Integration Patterns

REST API design uses resource-oriented endpoints with pagination parameters (limit/offset or page/size) and filter query strings to manage large datasets. Implement standardized request validation, authentication checks, and consistent error responses across all endpoints to ensure reliability and usability at scale.

Retry strategies balance exponential backoff, jitter, and maximum retry counts to handle transient failures without overwhelming downstream services. Combine with circuit breakers and timeouts to prevent cascading outages when integrating multiple microservices or external APIs.

REST provides straightforward resource-oriented design and caching; GraphQL enables efficient, client-specified data fetching with a single endpoint. Choose REST for simple, cacheable resources; GraphQL when clients need flexible, nested data retrieval from complex service landscapes.

Event-driven architecture decouples services by publishing events that other systems consume asynchronously. Webhooks are HTTP callbacks that notify external systems of events in real-time, replacing polling and enabling responsive, loosely coupled integrations between services and databases.

Database integration patterns include connection pooling to reuse connections, read replicas for scaling queries, and standardized dataflow patterns that minimize latency. Apply rate limiting and timeout policies to prevent connection exhaustion in distributed architectures.

API gateways enforce standardized error responses, request validation, and rate limiting per client or endpoint to protect backend services. Combine with authentication, controller routing, and retry logic to orchestrate multiple microservices reliably and transparently.