PCA Multiple Select — 20 Questions

Question 1

Which TWO of the following are valid metric types natively supported by Prometheus? (Choose TWO)

Accepted Answer

Gauge. Prometheus natively supports four core metric types: Counter, Gauge, Histogram, and Summary. Option B (Gauge) is correct because a gauge represents a single numerical value that can arbitrarily go up and down, such as current memory usage or temperature. Option C (Counter) is correct because a counter is a cumulative metric that only increases (or resets to zero on restart), such as the total number of HTTP requests served. The other options are not valid Prometheus metric types: Matrix, Vector, and Scalar are PromQL data types (instant vector, range vector, scalar, string) used in query expressions, not metric types exposed by instrumented targets.

Answer

Matrix

Answer

Vector

Answer

Scalar

Question 2

Which TWO are common causes of high-cardinality in Kubernetes environments?

Accepted Answer

Using a unique transaction ID as a label.. High cardinality occurs when a metric label takes on a very large number of distinct values, multiplying the number of time series. Option B is correct because a unique transaction ID as a label creates a new series for every transaction, producing unbounded cardinality. Option C is correct because the pod name in a metric label changes with every pod restart or rollout, generating a new series per pod instance and causing cardinality to grow continuously. Options A, D, and E are not common causes of high cardinality: deployment names, cluster regions, and service names are relatively stable, low-cardinality dimensions with a limited set of values.

Answer

Using a deployment name label.

Answer

Using a cluster region label.

Answer

Using a service name label.

Question 3

Which TWO of the following are true about the Pushgateway?

Accepted Answer

Metrics must be deleted manually. Option D is correct because the Pushgateway never expires or garbage-collects pushed metrics on its own; pushed time series persist until they are explicitly removed, typically with an HTTP DELETE to a path such as /metrics/job/<job> (or via the pushgateway's admin API), so operators must delete stale metrics manually. Option E is correct because the Pushgateway exists specifically for short-lived, batch, or cron-style jobs that cannot be scraped reliably during their brief runtime; such jobs push their final metrics to the gateway, which then exposes them for Prometheus to scrape. Option A is wrong because the Pushgateway is not a drop-in replacement for standard scraping: it only holds pushed metrics and cannot discover or scrape targets, and it lacks the full semantics of a normal Prometheus scrape target. Option B is wrong because the Pushgateway is not a persistent metrics store; it keeps pushed metrics in memory and loses them on restart, with persistence being Prometheus's role. Option C is wrong because the Pushgateway does not automatically expire metrics; there is no built-in TTL, which is exactly why manual deletion is required.

Answer

It is a drop-in for standard scraping

Answer

It stores metrics persistently

Answer

It automatically expires metrics

Question 4

Which THREE of the following are valid label matchers?

Accepted Answer

!~. In Prometheus-style label matching, the valid matchers are = (equality), != (inequality), =~ (regex match), and !~ (negative regex match), so C (!~), D (=~), and E (!=) are all correct. C (!~) is right because it selects series whose label value does not match the given regular expression, e.g. job!~"api.*". D (=~) is right because it selects series whose label value matches the regular expression, e.g. job=~"api.*". E (!=) is right because it selects series whose label value differs from the given string, e.g. job!="api". Options A (>>) and B (==) are not valid matchers: >> is not a PromQL label operator at all, and == is a comparison operator used in expressions, not a label matcher.

Answer

>>

Answer

==

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

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 8

Which TWO of the following are benefits of using recording rules?

Accepted Answer

Simplifying complex queries. Recording rules are correct in options A and B because they precompute expensive or frequently used PromQL expressions and store the result as a new time series, so complex queries can be referenced by a simpler metric name (A: simplifying complex queries) and dashboards or alerts that use that precomputed series avoid re-evaluating the full expression at query time, which lowers query latency (B: reducing query latency). They do not add authentication to metrics (C), since authentication is handled by the metrics endpoint, reverse proxy, or service configuration, not by recording rules. They also do not automatically increase retention (D), because retention is controlled by storage configuration such as retention time or size limits, and they do not provide a UI for alerts (E), since alerting UIs come from tools like Alertmanager or Grafana rather than from recording rules themselves.

Answer

Adding authentication to metrics

Answer

Automatically increasing retention

Answer

Providing UI for alerts

Question 9

Which TWO of the following statements about PromQL label matchers are correct? (Choose TWO)

Accepted Answer

The = operator performs an exact string match.. Option A is correct because in PromQL the '=' label matcher performs an exact string match, selecting time series whose label value is precisely equal to the provided string. Option E is correct because the '!~' operator performs a negative regular expression match, excluding series whose label value matches the given regex. Option B is incorrect because '?=' is not a valid PromQL label matcher operator. Option C is incorrect because '=~' is a positive regular expression match for label values, not a numeric comparison operator. Option D is incorrect because '==' is not a valid label selector operator in PromQL; equality matching uses '='.

Answer

The ?= operator performs fuzzy string matching.

Answer

The =~ operator is used exclusively for numeric comparisons.

Answer

The == operator is valid inside label selectors for filtering.

Question 10

Which THREE of these are recommended practices for an observability strategy?

Accepted Answer

Maintain logs for granular incident analysis.. Option A is correct because logs provide the high-cardinality, event-level detail needed for granular incident analysis and root-cause investigation, complementing the aggregate view from metrics and traces. Option B is correct because alerting on symptoms (user-visible impact such as latency or error rate) rather than internal causes reduces noise and false pages, since causes can vary while the symptom reliably indicates user pain. Option E is correct because the Four Golden Signals — latency, traffic, errors, and saturation — are a widely recommended Google SRE framework for monitoring request-driven systems and catching the most important failure modes. Option C is not recommended because a zero threshold would fire alerts constantly on any nonzero value, producing alert fatigue rather than meaningful signal. Option D is not recommended because metrics are cheap and aggregatable but lose per-event context; logs and traces are still required for detailed debugging, so 'metrics for everything' is an overreach.

Answer

Always set alert thresholds to zero.

Answer

Use metrics for everything.

Question 11

Which TWO of the following can be configured globally?

Accepted Answer

scrape_interval. Options C (scrape_interval) and D (evaluation_interval) are correct because both are global configuration parameters in the Prometheus configuration file's top-level `global:` block, where scrape_interval sets the default interval between scraping targets and evaluation_interval sets how often alerting and recording rules are evaluated. These values apply to all scrape jobs and rule groups unless overridden at the job or group level, making them genuinely global settings. The other options do not belong: alertmanager_host is not a valid Prometheus global setting (Alertmanager targets are configured under `alerting: alertmanagers:` with host/port details), storage_path is a command-line flag (`--storage.tsdb.path`) rather than a global config option, and target_labels is not a global configuration directive (labels are applied per scrape job or via relabeling).

Answer

alertmanager_host

Answer

storage_path

Answer

target_labels

Question 12

Which THREE labels are often considered part of the default Prometheus ecosystem metrics?

Accepted Answer

le. Option B (le) is correct because it is the standard label Prometheus attaches to histogram bucket series to indicate the inclusive upper bound of each bucket (e.g., le="0.5"), and it is essential for histogram_quantile() calculations. Option D (job) is correct because Prometheus automatically adds a job label to every scraped target, derived from the scrape configuration's job_name, identifying the logical service or scrape group. Option E (instance) is correct because Prometheus automatically attaches an instance label representing the specific target endpoint (host:port) that was scraped, distinguishing individual replicas within a job. Options A (group) and C (owner) are not part of the default Prometheus ecosystem labels; they are not injected by Prometheus during scraping and are not standard conventions used by PromQL functions or service discovery metadata.

Answer

group

Answer

owner

Question 13

Which THREE of the following are components of a Prometheus alert state?

Accepted Answer

inactive. In Prometheus, an alert rule transitions through three defined states: B. inactive, meaning the alert's expression evaluates to false and no alert is active; D. pending, meaning the expression has become true but the alert has not yet been true for the configured 'for' duration; and C. firing, meaning the condition has remained true for the full 'for' duration and the alert is now actively firing and sent to Alertmanager. These three states (inactive, pending, firing) are the complete set of alert states tracked by the Prometheus alerting engine. The unmarked options A. muted and E. sleeping are not Prometheus alert states; muting is an Alertmanager concept (silences/mute timers) applied to notifications, and 'sleeping' is not a Prometheus alert state at all.

Answer

muted

Answer

sleeping

Question 14

Which TWO are common types of Prometheus exporters?

Accepted Answer

Node Exporter. Node Exporter (A) is a canonical Prometheus exporter that runs on a host and exposes hardware and OS metrics such as CPU, memory, disk, filesystem, and network statistics on /metrics for Prometheus to scrape. Blackbox Exporter (D) is also a standard Prometheus exporter, but it probes external endpoints over HTTP, HTTPS, DNS, TCP, and ICMP and converts the results into Prometheus metrics, making it ideal for availability and latency monitoring. The other options are not established Prometheus exporter types: there is no standard "Log Exporter" (B) since logs are handled by Loki/Promtail rather than Prometheus, "Push Exporter" (C) is not a real exporter type because Prometheus uses the Pushgateway for push-based metrics rather than a push exporter, and "Trace Exporter" (E) relates to distributed tracing systems like OpenTelemetry/Jaeger, not Prometheus metrics collection.

Answer

Log Exporter

Answer

Push Exporter

Answer

Trace Exporter

Question 15

Which TWO of the following are valid Alertmanager configuration blocks?

Accepted Answer

route. Option A, route, is a valid top-level Alertmanager configuration block that defines the routing tree, specifying how alerts are grouped, matched, and dispatched to receivers. Option B, receivers, is also a valid top-level Alertmanager block that lists named notification integrations (such as email, Slack, or PagerDuty) that routes can reference. Options C (scrape_configs), D (targets), and E (rules) are not Alertmanager configuration blocks: scrape_configs and targets belong to Prometheus's scrape configuration, and rules is a Prometheus/recording-and-alerting rule file concept, not an Alertmanager config block.

Answer

scrape_configs

Answer

targets

Answer

rules

Question 16

Which THREE of the following are considered part of the 'Four Golden Signals' of monitoring?

Accepted Answer

Errors. The four golden signals are Latency, Traffic, Errors, and Saturation.

Answer

Disk Space

Answer

Up-time

Question 17

Which TWO of the following are valid data types returned by PromQL queries? (Choose two)

Accepted Answer

Range vector. PromQL, the query language used by Prometheus, defines exactly four expression data types: instant vector, range vector, scalar, and string. Option B (Range vector) is correct because a range vector is a set of time series containing a range of data points over time for each series, produced by appending a duration selector like [5m] to a selector (e.g., http_requests_total[5m]). Option D (Instant vector) is correct because it is the most common PromQL result type: a set of time series containing a single sample for each series at a given timestamp, returned by expressions such as http_requests_total. The unmarked options do not belong: 'Histogram matrix' (A) is not a PromQL type—histograms are exposed as instant or range vectors of bucket series, and 'matrix' is not a PromQL data type name; 'Log stream' (C) is a Loki concept, not PromQL; and 'Distributed trace' (E) is a tracing data type (e.g., from Tempo/Jaeger), not a PromQL return type.

Answer

Histogram matrix

Answer

Log stream

Answer

Distributed trace

Question 18

Which TWO of the following are valid data types in Prometheus?

Accepted Answer

Gauge. In Prometheus, the four core metric types are Counter, Gauge, Histogram, and Summary, so option B (Gauge) is correct because a gauge represents a value that can arbitrarily go up and down, such as temperature or current memory usage, and option C (Counter) is correct because a counter is a cumulative metric that only increases (or resets to zero on restart), such as total HTTP requests. These types are defined in the Prometheus client libraries and exposed via the text exposition format with TYPE annotations like 'counter' and 'gauge'. The other options are not Prometheus metric types: List (A) and Set (D) are not part of the Prometheus data model, and Boolean (E) is not a native metric type either, since boolean-like states are typically represented using a Gauge with values 0 or 1.

Answer

List

Answer

Set

Answer

Boolean

Question 19

Which THREE are true regarding the Prometheus TSDB?

Accepted Answer

It uses an inverted index for fast searching.. It uses blocks, WAL, and index files, and it is optimized for time-series data.

Answer

It uses a B-tree for all queries.

Answer

It is a relational database.

Question 20

Which TWO of the following are valid ways to run Prometheus?

Accepted Answer

As a container. Option B is correct because Prometheus is commonly deployed as a container (e.g., the official prom/prometheus Docker image) running its server process in an isolated environment. Option C is correct because Prometheus ships as a standalone compiled Go binary that can be downloaded and executed directly on a host without any container runtime. Option A is wrong because Prometheus is a server-side monitoring system, not a browser extension. Option D is wrong because Prometheus is a standalone time-series database and monitoring server, not a library embedded into a database engine. Option E is wrong because Prometheus runs entirely in user space and is never implemented as a kernel module.

Answer

As a browser extension

Answer

As a database engine library

Answer

As a kernel module