KCNA Cloud Native Observability Practice Question
What type of Prometheus metric is best suited to count the total number of HTTP requests received by a service?
⚠ Common exam trap
KCNA often tests the distinction between metric types, and a common trap is confusing Counter with Gauge or Histogram, especially when the question mentions 'total number'—candidates might incorrectly think a Gauge can track totals or that a Histogram is needed for counting, but the key is that a Counter is specifically for cumulative counts.
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
A Counter is a cumulative metric that only increases (or resets to zero on restart), making it ideal for tracking the total number of events like HTTP requests. Since the total request count is monotonically increasing, a Counter directly represents this without additional processing. Other metric types like Gauge, Histogram, and Summary serve different purposes: Gauge can go up and down, Histogram and Summary are for distributions (e.g., request durations).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Histogram
Why it's wrong here
Histograms bucket observations to produce distributions and cumulative counts per bucket, not a single running total. Counting HTTP requests requires a Counter, which increments monotonically and supports rate() and increase(). Histograms suit latency or response-size distributions.
- ✗
Gauge
Why it's wrong here
Gauges represent values that rise and fall, such as temperature or queue depth, so they cannot track a cumulative request total. A Counter is the correct type because it only increments and resets on restart, enabling rate() and increase() queries.
- ✗
Summary
Why it's wrong here
A Summary records pre-computed quantiles and a total over a sliding window, so concurrent request counting across instances is awkward and quantile aggregation is lossy. It is tempting for latency percentiles, where it genuinely excels, but a Counter incremented per request is the metric type designed for cumulative totals.
- ✓
Counter
Why this is correct
Counters are monotonically increasing values, so each HTTP request increments the total without resetting. This satisfies the stem's requirement to count cumulative requests; the rate() function then derives requests per second from that running total.
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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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