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Distributed System Architectural Patterns

A comprehensive reference guide for distributed system API architectural patterns, organized into 6 main categories with detailed documentation, diagrams, and decision frameworks.

Quick Navigation

Category Patterns Focus Area
API Communication Styles REST, GraphQL, gRPC, WebSockets How services communicate
API Gateway Patterns API Gateway, BFF, Aggregator Entry points and routing
Resilience Patterns Circuit Breaker, Retry, Bulkhead, Rate Limiting, Timeout Fault tolerance
Data Patterns CQRS, Event Sourcing, Saga, 2PC, Outbox Data management and consistency
Messaging Patterns Pub/Sub, Message Queue, Event-Driven Asynchronous communication
Service Discovery & Mesh Service Registry, Sidecar, Service Mesh Service orchestration
Deployment & Infrastructure Blue-Green, Canary, Feature Flags, Strangler Fig Deployment strategies

Pattern Decision Flowchart

Use this flowchart to help select the right pattern for your use case:

flowchart TD
    Start[What problem are you solving?] --> Q1{Need to expose APIs?}

    Q1 -->|Yes| Q2{What type of clients?}
    Q1 -->|No| Q3{Need fault tolerance?}

    Q2 -->|Public/Web| REST[REST API]
    Q2 -->|Mobile/Complex queries| GraphQL[GraphQL]
    Q2 -->|Internal microservices| gRPC[gRPC]
    Q2 -->|Real-time bidirectional| WS[WebSockets]

    Q3 -->|Yes| Q4{What kind of failure?}
    Q3 -->|No| Q5{Need async communication?}

    Q4 -->|Cascading failures| CB[Circuit Breaker]
    Q4 -->|Transient errors| Retry[Retry with Backoff]
    Q4 -->|Resource exhaustion| Bulkhead[Bulkhead]
    Q4 -->|Traffic spikes| RL[Rate Limiting]

    Q5 -->|Yes| Q6{Message pattern?}
    Q5 -->|No| Q7{Need distributed transactions?}

    Q6 -->|Fan-out to many| PubSub[Pub/Sub]
    Q6 -->|Work distribution| MQ[Message Queue]
    Q6 -->|Reactive system| EDA[Event-Driven]

    Q7 -->|Yes, eventual consistency OK| Saga[Saga Pattern]
    Q7 -->|Yes, need strong consistency| TwoPC[Two-Phase Commit]
    Q7 -->|No, read/write scaling| CQRS[CQRS]
    Q7 -->|No, full audit trail| ES[Event Sourcing]
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Pattern Categories Overview

1. API Communication Styles

Choose how your services will communicate with each other and with clients.

Pattern Best For Key Trade-off
REST CRUD operations, public APIs Simplicity vs over/under-fetching
GraphQL Complex data requirements, mobile apps Flexibility vs caching complexity
gRPC Internal microservices, high performance Speed vs browser support
WebSockets Real-time bidirectional communication Low latency vs connection overhead

2. API Gateway Patterns

Manage how clients access your microservices ecosystem.

Pattern Best For Key Trade-off
API Gateway Centralized entry point, cross-cutting concerns Single entry vs single point of failure
Backend for Frontend (BFF) Multi-platform clients (web, mobile, IoT) Optimized UX vs code duplication
Aggregator Composite responses from multiple services Reduced round trips vs complexity

3. Resilience Patterns

Build systems that gracefully handle failures.

Pattern Best For Key Trade-off
Circuit Breaker Preventing cascading failures Fail-fast vs implementation complexity
Retry with Backoff Handling transient failures Improved reliability vs thundering herd
Bulkhead Isolating resource pools Fault isolation vs resource underutilization
Rate Limiting Protecting against traffic spikes System protection vs user experience
Timeout Preventing hung connections Responsiveness vs false positives

4. Data Patterns

Handle data consistency and state management in distributed systems.

Pattern Best For Key Trade-off
CQRS Separate read/write scaling Performance optimization vs complexity
Event Sourcing Audit trails, temporal queries, replay Complete history vs storage/complexity
Saga Long-running distributed transactions Eventual consistency vs coordination overhead
Outbox Reliable event publishing Guaranteed delivery vs at-least-once semantics
Two-Phase Commit Strong consistency requirements ACID guarantees vs availability

5. Messaging Patterns

Enable asynchronous and decoupled communication.

Pattern Best For Key Trade-off
Pub/Sub Fan-out notifications, event broadcasting Decoupling vs message ordering
Message Queue Work distribution, load leveling Reliability vs latency
Event-Driven Architecture Reactive systems, loose coupling Flexibility vs debugging complexity

6. Service Discovery & Mesh

Manage service-to-service communication at scale.

Pattern Best For Key Trade-off
Service Registry Dynamic service discovery Flexibility vs additional infrastructure
Sidecar Cross-cutting concerns (logging, auth) Separation of concerns vs resource overhead
Service Mesh Complex microservices observability Full observability vs operational complexity

7. Deployment & Infrastructure

Deploy, migrate, and manage distributed systems in production.

Pattern Best For Key Trade-off
Blue-Green Deployment Zero-downtime releases, instant rollback Safety vs 2x infrastructure cost
Canary Deployment Gradual rollouts, risk mitigation Lower risk vs complexity
Rolling Deployment Resource-efficient updates Simple vs slower rollback
Feature Flags Runtime feature control, A/B testing Flexibility vs tech debt
Strangler Fig Legacy system migration Incremental vs longer timeline
Database Per Service Microservices data isolation Autonomy vs distributed complexity

How to Use This Guide

Each pattern document follows a consistent structure:

  1. Overview - What the pattern is and the problem it solves
  2. Why Use It - Motivation and benefits
  3. When to Use - Ideal scenarios and use cases
  4. When NOT to Use - Anti-patterns and bad fits
  5. How It Works - Architecture diagram (Mermaid)
  6. Pros and Cons - Detailed trade-off analysis
  7. Implementation Example - Code snippets
  8. Real-World Examples - Companies/systems using this pattern
  9. Related Patterns - Links to complementary or alternative patterns

Pattern Relationships

graph LR
    subgraph Communication[Communication Layer]
        REST
        GraphQL
        gRPC
        WebSockets
    end

    subgraph Gateway[Gateway Layer]
        APIGateway[API Gateway]
        BFF
        Aggregator
    end

    subgraph Resilience[Resilience Layer]
        CircuitBreaker[Circuit Breaker]
        Retry
        Bulkhead
        RateLimiting[Rate Limiting]
    end

    subgraph Data[Data Layer]
        CQRS
        EventSourcing[Event Sourcing]
        Saga
    end

    subgraph Messaging[Messaging Layer]
        PubSub[Pub/Sub]
        MessageQueue[Message Queue]
        EDA[Event-Driven]
    end

    Communication --> Gateway
    Gateway --> Resilience
    Resilience --> Data
    Data --> Messaging

    EventSourcing -.-> CQRS
    Saga -.-> EDA
    PubSub -.-> EDA
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Quick Reference: When to Use What

Scenario Recommended Pattern(s)
Building a public API REST + API Gateway + Rate Limiting
Mobile app with complex data needs GraphQL + BFF
High-performance internal services gRPC + Service Mesh
Real-time features (chat, notifications) WebSockets + Pub/Sub
E-commerce checkout Saga + Event-Driven
Financial audit requirements Event Sourcing + CQRS
Microservices resilience Circuit Breaker + Retry + Bulkhead
Multi-tenant SaaS Rate Limiting + Bulkhead
Zero-downtime deployments Blue-Green + Canary
Legacy modernization Strangler Fig + Feature Flags
Microservices data Database Per Service + Outbox

Contributing

When adding new patterns, ensure they follow the standard document structure and include:

  • Mermaid diagrams for visual explanation
  • Practical code examples
  • Real-world use cases
  • Clear pros/cons analysis

License

This documentation is part of the system-design repository.