Querying & Visualization Flashcards
7 cards from real PCA practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Querying & Visualization flashcards as text
What is the correct way to calculate the 95th percentile from a Prometheus histogram metric named `http_request_duration_seconds`?
Answer: `histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m]))`
`histogram_quantile()` requires the quantile as a decimal (0-1) and a range vector of the `_bucket` series with `rate()` applied.
What special label does Prometheus use to define the upper bound of each histogram bucket?
Answer: `le`
Prometheus histograms use the `le` label (meaning 'less than or equal') to mark the upper boundary of each bucket.
What is a key advantage of using a Prometheus histogram over a summary for calculating quantiles?
Answer: Histograms allow quantile calculation across multiple instances by aggregating buckets
Histogram buckets can be aggregated across multiple instances using `sum()`, allowing server-side quantile calculation, whereas summary quantiles are computed client-side and cannot be aggregated.
In a Prometheus histogram, what does the `_count` suffix metric represent?
Answer: The total number of observations recorded
The `_count` metric is a counter representing the total number of observations made, equivalent to the value in the `+Inf` bucket.
In Grafana, what is the purpose of a 'template variable' in a dashboard?
Answer: To allow users to dynamically filter or switch the data shown across panels
Template variables in Grafana allow dashboard users to interactively select values (like a job or instance) that are substituted into panel queries, making dashboards reusable.
Which Grafana panel type is most appropriate for displaying a single current metric value such as the number of active connections?
Answer: Stat
The Stat panel displays a single large numeric value with optional coloring based on thresholds, ideal for KPI-style current metrics.
What does the `delta()` function return when applied to a gauge metric in PromQL?
Answer: The difference between the first and last value in the range
`delta()` calculates the difference between the first and last value of a gauge in the range vector, using extrapolation to fill edge gaps.