Models, artifacts, and runtimes · Lesson 13 of 16 · 9 min

Choose a rollback artifact

A rollback artifact should be known-good, retained and compatible with the current runtime and configuration. The oldest available file is not automatically a safe rollback.

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learner@clairos:~ $

↑ history · Tab complete · Ctrl+C cancel · Esc, Tab to leaveExit 0

Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-models-runtimes-013.json. Separate the recorded facts from your assumptions.
Hint & worked example
A rollback artifact should be known-good, retained and compatible with the current runtime and configuration. The oldest available file is not automatically a safe rollback.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-models-runtimes-013.json
```
Common mistake to avoid: Delete the verified version as soon as a candidate loads.
2
Isolate the deciding signal
Select the previously_verified field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Retain m2 with its verified checksum and compatible configuration as the rollback candidate.
A successful JSON query isolates previously_verified.
```
jq .previously_verified /opt/ai-lab/cases/aiops-models-runtimes-013.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: retain-verified-m2, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-models-runtimes-013-decision.txt.
Hint & worked example
Retain m2 with its verified checksum and compatible configuration as the rollback candidate.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'retain-verified-m2' > /home/learner/lab/aiops-models-runtimes-013-decision.txt
```
Common mistake to avoid: Delete the verified version as soon as a candidate loads.

Understand the pattern

A rollback artifact should be known-good, retained and compatible with the current runtime and configuration. The oldest available file is not automatically a safe rollback.

Interpret the evidence

Retain m2 with its verified checksum and compatible configuration as the rollback candidate.

A tempting mistake

Delete the verified version as soon as a candidate loads.

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-models-runtimes-013.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "candidate": "m2",
  "previously_verified": true,
  "runtime_compatible": true,
  "checksum_verified": true
}

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

$ jq .previously_verified /opt/ai-lab/cases/aiops-models-runtimes-013.json

true

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

$ printf '%s\n' 'retain-verified-m2' > /home/learner/lab/aiops-models-runtimes-013-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 “retain-verified-m2” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Choose a rollback artifact” justify?Make the change now and gather the missing evidence afterward.Retain m2 with its verified checksum and compatible configuration as the rollback candidate.Delete the verified version as soon as a candidate loads.

Apply it elsewhere

A colleague concludes: “Delete the verified version as soon as a candidate loads.” 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 model provenance Try an incident drill

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Case methodology: evidence, limits, decision