Do not apply a job receipt just because it is valid JSON. First validate its structure against a versioned schema, then check whether the requested action is authorized, intended for the right target, allowed by policy, and based on current state. Preflight the change where possible, and apply it only if every check passes.
What a job receipt should prove
A job receipt is a machine-readable description of an operation. Treat it as a contract to evaluate before execution—not as proof that the operation is safe. Validation has several distinct gates:
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- Structure: Are required fields present, correctly typed, and limited to allowed values?
- Meaning and policy: Is the action permitted, intended, and consistent with domain rules?
- Trust: If the receipt is signed, is the signature valid and its issuer trusted?
- State and timing: Does the receipt still refer to the intended target and current state?
- Preflight: Can the system evaluate the request without persisting the change?
Passing one gate does not imply passing the others. A schema validator can accept a well-formed request whose action is unauthorized or whose target has changed.
Define a versioned schema
Specify the schema version alongside the receipt so that a receipt can be interpreted using the contract it was created for. Define required fields, field types, and allowed values, including explicit rules for fields the schema does not recognize.
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JSON Schema can validate structural constraints, but its default keyword is an annotation: validation does not populate a missing value. If an application depends on defaults, implement that behavior explicitly and decide whether defaulting happens before or after validation.
Choose an explicit policy for unknown and duplicate fields. Kubernetes documents that unknown fields may be dropped by default; strict field validation rejects unknown or duplicate fields with a bad-request response. Silent dropping can make a receipt appear accepted even when the caller’s intended data was not honored, so rejection is safer when the system can enforce it.
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Validate in a deliberate sequence
- Parse the input. Reject malformed JSON before any operation can change state.
- Validate against the declared schema version. Check required fields, types, allowed values, and the unknown- and duplicate-field policy.
- Run domain checks. Verify the requester’s authorization, target identity, permitted action, policy limits, freshness, and consistency with the user’s intent. These are application-level checks, not conclusions a structural schema can supply.
- Verify provenance when applicable. For a signed receipt, verify its signature and the trust relationship for the issuer’s key or certificate. Keep this result separate from the decision that the requested action is allowed.
- Preflight the operation. Use a dry-run or equivalent validation path when supported, and inspect its result before applying.
- Apply with a freshness precondition. Bind the write to the state version or other precondition that was checked. If the state has changed, stop and reassess rather than blindly retrying.
What a dry run can—and cannot—tell you
A dry run exercises relevant request processing before persistence. In Kubernetes, dry-run requests go through applicable admission and schema-validation stages without being persisted. The Kubernetes API Concepts documentation states: “Kubernetes guarantees that dry-run requests will not be persisted in storage or have any other side effects.” That guarantee is specific to Kubernetes dry-run requests; other systems need their own documented guarantees.
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Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →A preview is not necessarily an exact forecast of the eventual stored object. Kubernetes notes that generated values may differ between a dry-run request and the real request. Treat the preview as evidence that the request passed the stages actually run, not as a transaction lock or a promise that future state will be identical.
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Prevent stale receipts from overwriting newer state
Even a trusted, authorized receipt can become unsafe if the target changes after validation. Kubernetes resource-version checks detect lost updates: submitting an outdated version returns a conflict. Use version checks or equivalent preconditions at apply time, and handle a conflict by fetching current state and reevaluating the receipt against it. A retry without reevaluation can turn a valid operation on old state into an unintended change on new state.
Why schema validity is not semantic safety
A May 2026 preprint by Yin Li, “When JSON Is Not Enough: Semantic Reliability of Schema-Constrained LLM Ordering Agents,” illustrates the distinction. In a benchmark involving 2,400 calls to Nebius Token Factory across four open models and two prompting modes, the strongest model achieved 100% schema validity in both tested modes but near 80% semantic success; weaker models produced double-digit schema-valid unsafe acceptances. These are results from a specific restaurant-ordering benchmark, not general production failure rates. They show why a parser’s acceptance cannot replace checks for meaning, policy, and target state.
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Use separate decisions for parsing, trust, and permission
RFC 9943, published by the RFC Editor/IETF in May 2026, requires receipt-signature verification and trust in a verification key or certificate associated with at least one receipt issuer. It also permits additional validation policies after cryptographic verification. In practice, record these as separate outcomes: the receipt parsed, its signature and issuer trust were verified, and the requested operation passed the applicable policy checks. A valid signature establishes neither user intent nor authorization by itself.
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Sources
- RFC 9943, RFC Editor/IETF, May 2026.
- Kubernetes API Concepts, official living documentation, accessed October 7, 2026.
- Understanding JSON Schema: Annotations, Draft 2020-12 guide.
- Yin Li, “When JSON Is Not Enough: Semantic Reliability of Schema-Constrained LLM Ordering Agents”, arXiv preprint, posted May 16, 2026.
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