Microservices # Design Pattern

 Microservices design patterns are reusable solutions that address common challenges in distributed systems such as scalability, resilience, data consistency, and communication. Below is a comprehensive list of the most widely used patterns in microservices architecture.

 

📋 Core Microservices Design Patterns

1. Decomposition Patterns

• Decompose by Business Capability – Split services based on business functions.
• Decompose by Subdomain (DDD) – Use Domain-Driven Design to align services with bounded contexts.
• Strangler Fig Pattern – Gradually replace a monolith by routing requests to new microservices.

2. Integration Patterns

• API Gateway – A single entry point for clients, handling routing, composition, and cross-cutting concerns.
• Aggregator Pattern – Collect data from multiple services and return a unified response.
• Proxy Pattern – Forward requests to appropriate services without exposing internal details.
• Chained/Mesh Pattern – Services call other services in sequence to fulfill a request.

3. Database and Data Management Patterns

• Database per Service – Each microservice owns its database to ensure loose coupling.
• Shared Database (rarely recommended) – Multiple services share a single database.
• Saga Pattern – Manage distributed transactions using a sequence of local transactions with compensating actions.
• CQRS (Command Query Responsibility Segregation) – Separate read and write models for scalability and clarity.
• Event Sourcing – Persist state as a sequence of events rather than current state snapshots.

4. Observability and Reliability Patterns

• Circuit Breaker – Prevent cascading failures by stopping calls to unhealthy services.
• Bulkhead – Isolate resources so failures in one service don’t affect others.
• Retry Pattern – Automatically retry failed requests with backoff strategies.
• Timeout Pattern – Define maximum wait times to avoid hanging requests.
• Health Check Pattern – Monitor service health for orchestration and load balancing.

5. Security and Cross-Cutting Patterns

• Access Token / OAuth2 – Secure communication between services and clients.
• Centralized Configuration – Store and manage configuration in a central service.
• Service Discovery – Dynamically locate services using registries like Eureka or Consul.

6. Deployment and Evolution Patterns

• Sidecar Pattern – Deploy helper components (logging, monitoring, proxy) alongside services.
• Ambassador Pattern – Offload common tasks (e.g., routing, monitoring) to a proxy container.
• Adapter Pattern – Bridge legacy systems with new microservices.
• Serverless Integration – Use FaaS for lightweight, event-driven microservices.

 

🧩 Summary Table

Category	Patterns
Decomposition	Business Capability, Subdomain (DDD), Strangler Fig
Integration	API Gateway, Aggregator, Proxy, Chained/Mesh
Data Management	Database per Service, Saga, CQRS, Event Sourcing
Reliability & Observability	Circuit Breaker, Bulkhead, Retry, Timeout, Health Check
Security & Cross-Cutting	OAuth2/Access Token, Centralized Config, Service Discovery
Deployment & Evolution	Sidecar, Ambassador, Adapter, Serverless Integration