Incident response and capstones · Lesson 6 of 12 · 8 min

Trace a cost spike

A cost spike should be explained with comparable units and a measured driver. Increased retries can multiply work even when successful request counts remain flat.

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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-incidents-capstones-006.json. Separate the recorded facts from your assumptions.
Hint & worked example
A cost spike should be explained with comparable units and a measured driver. Increased retries can multiply work even when successful request counts remain flat.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-incidents-capstones-006.json
```
Common mistake to avoid: Flat successful request counts prove total work is unchanged.
2
Isolate the deciding signal
Select the attempts_after field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Investigate and bound retry amplification from 1020 to 3000 attempts.
A successful JSON query isolates attempts_after.
```
jq .attempts_after /opt/ai-lab/cases/aiops-incidents-capstones-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: bound-retry-amplification, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-incidents-capstones-006-decision.txt.
Hint & worked example
Investigate and bound retry amplification from 1020 to 3000 attempts.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'bound-retry-amplification' > /home/learner/lab/aiops-incidents-capstones-006-decision.txt
```
Common mistake to avoid: Flat successful request counts prove total work is unchanged.

Understand the pattern

A cost spike should be explained with comparable units and a measured driver. Increased retries can multiply work even when successful request counts remain flat.

Interpret the evidence

Investigate and bound retry amplification from 1020 to 3000 attempts.

A tempting mistake

Flat successful request counts prove total work is unchanged.

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-incidents-capstones-006.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "successful_requests": 1000,
  "attempts_before": 1020,
  "attempts_after": 3000,
  "mean_tokens_unchanged": true
}

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

$ jq .attempts_after /opt/ai-lab/cases/aiops-incidents-capstones-006.json

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

$ printf '%s\n' 'bound-retry-amplification' > /home/learner/lab/aiops-incidents-capstones-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 “bound-retry-amplification” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Trace a cost spike” justify?Make the change now and gather the missing evidence afterward.Investigate and bound retry amplification from 1020 to 3000 attempts.Flat successful request counts prove total work is unchanged.

Apply it elsewhere

A colleague concludes: “Flat successful request counts prove total work is unchanged.” What should you do?Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.Treat this fixture as a live measurement.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Review a guardrail regression Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision