Status code alone misses the failures that matter most
A 200 response with an empty array where results were expected, a paginated response missing its pagination metadata, or a JSON body that silently changed shape after a backend deploy — all pass a status-code- only check while being genuinely broken for whatever consumes the API. This is the single most common gap in API monitoring setups: checking that something answered, not that it answered correctly.
What a more complete check actually verifies
- Response schema. Confirming the response has the expected fields, of the expected types, catches contract-breaking changes — often introduced accidentally by an unrelated backend deploy — long before every consumer of the API notices independently.
- Response time, as a distribution, not an average. An average can look fine while a meaningful share of requests are much slower — tracking a high percentile (p95 or p99) surfaces the tail latency that an average quietly hides.
- Rate-limit headers. Watching your own API's
rate-limit response headers over time reveals usage trending toward a
limit before consumers actually start hitting
429responses. - Authentication and credential expiry. An API key, OAuth token, or certificate quietly expiring produces a sudden wave of 401/403 errors that looks like an outage but is really a credentials problem — worth checking expiry proactively rather than waiting for the failure.
CORS is a browser-only concern, and a common false alarm
A CORS-related failure only ever happens in a browser context — a server-side monitoring check calling the same endpoint will succeed even when a browser-based client is failing on a strict CORS policy, since CORS enforcement is a browser behavior, not a server-side check. This is why "the monitoring check passes but the frontend is broken" can legitimately both be true at once — the two are testing genuinely different things, and API monitoring needs an explicit CORS check if browser clients matter, not an assumption that a passing server-side check covers it.
Multi-step flows need chained checks
Many real API usage patterns aren't a single request — authenticate, then fetch a resource, then act on it using data from the first response. A monitoring setup limited to independent single-endpoint checks can't catch a break in that chain (a token that authenticates fine but doesn't carry the right scope for the next call, for example) — this needs a genuinely chained check that mirrors the real usage pattern, not just a battery of unrelated single-request checks.