Cost, capacity, and reliability · Lesson 5 of 14 · 8 min

Read concurrency limits

Concurrency limits bound in-flight work; they do not directly state requests per second. Throughput also depends on service time and workload size.

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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-cost-reliability-005.json. Separate the recorded facts from your assumptions.
Hint & worked example
Concurrency limits bound in-flight work; they do not directly state requests per second. Throughput also depends on service time and workload size.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-cost-reliability-005.json
```
Common mistake to avoid: Sixteen in-flight slots guarantee sixteen requests per second.
2
Isolate the deciding signal
Select the queue_depth field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Manage admission or capacity because the in-flight limit is full and eight requests are queued.
A successful JSON query isolates queue_depth.
```
jq .queue_depth /opt/ai-lab/cases/aiops-cost-reliability-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: manage-admission, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-cost-reliability-005-decision.txt.
Hint & worked example
Manage admission or capacity because the in-flight limit is full and eight requests are queued.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'manage-admission' > /home/learner/lab/aiops-cost-reliability-005-decision.txt
```
Common mistake to avoid: Sixteen in-flight slots guarantee sixteen requests per second.

Understand the pattern

Concurrency limits bound in-flight work; they do not directly state requests per second. Throughput also depends on service time and workload size.

Interpret the evidence

Manage admission or capacity because the in-flight limit is full and eight requests are queued.

A tempting mistake

Sixteen in-flight slots guarantee sixteen requests per second.

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-cost-reliability-005.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "max_in_flight": 16,
  "currently_in_flight": 16,
  "queue_depth": 8
}

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

$ jq .queue_depth /opt/ai-lab/cases/aiops-cost-reliability-005.json

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

$ printf '%s\n' 'manage-admission' > /home/learner/lab/aiops-cost-reliability-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 “manage-admission” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Read concurrency limits” justify?Sixteen in-flight slots guarantee sixteen requests per second.Make the change now and gather the missing evidence afterward.Manage admission or capacity because the in-flight limit is full and eight requests are queued.

Apply it elsewhere

A colleague concludes: “Sixteen in-flight slots guarantee sixteen requests per second.” 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: Estimate capacity headroom Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision