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Prometheus & Metric Types — KCNA Practice Question

A representative Kubernetes and Cloud Native Associate (KCNA) exam question on Prometheus & Metric Types. Work through it below, then read why each option is right or wrong.

This question is part of the free Kubernetes and Cloud Native Associate practice test.

Short answer

The correct answer is D. Gauge, because the value is a single number that can go up and down arbitrarily over time..

D is correct. A gauge is a single numerical value that can go up and down, which matches in-progress requests. The documentation's rule of thumb is that if a value can go down, it is a gauge. A is wrong because a counter only increases (or resets to zero on restart), so it cannot represent a value that falls. B is wrong because a summary tracks quantiles of observations over a sliding window, not a current level. C is wrong because a histogram counts observations such as durations into buckets, not a current count.

The Question

A team wants a Prometheus metric for the number of requests currently being processed by a server. The value rises when a request starts and falls when it ends. Which metric type fits?

ACounter, because each request that arrives must be added to a cumulative total over time.
BSummary, because the value must be computed over a sliding time window of recent samples.
CHistogram, because each request should be placed into a bucket based on how long it takes.
DGauge, because the value is a single number that can go up and down arbitrarily over time.Correct

Why D is correct

D is correct. A gauge is a single numerical value that can go up and down, which matches in-progress requests. The documentation's rule of thumb is that if a value can go down, it is a gauge. A is wrong because a counter only increases (or resets to zero on restart), so it cannot represent a value that falls. B is wrong because a summary tracks quantiles of observations over a sliding window, not a current level. C is wrong because a histogram counts observations such as durations into buckets, not a current count.

Why the other options are wrong

Option A: Counter, because each request that arrives must be added to a cumulative total over time.

Option A does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (D) is the only one that fully meets every constraint stated in the question.

Option B: Summary, because the value must be computed over a sliding time window of recent samples.

Option B does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (D) is the only one that fully meets every constraint stated in the question.

Option C: Histogram, because each request should be placed into a bucket based on how long it takes.

Option C does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (D) is the only one that fully meets every constraint stated in the question.

Key idea: Prometheus & Metric Types

D is correct. A gauge is a single numerical value that can go up and down, which matches in-progress requests. The documentation's rule of thumb is that if a value can go down, it is a gauge. A is wrong because a counter only increases (or resets to zero on restart), so it cannot represent a value that falls. B is wrong because a summary tracks quantiles of observations over a sliding window, not a current level. C is wrong because a histogram counts observations such as durations into buckets, not a current count. On the KCNA exam, questions in the "Cloud Native Architecture" domain test whether you can map a scenario's constraints to the right choice. Read the requirement carefully, eliminate options that violate any single constraint, and pick the one that satisfies all of them with the least operational overhead.

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Official sources used

Verify program and exam details at the source before scheduling.

prometheus.ioConcepts: Metric_typesprometheus.ioPractices: Instrumentation