KCNA Cloud Native Observability Practice Question

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Summary

  Why it's wrong here

  A summary records observations and computes configurable quantiles client-side, suiting latency percentiles rather than request totals. Counting HTTP requests needs a monotonically increasing value that only ever rises; a summary's quantile streams and _sum/_count do not provide that simple cumulative total.

• ✓

  Counter

  Why this is correct

  A Counter is a monotonically increasing metric that only goes up, making it ideal for cumulative totals such as HTTP requests received. Rate or increase functions applied to the counter yield per-second request rates, whereas Gauge and Histogram serve different measurement purposes.

• ✗

  Gauge

  Why it's wrong here

  A gauge represents a value that can rise or fall, such as current memory usage or in-flight requests, so it is unsuitable for a cumulative request count that must only increase. Counting total HTTP requests requires a counter, which resets only on process restart and supports rate() and increase().

• ✗

  Histogram

  Why it's wrong here

  A histogram buckets observations into cumulative ranges and produces a _sum and _count, so it can derive request totals, but its purpose is measuring value distributions such as latency. For a plain monotonic request counter, the counter type increments indefinitely and is queried directly with rate() or increase().