Inference requests and APIs · Lesson 9 of 16 · 6 min

Inspect a request identifier

A request identifier ties a client operation to gateway and runtime evidence. Record the identifier rather than copying the whole prompt into ordinary logs.

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learner@clairos:~ $

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-inference-apis-009.json. Separate the recorded facts from your assumptions.
Hint & worked example
A request identifier ties a client operation to gateway and runtime evidence. Record the identifier rather than copying the whole prompt into ordinary logs.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-inference-apis-009.json
```
Common mistake to avoid: A request ID is useless unless the entire prompt is public.
2
Isolate the deciding signal
Select the request_id field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Record req-014 and bounded metadata instead of logging the sensitive prompt.
A successful JSON query isolates request_id.
```
jq .request_id /opt/ai-lab/cases/aiops-inference-apis-009.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: log-request-id, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-inference-apis-009-decision.txt.
Hint & worked example
Record req-014 and bounded metadata instead of logging the sensitive prompt.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'log-request-id' > /home/learner/lab/aiops-inference-apis-009-decision.txt
```
Common mistake to avoid: A request ID is useless unless the entire prompt is public.

Understand the pattern

A request identifier ties a client operation to gateway and runtime evidence. Record the identifier rather than copying the whole prompt into ordinary logs.

Interpret the evidence

Record req-014 and bounded metadata instead of logging the sensitive prompt.

A tempting mistake

A request ID is useless unless the entire prompt is public.

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-009.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "request_id": "req-014",
  "contains_sensitive_prompt": true,
  "logging_policy": "metadata-only"
}

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

$ jq .request_id /opt/ai-lab/cases/aiops-inference-apis-009.json

"req-014"

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

$ printf '%s\n' 'log-request-id' > /home/learner/lab/aiops-inference-apis-009-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 “log-request-id” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Inspect a request identifier” justify?A request ID is useless unless the entire prompt is public.Make the change now and gather the missing evidence afterward.Record req-014 and bounded metadata instead of logging the sensitive prompt.

Apply it elsewhere

A colleague concludes: “A request ID is useless unless the entire prompt is public.” What should you do?Treat this fixture as a live measurement.Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Follow a trace identifier Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision