How do you implement automated API integration workflows between enterprise systems?

Enterprise API integration automation connects disparate systems into cohesive business workflows. Architecture: integration platform (MuleSoft, Workato, or custom) serves as the middleware layer, implementing canonical data models that standardize data formats across systems, adapter patterns that encapsulate system-specific logic, and orchestration logic that coordinates multi-system transactions. Integration patterns: request-reply (synchronous API calls for real-time data), publish-subscribe (event-driven for decoupled systems), batch file transfer (scheduled bulk data movement), and shared database (last resort, high coupling). API management: implement API gateway for external integrations (rate limiting, authentication, throttling), maintain API versioning for backward compatibility, and use OpenAPI specifications for documentation. Data transformation: build reusable mapping templates between canonical model and system-specific formats, implement validation rules at integration boundaries, and handle data type conversions (date formats, currency, units). Error handling: implement retry policies per integration endpoint, circuit breakers for unreliable systems, dead letter queues for failed messages, and compensating transactions for multi-system rollback. Monitoring: track API response times, error rates, and throughput per integration, implement SLA monitoring with alerting, and maintain integration health dashboards. Security: OAuth 2.0 for API authentication, TLS for transport security, payload encryption for sensitive data, and API key rotation automation. Testing: contract testing (Pact) to verify API compatibility, integration testing with service virtualization (WireMock, Mountebank), and synthetic monitoring for production health validation.