Walk the stages in order for Designing APIs Around Explicit Semantics: start from the contract, trace the representation through the operation, then confirm the boundary. Worked case: A PUT that replaces a resource can be retried safely when the same request produces the same target state. For a worked explanation, continue to the topic article and execution trace.
Stage-by-stage execution walkthrough
This request flow decomposes Designing APIs Around Explicit Semantics into 5 sequential stages so you can trace where latency accumulates, which state transitions are irreversible, and where production failure modes occur.
Stage 1: Contract
An API contract defines the meaning of operations, inputs, outputs, errors, and side effects. A good contract lets clients reason about retries and compatibility without depending on undocumented server behavior. HTTP methods communicate broad intent, while the application contract defines the resource-specific rules. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Stage 2: Representation
A PUT that replaces a resource can be retried safely when the same request produces the same target state. A POST that creates a payment may create duplicates unless the server recognizes an idempotency key. A response should distinguish validation failures, authorization failures, and transient server problems. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Stage 3: Operation
An endpoint creates an invoice but the client times out before receiving the response. Specify a request and storage design that lets the client retry without creating a second invoice. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Stage 4: Boundary
Backward compatibility includes behavior as well as field names: changing default ordering or error semantics can break clients. Adding an optional field is often safer than changing a required one, but strict client decoders may still reject it. Version only when compatibility policy and migration need justify it. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Stage 5: Result
An endpoint creates an invoice but the client times out before receiving the response. Specify a request and storage design that lets the client retry without creating a second invoice. During this transition, the runtime enforces strict state invariants before handing control to the next stage: inputs are validated at the boundary, state mutations are ordered deterministically, and latency/resource costs are bounded so downstream consumers never observe a torn or partially initialized state.
Production invariants and failure modes
Done when the worked check holds: An endpoint creates an invoice but the client times out before receiving the response. When debugging or capacity-planning this flow in production, instrument each stage boundary separately (measuring both p50 median and p99.9 tail latency), verify what happens when an intermediate stage times out or drops packets, and ensure retry or fallback paths preserve end-to-end idempotency.