PCA Instrumentation And Exporters Practice Question
Which TWO factors directly influence the accuracy of quantile calculations when using Prometheus Summary metrics?
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
✓
The configured quantiles (e.g., 0.9, 0.99).
Summaries compute quantiles on the client side, and accuracy is determined by the configured quantiles and the sliding time window over which they are calculated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The total number of instances scraping the metric.
Why it's wrong here
Scraping frequency does not change the internal quantile calculation of a summary.
- ✓
The configured quantiles (e.g., 0.9, 0.99).
Why this is correct
The chosen quantiles determine what the client tracks.
- ✗
The CPU architecture of the client host.
Why it's wrong here
CPU architecture does not influence metric accuracy.
- ✗
The number of buckets defined in the configuration.
Why it's wrong here
Buckets are specific to Histograms, not Summaries.
- ✓
The sliding time window for observation calculation.
Why this is correct
The time window is critical for how the client ages out old data.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official CNCF / Linux Foundation exam blueprint
This PCA practice question is part of Courseiva's free CNCF / Linux Foundation certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCA exam.