Inference requests and APIs · Lesson 6 of 16 · 8 min

Distinguish client and server errors

Client and server status classes point to different boundaries. A malformed request calls for correction, while a transient server failure may warrant a bounded retry policy.

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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-006.json. Separate the recorded facts from your assumptions.
Hint & worked example
Client and server status classes point to different boundaries. A malformed request calls for correction, while a transient server failure may warrant a bounded retry policy.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-inference-apis-006.json
```
Common mistake to avoid: Treat every non-200 response as a transient server outage.
2
Isolate the deciding signal
Select the retry_unchanged field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Correct the client request rather than repeatedly sending the same invalid envelope.
A successful JSON query isolates retry_unchanged.
```
jq .retry_unchanged /opt/ai-lab/cases/aiops-inference-apis-006.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: correct-client-request, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-inference-apis-006-decision.txt.
Hint & worked example
Correct the client request rather than repeatedly sending the same invalid envelope.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'correct-client-request' > /home/learner/lab/aiops-inference-apis-006-decision.txt
```
Common mistake to avoid: Treat every non-200 response as a transient server outage.

Understand the pattern

Client and server status classes point to different boundaries. A malformed request calls for correction, while a transient server failure may warrant a bounded retry policy.

Interpret the evidence

Correct the client request rather than repeatedly sending the same invalid envelope.

A tempting mistake

Treat every non-200 response as a transient server outage.

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-006.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "status": 400,
  "error": "invalid_request",
  "retry_unchanged": false
}

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

$ jq .retry_unchanged /opt/ai-lab/cases/aiops-inference-apis-006.json

false

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

$ printf '%s\n' 'correct-client-request' > /home/learner/lab/aiops-inference-apis-006-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 “correct-client-request” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Distinguish client and server errors” justify?Treat every non-200 response as a transient server outage.Make the change now and gather the missing evidence afterward.Correct the client request rather than repeatedly sending the same invalid envelope.

Apply it elsewhere

A colleague concludes: “Treat every non-200 response as a transient server outage.” 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: Reason about timeouts Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision