Models, artifacts, and runtimes · Lesson 5 of 16 · 6 min

Verify an artifact checksum

Checksums detect byte differences relative to a reference. The reference must itself be trusted, and a mismatch should stop activation until its cause is understood.

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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-models-runtimes-005.json. Separate the recorded facts from your assumptions.
Hint & worked example
Checksums detect byte differences relative to a reference. The reference must itself be trusted, and a mismatch should stop activation until its cause is understood.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-models-runtimes-005.json
```
Common mistake to avoid: Ignore the mismatch because the file sizes are close.
2
Isolate the deciding signal
Select the same_bytes field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Do not activate an artifact whose bytes differ from the trusted reference.
A successful JSON query isolates same_bytes.
```
jq .same_bytes /opt/ai-lab/cases/aiops-models-runtimes-005.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: quarantine-mismatch, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-models-runtimes-005-decision.txt.
Hint & worked example
Do not activate an artifact whose bytes differ from the trusted reference.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'quarantine-mismatch' > /home/learner/lab/aiops-models-runtimes-005-decision.txt
```
Common mistake to avoid: Ignore the mismatch because the file sizes are close.

Understand the pattern

Checksums detect byte differences relative to a reference. The reference must itself be trusted, and a mismatch should stop activation until its cause is understood.

Interpret the evidence

Do not activate an artifact whose bytes differ from the trusted reference.

A tempting mistake

Ignore the mismatch because the file sizes are close.

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-005.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "expected": "sha256:training-111",
  "observed": "sha256:training-222",
  "same_bytes": false
}

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

$ jq .same_bytes /opt/ai-lab/cases/aiops-models-runtimes-005.json

false

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

$ printf '%s\n' 'quarantine-mismatch' > /home/learner/lab/aiops-models-runtimes-005-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 “quarantine-mismatch” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Verify an artifact checksum” justify?Do not activate an artifact whose bytes differ from the trusted reference.Ignore the mismatch because the file sizes are close.Make the change now and gather the missing evidence afterward.

Apply it elsewhere

A colleague concludes: “Ignore the mismatch because the file sizes are close.” 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: Match model and runtime Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision