Architectural patterns and coding practices for building high-performance, maintainable REST and GraphQL APIs.
An API that works well for ten users can fall over at ten thousand if it wasn't designed with scale in mind. The good news is that most scalability problems are architectural, not exotic and are avoidable with a handful of established patterns.
Design the contract before the code
Whether REST or GraphQL, define resources, versioning strategy, and error formats up front. Changing an API contract after clients depend on it is far more expensive than getting it right early.
Cache aggressively, invalidate carefully
Response caching, CDN edge caching, and database query caching each remove load from your busiest layer. Pair caching with clear invalidation rules to avoid serving stale data.
Paginate and rate-limit from day one
Unbounded list endpoints and unlimited request rates are two of the most common causes of production incidents as usage grows. Both are far easier to design in from the start than to retrofit under pressure.
Design for failure
- Use timeouts and circuit breakers for calls to downstream services
- Make write operations idempotent where possible
- Return clear, structured error responses that clients can act on
- Log and monitor with enough context to debug without reproducing the issue