Inference requests and APIs · Lesson 14 of 16 · 6 min

Review idempotency guidance

Idempotency is an endpoint contract, not a property to assume. Reusing a key is useful only where the service documents how duplicate requests are handled.

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-inference-apis-014.json. Separate the recorded facts from your assumptions.
Hint & worked example
Idempotency is an endpoint contract, not a property to assume. Reusing a key is useful only where the service documents how duplicate requests are handled.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-inference-apis-014.json
```
Common mistake to avoid: Every POST is safe to repeat if the client timed out.
2
Isolate the deciding signal
Select the idempotency_supported field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Resolve the previous result before repeating a potentially non-idempotent job creation.
A successful JSON query isolates idempotency_supported.
```
jq .idempotency_supported /opt/ai-lab/cases/aiops-inference-apis-014.json
```
Common mistake to avoid: Using a different case or an unrelated signal as the justification.
3
Record your operational decision
Choose the justified code: resolve-prior-result, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-inference-apis-014-decision.txt.
Hint & worked example
Resolve the previous result before repeating a potentially non-idempotent job creation.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'resolve-prior-result' > /home/learner/lab/aiops-inference-apis-014-decision.txt
```
Common mistake to avoid: Every POST is safe to repeat if the client timed out.

Understand the pattern

Idempotency is an endpoint contract, not a property to assume. Reusing a key is useful only where the service documents how duplicate requests are handled.

Interpret the evidence

Resolve the previous result before repeating a potentially non-idempotent job creation.

A tempting mistake

Every POST is safe to repeat if the client timed out.

All names, measurements, prices, versions, and thresholds in this exercise are fictional training data. The evidence supports this bounded scenario, not a claim about a live provider.

Worked example and expected result

$ cat /opt/ai-lab/cases/aiops-inference-apis-014.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "operation": "create-job",
  "idempotency_supported": false,
  "previous_result": "unknown"
}

Exit status: 0. The command completed successfully in the training fixture.

$ jq .idempotency_supported /opt/ai-lab/cases/aiops-inference-apis-014.json

false

Exit status: 0. The command completed successfully in the training fixture.

$ printf '%s\n' 'resolve-prior-result' > /home/learner/lab/aiops-inference-apis-014-decision.txt

(no output; exit 0)

Exit status: 0. The command completed successfully in the training fixture.

Try a variation

Name the assumption that would have to change for “resolve-prior-result” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Review idempotency guidance” justify?Resolve the previous result before repeating a potentially non-idempotent job creation.Every POST is safe to repeat if the client timed out.Make the change now and gather the missing evidence afterward.

Apply it elsewhere

A colleague concludes: “Every POST is safe to repeat if the client timed out.” What should you do?Accept it because the training command completed.Treat this fixture as a live measurement.Reject that conclusion; return to the case evidence and its stated limits.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Build an API evidence bundle Try an incident drill

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Case methodology: evidence, limits, decision