Consistent error handling transforms debugging from guesswork into systematic troubleshooting. I use a rescue handler that catches exceptions globally and transforms them into a standard JSON structure containing an error code, human-readable message,

Rate limiting is essential protection against abuse and ensures fair resource distribution across API consumers. Rack::Attack with Redis backing provides a robust, shared state solution that works across multiple application servers. I define differen

Stateless authentication with JWT tokens simplifies horizontal scaling but introduces security concerns around token lifetime and revocation. I use short-lived access tokens (15 minutes) combined with longer-lived refresh tokens stored in an encrypted

API versioning is critical for maintaining backward compatibility while evolving your endpoints. I use Rails namespace routing to organize versions cleanly within the app/controllers structure. Each version lives in its own module like Api::V1 or Api:

Even well-tested services panic occasionally: a nil pointer from an unexpected edge case, a slice bounds bug, or a library doing something surprising. If you don’t recover, one request can crash the entire process and turn a small bug into an outage.

For workloads that run at SERIALIZABLE isolation (or that hit serialization conflicts under load), retries are part of the contract. The important part is to retry only the safe errors (typically SQLSTATE 40001) and to keep the loop bounded so you don

Cleanup paths are easy to under-test, and it’s common to ignore close errors because you only have one return value. With Go 1.20+, errors.Join gives you a clean way to accumulate multiple cleanup errors and return them as a single error value. This i

When you need accurate request logs or metrics, you can’t rely on “what you intended to write” — you need what actually got written. Wrapping http.ResponseWriter to capture WriteHeader and count bytes is a simple way to record status codes and respons

I like explicit response helpers because they prevent subtle inconsistencies: missing Content-Type, forgetting Cache-Control, or writing headers after the body has started. A WriteJSON function centralizes the “happy path” and makes error handling con

Most handler bugs I debug are really input bugs: oversized bodies, unexpected fields, or clients sending arrays when the API expects an object. A dedicated decode helper makes behavior consistent. This pattern wraps the request body with http.MaxBytes

In-flight request count is a simple but powerful saturation signal. I keep an atomic.Int64 gauge that increments at the start of a request and decrements in a defer, which makes it robust even on early returns. This gauge can be exported via expvar, P

Clients can lie about Content-Type, so for uploads I prefer sniffing the first bytes with http.DetectContentType. The safe flow is: open the multipart file, read a small prefix, detect type, then rewind (or re-open) before writing to disk or object st