PCA Practice Test 14 — 15 Questions

Question 1

When should you use the 'absent()' function?

Accepted Answer

To alert when a metric has no data points in a given range.. absent() returns a time series if the input vector is empty, useful for alerting on missing metrics.

Answer

To reset a counter.

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To ignore null values in a calculation.

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To handle missing labels in a join.

Question 2

What happens to your alerts if the Alertmanager configuration file contains a syntax error?

Accepted Answer

Alertmanager continues using the previous configuration. If the configuration is invalid, Alertmanager will fail to reload, and it will continue using the last known good configuration.

Answer

Prometheus stops scraping

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Alertmanager crashes immediately

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All alerts are dropped

Question 3

You are deploying Prometheus in a cluster with highly dynamic ephemeral pods. Which concern is the most significant regarding cardinality?

Accepted Answer

The memory overhead of storing time series with unique label sets.. Cardinality in Prometheus is driven by the number of unique label combinations, and each unique time series consumes memory in the head block (in-memory TSDB) regardless of scrape frequency. Ephemeral pods with dynamic labels (pod UID, container ID, ephemeral IPs) create a churn of new series that accumulate in memory, causing OOM kills and slow queries. This memory overhead is the dominant concern.

Answer

The network bandwidth used by the pushgateway.

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The disk space used by WAL logs.

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The number of targets being scraped.

Question 4

When evaluating the 'Traffic' golden signal, what is the best metric to watch for a web service?

Accepted Answer

Requests per second.. Request rate (requests per second) is the standard way to measure traffic volume.

Answer

CPU usage percentage.

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HTTP error count.

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Response latency.

Question 5

You are designing a monitoring architecture for an ephemeral, auto-scaling microservices environment. Why is the Prometheus 'pull' model generally preferred over a 'push' model in this scenario?

Accepted Answer

Pull models enable automatic service discovery and health management via the Prometheus server.. Prometheus's pull model lets the server discover targets dynamically (via Kubernetes SD, Consul, EC2 SD, etc.) and scrape them on a schedule, so ephemeral pods that appear and disappear are picked up automatically. It also gives the server a built-in health signal: if a target fails to respond to a scrape, Prometheus marks it down via the 'up' metric, providing liveness monitoring for free.

Answer

Pull models eliminate the need for firewall configuration.

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Pull models reduce network latency on the monitored targets.

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Push models require a Prometheus Pushgateway for every single target.

Question 6

Which tool would you pair with Prometheus to visualize the collected data?

Accepted Answer

Grafana. Grafana is the standard visualization tool paired with Prometheus. It connects to Prometheus as a data source and allows users to create dashboards, graphs, and alerts based on Prometheus metrics. Grafana's native support for PromQL and its rich visualization capabilities make it the go-to choice for visualizing Prometheus data.

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Kibana

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PromQL

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Alertmanager

Question 7

Which of these is considered a 'counter' in Prometheus?

Accepted Answer

Total number of HTTP requests processed.. A counter in Prometheus is a cumulative metric that only increases (or resets to zero on process restart), and 'total number of HTTP requests processed' is the canonical example — it monotonically grows and is typically queried with rate() or increase(). Counters are used to compute rates of events over time.

Answer

Temperature of a server room.

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Average latency over 5 minutes.

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Current memory usage of a process.

Question 8

What is the primary benefit of using a pull-based model for monitoring?

Accepted Answer

The Prometheus server can detect target failure.. The primary benefit of a pull-based model for monitoring is that the Prometheus server can detect target failure. In a pull model, the monitoring server periodically scrapes metrics from targets; if a target fails to respond, the server can immediately detect that failure and trigger alerts. This is a key advantage over push-based models where the absence of data might not be noticed as quickly.

Answer

It supports higher data throughput.

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It is easier to configure for firewalls.

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It avoids network security issues.

Question 9

Which TWO of these are potential side effects of high-cardinality metrics?

Accepted Answer

High memory consumption on the Prometheus server.. Memory exhaustion (OOM) and slow query performance are the direct results of high cardinality.

Answer

Reduced CPU usage on target.

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Faster alert evaluation.

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Decreased network bandwidth.

Question 10

You need to measure the P99 latency of your service. Which PromQL function do you use on a Histogram?

Accepted Answer

histogram_quantile(). histogram_quantile() is the correct PromQL function to compute quantiles (like P99) from a histogram metric. It takes a φ (phi) value between 0 and 1 and a histogram bucket series, then interpolates the quantile from the cumulative bucket counts. For P99, you would use histogram_quantile(0.99, ...). This function is specifically designed for Prometheus histograms, which expose _bucket time series with an le label.

Answer

avg()

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sum()

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rate()

Question 11

What is the benefit of the 'service discovery' feature in Prometheus?

Accepted Answer

It simplifies management in dynamic environments.. Prometheus service discovery automatically detects and updates scrape targets from dynamic sources such as Kubernetes, EC2, Consul, or DNS. In environments where instances are constantly created and destroyed, this eliminates manual target configuration and keeps monitoring in sync with the actual infrastructure. The primary benefit is simplified management in dynamic environments.

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It improves query performance.

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It encrypts the data.

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It reduces the storage size.

Question 12

Which operator performs a set union in PromQL?

Accepted Answer

or. In PromQL, the `or` operator performs a set union between two instant vectors, returning all series from the left-hand side plus any series from the right-hand side that do not already match on the label set. This is the PromQL equivalent of a SQL UNION, used to combine metrics from different sources into a single result set. The other logical operators (`and`, `unless`) perform intersection and set subtraction, not union.

Answer

unless

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join

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and

Question 13

Your Prometheus server is hitting high memory usage due to high cardinality. Which action is most effective at reducing memory pressure?

Accepted Answer

Drop high-cardinality labels using relabel_configs. Reducing label cardinality (e.g., removing unique user IDs) is the primary way to reduce TSDB index size and memory usage.

Answer

Increase scrape_interval

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Use more exporters

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Enable remote write

Question 14

Which of the following best describes the function of the 'continue: true' setting within an Alertmanager route?

Accepted Answer

It allows an alert to continue matching against sibling routes. Setting 'continue: true' allows an alert to match multiple routes, ensuring it can be sent to multiple destinations if desired.

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It enables alert silencing

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It allows the Alertmanager to retry failed notifications

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It causes the alert to stay active indefinitely

Question 15

Which THREE of the following are standard ways to send notifications from Alertmanager?

Accepted Answer

Webhook. Webhook, Email, and PagerDuty are built-in, widely used receiver types.

Answer

FTP

Answer

SSH