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Cost, capacity, and reliability · Lesson 6 of 14 · 9 min

Estimate capacity headroom

Capacity headroom compares measured demand with a relevant tested limit. State the workload and measurement assumptions instead of calling all unused resources interchangeable.

Open the labCourse map
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learner@clairosSimulated AI Ops lab
learner@clairos:~ $
↑ history · Tab complete · Ctrl+C cancel · Esc, Tab to leaveExit 0

Understand the pattern

Capacity headroom compares measured demand with a relevant tested limit. State the workload and measurement assumptions instead of calling all unused resources interchangeable.

Interpret the evidence

Record 20 percent headroom under this tested workload and limit.

A tempting mistake

The headroom is 80 percent because current use is 80.

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-006.json
{
  "fixture": "Fictional training data; not a live measurement.",
  "tested_rps_limit": 100,
  "current_rps": 80,
  "headroom_percent": 20
}

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

$ jq .headroom_percent /opt/ai-lab/cases/aiops-cost-reliability-006.json
20

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

$ printf '%s\n' 'record-20-percent-headroom' > /home/learner/lab/aiops-cost-reliability-006-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 “record-20-percent-headroom” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Estimate capacity headroom” justify?

Apply it elsewhere

A colleague concludes: “The headroom is 80 percent because current use is 80.” What should you do?

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Inspect queue depthTry an incident drill

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Keep learning

  1. 01Read concurrency limitsConcurrency limits bound in-flight work; they do not directly state requests per second. Throughput also depends on service time and workload size.Practice
  2. 02Inspect queue depthQueue depth is meaningful with arrival and completion rates. A growing queue can signal overload even while workers remain healthy.Practice
  3. 03Compare latency and costCost and latency tradeoffs must respect task quality and service targets. Choose among configurations that pass the required gates rather than optimizing a single metric.Practice

Case methodology: evidence, limits, decision