Architecture & Patterns
This section explores software architecture patterns and design principles that are essential for building scalable, maintainable, and robust systems. Learn about modern architectural approaches and their practical implementations.
π Architecture Categories
ποΈ Application Architecture
Core application design patterns and principles for building scalable software systems.
Microservices Architecture - Service decomposition and design
Domain-Driven Design - Business-aligned software architecture
MVC Without View Pattern - Backend-focused architectural approach
Fundamental design patterns for object creation, structure, and behavior.
Creational Patterns - Object creation mechanisms (Singleton, Factory, Builder, etc.)
Coming Soon: Structural and Behavioral patterns
π Data Architecture
Data pipeline patterns and storage strategies for modern data systems.
ETL vs ELT Pipelines - Data processing approaches
Medallion Architecture - Bronze-Silver-Gold data lakehouse pattern
π Integration Patterns
Communication and integration strategies for distributed systems.
Event-Driven Architecture - Asynchronous system communication
π‘οΈ Security Architecture
Security patterns and design principles for building secure systems.
Web Application Firewalls - Layer 7 application protection
π§ͺ Testing Patterns
Testing architecture patterns for building robust, reliable software systems.
Testing Pyramid for Microservices - Comprehensive testing strategy for distributed systems
Chaos Engineering - Netflix Chaos Monkey principles and AWS Fault Injection Simulator
βοΈ Cloud-Native Patterns
Cloud-native architecture patterns for leveraging cloud computing capabilities.
Coming Soon: Serverless, Container, and DevOps patterns
Performance optimization patterns for building high-performance systems.
Coming Soon: Caching, Load Balancing, and Database optimization patterns
What You'll Learn
Scalable System Design - Patterns for handling growth and complexity
Distributed System Patterns - Communication and coordination strategies
Data Engineering Architectures - Modern data processing and storage patterns
Security-First Design - Building security into system architecture
Cloud-Native Patterns - Leveraging cloud services effectively
Integration Strategies - Connecting systems and services reliably
Key Principles
Separation of Concerns - Clear boundaries between different responsibilities
Scalability - Design systems that can grow with demand
Resilience - Build fault-tolerant and self-healing systems
Security - Implement defense-in-depth strategies
Maintainability - Create systems that are easy to understand and modify
Performance - Optimize for speed and efficiency
Last updated