Serving, containers, and resources · Lesson 9 of 17 · 5 min

Read pod logs

Container logs describe a particular process instance. After a restart, retain the prior instance evidence when it is needed to explain the failure.

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-serving-resources-009.json. Separate the recorded facts from your assumptions.
Hint & worked example
Container logs describe a particular process instance. After a restart, retain the prior instance evidence when it is needed to explain the failure.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-serving-resources-009.json
```
Common mistake to avoid: A clean startup log proves the previous process never failed.
2
Isolate the deciding signal
Select the previous_log field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Inspect the previous out-of-memory event rather than dismissing the restart because current startup succeeded.
A successful JSON query isolates previous_log.
```
jq .previous_log /opt/ai-lab/cases/aiops-serving-resources-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: inspect-previous-instance, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-serving-resources-009-decision.txt.
Hint & worked example
Inspect the previous out-of-memory event rather than dismissing the restart because current startup succeeded.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'inspect-previous-instance' > /home/learner/lab/aiops-serving-resources-009-decision.txt
```
Common mistake to avoid: A clean startup log proves the previous process never failed.

Understand the pattern

Container logs describe a particular process instance. After a restart, retain the prior instance evidence when it is needed to explain the failure.

Interpret the evidence

Inspect the previous out-of-memory event rather than dismissing the restart because current startup succeeded.

A tempting mistake

A clean startup log proves the previous process never failed.

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-serving-resources-009.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "restart_count": 2,
  "current_log": "started successfully",
  "previous_log": "out of memory"
}

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

$ jq .previous_log /opt/ai-lab/cases/aiops-serving-resources-009.json

"out of memory"

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

$ printf '%s\n' 'inspect-previous-instance' > /home/learner/lab/aiops-serving-resources-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 “inspect-previous-instance” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Read pod logs” justify?A clean startup log proves the previous process never failed.Make the change now and gather the missing evidence afterward.Inspect the previous out-of-memory event rather than dismissing the restart because current startup succeeded.

Apply it elsewhere

A colleague concludes: “A clean startup log proves the previous process never failed.” 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: Inspect pod resources Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision