PCA Practice Test 2 — 10 Questions

Question 1

What is the purpose of the 'up' metric?

Accepted Answer

To indicate if a target is reachable. The 'up' metric is 1 if the target was successfully scraped and 0 otherwise.

Answer

To show system uptime

Answer

To measure request latency

Answer

To track CPU usage

Question 2

You need to calculate the 99th percentile HTTP request latency from a Prometheus histogram named http_request_duration_seconds. Which function is correct?

Accepted Answer

histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m])). The correct PromQL expression is histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m])). This computes the 99th percentile by first calculating the per-second rate of increase of each bucket over a 5-minute window, then applying histogram_quantile to interpolate the quantile from the bucket boundaries. The rate function is essential to convert cumulative counters into a rate suitable for quantile estimation.

Answer

rate(histogram_quantile(0.99, http_request_duration_seconds_bucket)[5m])

Answer

quantile_over_time(0.99, http_request_duration_seconds[5m])

Answer

histogram_quantile(http_request_duration_seconds_bucket[5m], 0.99)

Question 3

Which function is used to convert a counter rate into a per-second rate over a time range?

Accepted Answer

rate(). rate() is the standard function for per-second rates of counters.

Answer

delta()

Answer

increase()

Answer

sum()

Question 4

You are troubleshooting high cardinality in your metrics. What is a common cause for this in a custom exporter?

Accepted Answer

Including dynamic values like IDs or timestamps in label values.. High cardinality occurs when a label value has an unbounded number of unique values (like a request ID or a timestamp), causing a massive explosion in the number of unique time series.

Answer

Using too many different metrics.

Answer

Scraping the exporter too frequently.

Answer

Using the wrong metric type for a simple count.

Question 5

Which THREE of the following are valid components within a Prometheus Alerting Rule file?

Accepted Answer

expr. Prometheus alerting rules contain a 'groups' array, which contains individual 'rules' (alerts or recordings), and each alert rule must have an 'alert' name and 'expr'.

Answer

receiver

Answer

routing_tree

Question 6

Which THREE of the following are valid aggregation operators in PromQL? (Choose THREE)

Accepted Answer

stddev. In PromQL, the aggregation operators are applied with syntax like ([parameter,] ) [without|by (...)], and the valid set includes stddev, sum, and topk. Option C (stddev) is correct because stddev is a built-in aggregation operator that computes the standard deviation across the aggregated time series. Option D (sum) is correct because sum is a core aggregation operator that adds the values of all matched series. Option E (topk) is correct because topk is a parameterized aggregation operator that returns the k series with the highest values. Options A (median) and B (average) are not valid PromQL aggregation operators; the average is expressed as sum(...) / count(...), and median is not provided as an aggregation operator in PromQL.

Answer

median

Answer

average

Question 7

A Prometheus administrator wants to query the current value of the metric 'http_requests_total'. Which of the following PromQL expressions should be used?

Accepted Answer

http_requests_total. The expression `http_requests_total` is a valid PromQL instant vector selector that returns the current value of the metric at the evaluation timestamp. It does not require a range or function because the question asks for the current value, not a rate or aggregation. This is the simplest and correct way to query a single metric's latest sample.

Answer

http_requests_total[5m]

Answer

rate(http_requests_total)

Answer

sum(http_requests_total) over (instance)

Question 8

How does Prometheus handle subqueries embedded within an instant query, such as rate(http_requests_total[5m])[30m:1m]?

Accepted Answer

It runs the inner instant query at multiple evaluation timestamps over the specified range at the given resolution, returning a range vector.. Prometheus evaluates subqueries by running the inner instant query at each step of the outer range, using the specified resolution (1m) and range (30m). This produces a range vector that can then be used by outer functions like rate(). The subquery syntax [30m:1m] means evaluate the inner expression over the last 30 minutes at 1-minute intervals.

Answer

It caches the inner query results in memory for 30 minutes.

Answer

It increases the global scrape interval to 1 minute for the next 30 minutes.

Answer

It converts the range vector into a scalar through statistical interpolation.

Question 9

Which TWO of the following statements regarding PromQL subqueries are correct? (Choose two)

Accepted Answer

Subqueries allow instant vector queries to be passed as range vector inputs to functions like max_over_time().. Option B is correct because a PromQL subquery wraps an instant vector expression and evaluates it over a time range, producing a range vector that can be fed into range-vector functions such as max_over_time(), avg_over_time(), or rate(). Option C is correct because the subquery syntax is exactly [:], for example max_over_time(rate(http_requests_total[5m])[1h:1m]). Option A is wrong because subqueries do not bypass the storage engine; they still query TSDB data and typically add overhead by evaluating the inner expression at each resolution step. Option D is wrong because subqueries operate on instant vector expressions (the inner expression must return an instant vector), not exclusively on range vectors. Option E is wrong because the resolution parameter is optional; when omitted, Prometheus uses the global evaluation_interval as the default step.

Answer

Subqueries execute faster than standard instant queries because they bypass the storage engine.

Answer

Subqueries can only be executed against range vectors, never instant vectors.

Answer

The resolution parameter in a subquery is mandatory.

Question 10

You need to send critical alerts to a specific Slack channel while warning alerts go to email. Where should this routing logic be defined?

Accepted Answer

In the Alertmanager 'route' configuration. The Alertmanager 'route' configuration is where routing logic is defined. It uses a tree of routes with matchers (e.g., severity='critical') to direct alerts to specific receivers (e.g., Slack for critical, email for warning). This is the core mechanism for conditional alert routing in Prometheus-based monitoring.

Answer

In the Alertmanager 'receivers' configuration

Answer

In the Grafana 'Alerting' UI

Answer

In the Prometheus 'alerting' rule file