APIs & Microservices
Master RESTful API design, GraphQL, microservices architecture, and distributed system patterns
Overview
APIs (Application Programming Interfaces) enable different software systems to communicate and exchange data. RESTful APIs have become the standard for web services, while GraphQL offers flexible querying capabilities. Microservices architecture breaks applications into independently deployable services.
This section covers API design principles, REST and GraphQL implementation, microservices patterns, service mesh architectures, API gateways, distributed system challenges, and best practices. For backend development, see our Backend Developer Path.
Microservices enable teams to work independently, scale components separately, and use different technologies. However, they introduce complexity in service communication, data consistency, and deployment. Understanding these trade-offs is crucial for successful microservices implementations.
RESTful APIs
Design intuitive, scalable REST APIs following best practices and industry standards.
Learn More →GraphQL
Flexible query language and runtime for APIs, enabling clients to request exactly the data they need.
Learn More →Microservices
Architectural pattern for building applications as a collection of loosely coupled services.
Learn More →API Gateway
Single entry point for managing API requests, routing, authentication, and rate limiting.
Learn More →Service Mesh
Infrastructure layer for managing service-to-service communication, security, and observability.
Learn More →Event-Driven
Architecture pattern using events to trigger and communicate between services asynchronously.
Learn More →API Design Principles
RESTful Design
REST (Representational State Transfer) uses HTTP methods (GET, POST, PUT, DELETE) to perform operations on resources identified by URLs. Follow REST conventions: use nouns for resources, proper HTTP status codes, version your APIs, and implement pagination for collections.
Design intuitive URLs that reflect resource hierarchy. Use query parameters for filtering and sorting. Implement proper error handling with meaningful messages. For comprehensive REST API guidance, see our RESTful API Design guide.
API Versioning
Version APIs to manage changes without breaking existing clients. Common approaches include URL versioning (/api/v1/), header versioning, or query parameter versioning. Maintain backward compatibility when possible and deprecate old versions gracefully.
Document versioning strategy clearly and provide migration guides. Use semantic versioning principles. Consider supporting multiple versions simultaneously during transition periods.
Authentication and Authorization
Secure APIs using OAuth 2.0, JWT tokens, or API keys. Implement proper authentication for all endpoints. Use role-based access control (RBAC) for authorization. Never expose sensitive data in URLs or error messages.
Use HTTPS for all API communications. Implement rate limiting to prevent abuse. For security best practices, see our Security & Networking documentation.
Documentation
Comprehensive API documentation is essential. Use OpenAPI/Swagger specifications for REST APIs and GraphQL schema documentation. Include examples, error responses, and authentication requirements. Keep documentation updated with code changes.
Provide interactive documentation when possible. Include code samples in multiple languages. Document rate limits, pagination, and filtering options clearly.
Microservices Patterns
Service Decomposition
Decompose applications into services based on business capabilities or domain boundaries. Each service should have a single responsibility and own its data. Use Domain-Driven Design (DDD) principles to identify bounded contexts.
Avoid creating too many small services (nanoservices) or too few large services. Balance between team autonomy and operational complexity. For database patterns, see our Databases guide on database-per-service.
Inter-Service Communication
Services communicate via synchronous (REST, gRPC) or asynchronous (message queues, event streaming) patterns. Use synchronous communication for request-response patterns and asynchronous for event-driven architectures.
Implement circuit breakers to handle service failures gracefully. Use service discovery for dynamic service location. Consider using a service mesh like Istio for advanced traffic management. For container orchestration, see our Kubernetes guide.
Data Management
Each microservice should own its database (database-per-service pattern). This ensures loose coupling and allows services to use appropriate database technologies. Implement eventual consistency patterns like Saga for distributed transactions.
Use event sourcing and CQRS (Command Query Responsibility Segregation) for complex domains. Implement data replication strategies for read scaling. For database design, see our Database Design guide.
Deployment and Scaling
Deploy services independently using containers and orchestration platforms. Scale services individually based on load. Use blue-green or canary deployments for zero-downtime updates.
Implement health checks and readiness probes. Use container orchestration platforms like Kubernetes for automated scaling and deployment. For DevOps practices, see our DevOps & Infrastructure documentation.