpose

When to Use

Template Content

1. Executive Summary

2. Problem Statement

3. Design Approach

4. Component Design

5. Data Model

6. API Specification

7. Code Structure

8. Implementation Details

9. Error Handling

10. Performance Considerations

11. Testing Strategy

12. Deployment & Operations

13. Security Considerations

14. Dependencies & Risks

15. Future Enhancements

Technical Design Template

Purpose

When to Use

Template Content

1. Executive Summary

2. Problem Statement

3. Design Approach

4. Component Design

5. Data Model

6. API Specification

7. Code Structure

8. Implementation Details

9. Error Handling

10. Performance Considerations

11. Testing Strategy

12. Deployment & Operations

13. Security Considerations

14. Dependencies & Risks

15. Future Enhancements

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