KCNA Counter Practice Question
Which TWO of the following are valid Prometheus metric types? (Select two.)
⚠ Common exam trap
KCNA often tests whether candidates confuse observability signal types (logs, metrics, traces) with Prometheus metric types, so options like 'Log' and 'Trace' look plausible but are not Prometheus metric primitives.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Counter
Counter is one of the four core Prometheus metric types, representing a cumulative value that only increases (or resets to zero on restart), such as http_requests_total. Option D (Histogram) is also correct because Histogram is a core Prometheus metric type that samples observations into configurable buckets and exposes _bucket, _sum, and _count series, commonly used for request durations or response sizes. The other options do not belong: Log (A) and Trace (E) are observability signal categories (logs and distributed traces) rather than Prometheus metric types, and Event (C) is not a Prometheus metric type—Prometheus has Gauge and Summary as its other two types, but neither is listed here.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Log
Why it's wrong here
Log is not a Prometheus metric type; logs are collected by separate tooling such as Loki or Elasticsearch. It tempts because monitoring stacks combine metrics and logs, but Prometheus stores only counter, gauge, histogram and summary samples, not log lines.
- ✓
Counter
Why this is correct
Counter metrics only increase monotonically, resetting solely on process restart, which satisfies Prometheus's requirement for cumulative time-series data such as request totals. This monotonic behaviour distinguishes it from gauges, which rise and fall freely, and makes Counter one of the four valid Prometheus metric types alongside Gauge, Histogram and Summary.
- ✗
Event
Why it's wrong here
Prometheus exposes four metric types: Counter, Gauge, Histogram and Summary; Event is not among them, so it cannot be selected. The term is tempting because event-driven monitoring and logging pipelines genuinely track discrete occurrences, but Prometheus records numeric time series, not event objects.
- ✓
Histogram
Why this is correct
Histogram is a core Prometheus metric type, satisfying the stem's requirement for valid types. It samples observations into configurable buckets and exposes cumulative counters plus a sum, enabling calculation of quantiles and distributions via histogram_quantile. This distinguishes it from summaries, which compute quantiles client-side instead.
- ✗
Trace
Why it's wrong here
Trace is not a Prometheus metric type; tracing is handled by separate systems such as Jaeger or Tempo. It tempts because observability stacks pair metrics with traces, but Prometheus exposes only counter, gauge, histogram and summary, so trace data must be ingested elsewhere.
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Same concept, more angles
3 more ways this is tested on KCNA
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Which TWO of the following are valid Prometheus metric types? (Select two)
medium- A.Set
- ✓ B.Counter
- C.Timer
- D.Meter
- ✓ E.Gauge
Why B: Option B (Counter) is correct because Prometheus defines Counter as a core metric type: a cumulative value that only increases (or resets to zero on restart), typically used for counts like total requests or errors, and queried with rate()/increase(). Option E (Gauge) is also correct because Prometheus defines Gauge as a metric type representing a value that can arbitrarily go up and down, such as temperature, memory usage, or current queue depth. The other options are not Prometheus metric types: Set, Timer, and Meter are metric abstractions found in other monitoring libraries/systems (for example, Dropwizard Metrics or Micrometer), not in the Prometheus client data model, whose four types are Counter, Gauge, Histogram, and Summary.
Variation 2. Which TWO of the following are Prometheus metric types? (Select two.)
medium- A.Event
- ✓ B.Gauge
- C.Set
- ✓ D.Counter
- E.Timer
Why B: Prometheus defines exactly four core metric types, and Gauge (B) is one of them: it represents a value that can arbitrarily go up or down, such as current temperature or memory usage. Counter (D) is also a core Prometheus metric type: it is a cumulative value that only increases (or resets to zero on restart), used for things like total requests served. The other options are not Prometheus metric types: Event (A) is not a Prometheus concept, Set (C) is a StatsD metric type, and Timer (E) is also a StatsD metric type, so none of them belong to Prometheus's metric model.
Variation 3. Which TWO of the following are valid Prometheus metric types?
medium- A.Quantile
- ✓ B.Counter
- C.Timer
- D.Meter
- ✓ E.Gauge
Why B: Option B (Counter) is correct because Prometheus defines the counter metric type as a cumulative value that only increases or resets to zero on restart, typically used for counts of events or errors. Option E (Gauge) is correct because Prometheus defines the gauge metric type as a value that can arbitrarily go up and down, used for measurements like temperature, memory usage, or current queue size. The other options are not Prometheus metric types: Quantile (A) is a concept used in summary/histogram quantile calculations rather than a metric type itself, while Timer (C) and Meter (D) are metric types from other monitoring libraries such as Dropwizard Metrics or Micrometer, not native Prometheus types.
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CNCF exam blueprint
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