Gateway Offloading: Centralizing Cross Cutting Concerns

Gateway offloading moves authentication, rate limiting, request validation, TLS termination, Web Application Firewall (WAF), caching, and observability from individual microservices to a centralized edge layer. This avoids duplicating these functions across 20, 50, or 100 services and ensures uniform policy enforcement.

Authentication offloading typically involves validating JSON Web Tokens (JWT) or OAuth tokens at the gateway and caching public keys from JSON Web Key Set (JWKS) endpoints for 5 to 15 minutes with overlap during key rotations. The gateway verifies signature, expiration, and claims (scope, audience) then forwards a normalized identity header to backends. This keeps backends stateless and eliminates the need for each service to implement token validation, key rotation logic, and secure storage of secrets. Rate limiting uses token bucket or leaky bucket algorithms with per API key or per user quotas. A common setup is 100 requests per second steady state with 300 token burst capacity, enforced at admission before expensive authentication or backend fan out.

Caching at the gateway reduces backend load and improves response time for read heavy endpoints. Typical pattern is caching GET and HEAD responses with Time To Live (TTL) values from 30 seconds for dynamic feeds to 1 hour for semi static content like product catalogs. Use normalized cache keys including method, path, query parameters, and Vary headers (Accept, Accept Encoding). Request coalescing collapses multiple concurrent identical requests into a single backend call, critical during cache expiration stampedes where 1000 clients simultaneously request the same expired hot key.

The downside is that centralized policy can become a bottleneck and single point of failure. If the gateway's authentication provider or rate limit store goes down, all traffic halts. Mitigation includes running the data plane stateless with in memory caches, failing open with degraded security during control plane outages (time bounded), and using multi region active active deployments with health aware DNS. AWS API Gateway enforces 10 megabyte payload limits at the edge forcing large uploads to use pre signed URLs to object storage instead of passing through the gateway.

💡 Key Takeaways

•JWT validation with JWKS caching for 5 to 15 minutes eliminates per service token logic and key rotation complexity; overlap keys during rotations to prevent mass auth failures

•Token bucket rate limiting with 100 requests per second steady and 300 burst capacity enforced at admission before authentication or backend calls to shed load early

•Request coalescing collapses 1000 concurrent identical requests into one backend call during cache expiration preventing stampede and overload

•Stale while revalidate pattern serves cached content up to 60 seconds past TTL during backend blips maintaining availability with bounded staleness

•Centralized policy single point of failure risk: control plane outage can halt all traffic requiring stateless data plane with fail open mechanisms

•10 megabyte payload limit typical at edge gateways forces offload of large uploads to object storage with pre signed URLs passing only metadata through gateway

📌 Examples

SaaS platform validates OAuth tokens at gateway caching JWKS for 10 minutes, forwards user ID and tenant ID headers to 40 backend services eliminating per service token logic

API enforces 1000 requests per hour per free tier user and 10000 per premium user using token bucket; returns 429 with Retry After header when exceeded

Content API caches product listings for 15 minutes with stale while revalidate; serves stale data for up to 60 seconds during backend maintenance window

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