AI systems foundations · Lesson 11 of 15 · 5 min

Read a system dependency map

Dependencies form a directed map. A failed shared dependency can affect several healthy callers; confirm the dependency evidence instead of restarting every caller.

Open the lab Course map

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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-systems-foundations-011.json. Separate the recorded facts from your assumptions.
Hint & worked example
Dependencies form a directed map. A failed shared dependency can affect several healthy callers; confirm the dependency evidence instead of restarting every caller.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-systems-foundations-011.json
```
Common mistake to avoid: Restart every service without checking the shared dependency.
2
Isolate the deciding signal
Select the vector_store field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Inspect the unavailable vector store that the degraded retriever depends on.
A successful JSON query isolates vector_store.
```
jq .vector_store /opt/ai-lab/cases/aiops-systems-foundations-011.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-vector-store, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-systems-foundations-011-decision.txt.
Hint & worked example
Inspect the unavailable vector store that the degraded retriever depends on.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'inspect-vector-store' > /home/learner/lab/aiops-systems-foundations-011-decision.txt
```
Common mistake to avoid: Restart every service without checking the shared dependency.

Understand the pattern

Dependencies form a directed map. A failed shared dependency can affect several healthy callers; confirm the dependency evidence instead of restarting every caller.

Interpret the evidence

Inspect the unavailable vector store that the degraded retriever depends on.

A tempting mistake

Restart every service without checking the shared dependency.

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-systems-foundations-011.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "gateway": "ready",
  "retriever": "degraded",
  "vector_store": "unavailable",
  "retriever_depends_on": "vector_store"
}

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

$ jq .vector_store /opt/ai-lab/cases/aiops-systems-foundations-011.json

"unavailable"

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

$ printf '%s\n' 'inspect-vector-store' > /home/learner/lab/aiops-systems-foundations-011-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-vector-store” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Read a system dependency map” justify?Make the change now and gather the missing evidence afterward.Inspect the unavailable vector store that the degraded retriever depends on.Restart every service without checking the shared dependency.

Apply it elsewhere

A colleague concludes: “Restart every service without checking the shared dependency.” 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: Define an operator signal Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision