PCA Practice Exam 2 — 20 Questions

Question 1

In Alertmanager, what is the role of the 'continue' field in a route?

Accepted Answer

To force the alert to be sent to multiple routes. The 'continue' field in an Alertmanager route, when set to true, allows the alert to continue matching subsequent sibling routes. This means the alert can be sent to multiple receivers, effectively forcing it to be routed to multiple destinations.

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To keep the alert firing after resolution

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To ignore duplicate alerts

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To restart the Alertmanager process

Question 2

You need to monitor the availability of a specific web endpoint from external locations using blackbox_exporter. What is the primary purpose of the 'module' configuration in blackbox_exporter?

Accepted Answer

To define the protocol-specific behavior and parameters for the probe.. In blackbox_exporter, a module defines the protocol-specific behavior and parameters for a probe, such as HTTP, TCP, ICMP, or DNS. It specifies details like the HTTP method, headers, expected status codes, timeouts, and TLS settings. This allows the exporter to perform customized checks for different types of endpoints.

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To specify the IP address of the target server.

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To manage the authentication credentials for the exporter process.

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To automatically register the exporter with the Prometheus server.

Question 3

What is the purpose of the instant vector selector syntax http_requests_total{job="api-server"}?

Accepted Answer

It selects current values of time series matching the metric name and label filter.. The instant vector selector http_requests_total{job="api-server"} returns the most recent sample value for every time series whose metric name is http_requests_total and whose job label equals 'api-server'. It is evaluated at a single point in time (the query evaluation timestamp), producing one value per matching series rather than a range of samples. This is the fundamental building block for PromQL queries that feed into functions like rate(), sum(), or comparison operators.

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It aggregates all API server requests into a single sum.

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It triggers an alert if the job is down.

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It selects historical data points spanning the last hour for the matching series.

Question 4

What is the purpose of 'labels' in Prometheus?

Accepted Answer

To identify unique time series.. Labels provide metadata to metrics, allowing for multi-dimensional querying and filtering (e.g., job='web', instance='1.2.3.4').

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To store the actual data values.

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To define the scrape interval.

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To set the alert threshold.

Question 5

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

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Automatically increasing retention

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Providing UI for alerts

Question 6

Which function is best suited for identifying the 'top 5' instances with the highest value for a specific metric?

Accepted Answer

topk(5, metric). topk(5, metric) is the PromQL aggregation operator that returns the 5 time series with the highest instantaneous values for the given metric, which is exactly what is needed to identify the top 5 instances. It operates as an aggregation over the sample set at each evaluation step, preserving the labels of the winning series so you can see which instance is which. This is the canonical way to build 'top N' dashboards or alerts in Prometheus.

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sort_desc()

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max_over_time()

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limit_rate(5, metric)

Question 7

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.

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The =~ operator is used exclusively for numeric comparisons.

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

Question 8

Which component allows Prometheus to be scaled horizontally for high availability?

Accepted Answer

Running identical instances in parallel. Prometheus is a single-node, stateful system with no built-in clustering, so horizontal scaling for high availability is achieved by running two or more identical Prometheus instances scraping the same targets in parallel. Each instance maintains its own TSDB, and queries can be deduplicated or load-balanced across them.

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Using a Load Balancer

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Pushgateway

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Prometheus Operator

Question 9

An engineer observes a massive spike in Prometheus memory usage after introducing a new custom label that includes a unique user ID. Which observability concept is being violated?

Accepted Answer

High cardinality. High cardinality occurs when a label has a large number of unique values, such as a unique user ID, which creates a massive number of time series. This leads to increased memory usage, slower queries, and potential instability in Prometheus. The spike in memory usage directly indicates that the cardinality of the metric has exploded due to the new label.

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Data retention policy

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Metric saturation

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Service discovery limits

Question 10

A developer wants to expose a metric that represents the current memory usage of a process. Which type is most appropriate?

Accepted Answer

Gauge. A Gauge is the correct metric type because it represents a value that can arbitrarily go up or down over time, such as current memory usage, CPU load, or temperature. Prometheus gauges expose instantaneous snapshots via Set(), Inc(), and Dec() operations, making them ideal for measuring fluctuating resource consumption. Memory usage is not cumulative and can decrease when a process releases memory, which rules out Counter.

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Counter

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Summary

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Histogram

Question 11

A developer adds a 'user_id' label to an HTTP request counter. What is the operational risk?

Accepted Answer

High cardinality will consume excessive memory.. Adding a 'user_id' label to an HTTP request counter creates a label with unbounded, per-user values. Each unique combination of label values produces a distinct time series in Prometheus, so a user_id label can generate thousands or millions of series. Prometheus holds all active series in memory (head block), so this high cardinality rapidly consumes RAM and can destabilize or crash the server.

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The query speed will increase.

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Prometheus will reject the metric.

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The metric will stop recording.

Question 12

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.

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Use metrics for everything.

Question 13

Why would you choose to create a recording rule for a complex PromQL query?

Accepted Answer

To reduce dashboard query latency. Recording rules pre-calculate complex queries, making dashboards load faster by querying the pre-computed series instead of re-calculating the entire expression.

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To increase metric resolution

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To bypass authentication

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To enable cross-server alerting

Question 14

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).

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alertmanager_host

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storage_path

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target_labels

Question 15

When evaluating a PromQL query involving arithmetic operators, such as 'vector1 + vector2 * vector3', which operator has the highest precedence?

Accepted Answer

* (Multiplication). In PromQL, arithmetic operators follow standard mathematical precedence: multiplication (*), division (/), and modulo (%) bind tighter than addition (+) and subtraction (-). Therefore in 'vector1 + vector2 * vector3', the multiplication of vector2 and vector3 is evaluated first, and the result is then added to vector1. This mirrors conventional arithmetic rules rather than left-to-right evaluation.

Answer

Both have equal precedence and are evaluated left-to-right.

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+ (Addition)

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Precedence is determined by the order of labels.

Question 16

When using 'irate', what is the impact of choosing a range vector that is too small (e.g., [10s])?

Accepted Answer

It captures high-frequency spikes but can be volatile.. Using a very small range vector with irate, such as [10s], means irate calculates the per-second rate based on only the last two data points within that short window. This can capture rapid changes but makes the result highly sensitive to scrape timing and outliers, leading to volatile output.

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It returns an error if no data points are found.

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The result becomes a scalar.

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The value is capped at 1.

Question 17

When using the Pushgateway, what happens if you push a metric with the same name and labels as an existing one?

Accepted Answer

It overwrites the old value. The Pushgateway overwrites the existing metric with the new value provided in the push request.

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It creates a new series

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It rejects the push

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It adds to the existing value

Question 18

When designing a monitoring strategy, why should you avoid monitoring 'everything'?

Accepted Answer

It leads to signal noise and high resource costs.. Excessive metric collection leads to high storage costs, increased query latency, and signal-to-noise ratio degradation (alert fatigue).

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Logs are always better for everything.

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The network will be saturated.

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Prometheus cannot handle many metrics.

Question 19

You are creating a recording rule to calculate the rate of requests over 5 minutes. Why would you prefer a recording rule over a direct dashboard query?

Accepted Answer

To reduce query latency on dashboards. Recording rules precompute expensive queries, reducing the load on Prometheus and speeding up dashboard loading times.

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To bypass the retention settings of Prometheus

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To increase the resolution of the data

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To automatically send alerts to PagerDuty

Question 20

When configuring Alertmanager to send notifications to Slack, which block defines the routing tree?

Accepted Answer

route. In Alertmanager's configuration, the route block defines the routing tree that determines how alerts are grouped and which receiver they are sent to. It is the top-level entry point (with child routes for matching) that evaluates alert labels against matchers and dispatches notifications accordingly.

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receivers

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inhibit_rules

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global