Schema Validation

Overview

Schema Validation checks data against a declared schema for types, required fields, constraints, formats, object structure, and allowed alternatives. It does not replace authentication or business validation because structurally valid data can still be unauthorized, inconsistent, or operationally unsafe.

The main risks include rejecting compatible extensions, accepting coerced invalid data, schema drift, denial of service from complex payloads, and incomplete error handling. It can be applied to API requests, responses, webhook payloads, configuration, and event messages. Data handled by Schema Validation should use documented types, units, timestamp rules, nullable fields, and enum behavior to prevent silent interpretation errors.

In production, teams should define ownership and apply versioned schemas, strict but compatible rules, clear error paths, size limits, unknown-field policy, and monitoring of validation failures. For Schema Validation, the application should preserve a correlation path from request construction through response, asynchronous completion, and final business state.

Useful measures include validation failure rate, top failed fields, schema-version usage, drift incidents, and false rejection count. Schema Validation is closely connected to Request Schema, Response Schema, and Webhook Payload Validation. Observability for Schema Validation should record operation, version, principal, request ID, latency, retry count, error code, and final state without exposing secrets.

Testing Schema Validation should cover malformed input, denied access, rate limits, timeouts, duplicates, asynchronous completion, and version changes. The Schema Validation owner should publish stable error semantics and guidance on whether correction, retry, status lookup, or escalation is appropriate.

The Schema Validation contract should define identifiers, validation, authorization, status semantics, errors, limits, and version behavior at the same boundary.