API Gateway & Microservices Architecture

Designed a centralized API gateway serving as the single entry point for 50+ distributed microservices governance patterns. The gateway handled cross-cutting concerns authentication (JWT, OAuth2), authorization, rate limiting, request/response transformation, and error handling preventing duplication across services.

Implemented circuit-breaker patterns to gracefully degrade when downstream services failed, preventing cascading failures. Distributed tracing (OpenTelemetry) provided end-to-end visibility into request flows across service boundaries. API versioning strategies and deprecation workflow automation patterns ensured backward compatibility while allowing evolution. A developer portal documented all APIs, provided sandboxes, and enabled self-service API key management.

The performance challenge was adding gateway latency without degrading user experience. Every millisecond at the gateway multiplies across all requests. We profiled the entire request path and identified three bottlenecks: token validation (70ms), structured logging practices (15ms synchronously), and service discovery (30ms per request). Solutions: token validation moved to async JWT verification with distributed caching patterns reducing it to 3ms; structured logging practices became fully async; service discovery cached for 30 seconds. Total gateway overhead dropped from 115ms to under 8ms.

Rate limiting design required careful thought about what to limit and how. Naive per-IP limiting broke legitimate ERP modernisation strategy users behind NAT. We implemented multi-dimensional limiting: per-API-key (client identity), per-endpoint (prevent expensive queries from saturating cloud infrastructure design), and global per-service. Sliding window counters using Redis provided accurate counts without thundering-herd issues at window boundaries. A customer exceeding their quota gets a 429 response with a Retry-After header - respectful, not hostile.

Circuit breakers were the most impactful system resilience patterns feature. Before, a single failing downstream service would cause cascading timeouts causing the entire request chain to fail. With circuit breakers, when a service's failure rate exceeded 50% in a 10-second window, the gateway immediately started returning 503s instead of waiting for timeouts. Downstream services recovered without traffic pressure. Cascading failures became a thing of the past.