Backend Architectures Cheat Sheet

Updated 2026-04-29

Backend architecture defines how server-side systems are structured, organized, and scaled to handle business logic, data processing, and service orchestration. From traditional monoliths to distributed microservices and cell-based architectures, each architectural pattern represents trade-offs between simplicity, scalability, team independence, and operational complexity. Choosing the right architecture depends on team size, deployment frequency, performance requirements, and how much complexity your organization can effectively manage — there's no universal "best" architecture, only the one that fits your current constraints and enables your team to deliver value efficiently.

What This Cheat Sheet Covers

This topic spans 11 focused tables and 91 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.

Table 1: Primary Architecture StylesTable 2: Domain-Driven Design (DDD) PatternsTable 3: Distributed System PatternsTable 4: Communication PatternsTable 5: Resilience & Reliability PatternsTable 6: Data Management PatternsTable 7: Caching StrategiesTable 8: Scalability PatternsTable 9: Deployment PatternsTable 10: Message Broker PatternsTable 11: Security & Authentication Patterns

Table 1: Primary Architecture Styles

Style	Example	Description
Monolithic Architecture	`application.war` `└── all components in single deployable`	• Single unified codebase deployed as one unit • simplest to develop and deploy initially but becomes difficult to scale and modify as the application grows.
Microservices Architecture	`user-service`, `order-service`, `payment-service` `(each independently deployed)`	• Application split into independently deployable services organized around business capabilities • enables team autonomy and technology diversity but adds operational complexity.
Modular Monolith	`app.jar` `├── users/` `├── orders/` `└── payments/`	• Monolith with strong internal boundaries between modules • provides organizational benefits of microservices without distributed system complexity — recommended starting point for most projects.
Serverless Architecture	`AWS Lambda`, `Azure Functions` `triggered by events`	• Event-driven functions managed by cloud provider • eliminates server management and scales automatically but introduces cold starts and vendor lock-in.
Event-Driven Architecture (EDA)	`Kafka/RabbitMQ` `services react to events`	• Services communicate through asynchronous event streams rather than direct calls • enables loose coupling and real-time processing but requires careful event schema management.

Table 1: Primary Architecture Styles

Style	Example	Description
Monolithic Architecture	`application.war` `└── all components in single deployable`	• Single unified codebase deployed as one unit • simplest to develop and deploy initially but becomes difficult to scale and modify as the application grows.
Microservices Architecture	`user-service`, `order-service`, `payment-service` `(each independently deployed)`	• Application split into independently deployable services organized around business capabilities • enables team autonomy and technology diversity but adds operational complexity.
Modular Monolith	`app.jar` `├── users/` `├── orders/` `└── payments/`	• Monolith with strong internal boundaries between modules • provides organizational benefits of microservices without distributed system complexity — recommended starting point for most projects.
Serverless Architecture	`AWS Lambda`, `Azure Functions` `triggered by events`	• Event-driven functions managed by cloud provider • eliminates server management and scales automatically but introduces cold starts and vendor lock-in.
Event-Driven Architecture (EDA)	`Kafka/RabbitMQ` `services react to events`	• Services communicate through asynchronous event streams rather than direct calls • enables loose coupling and real-time processing but requires careful event schema management.