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[General] PCA Exam Topics Pdf | PCA Latest Practice Questions

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【General】 PCA Exam Topics Pdf | PCA Latest Practice Questions

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Linux Foundation Prometheus Certified Associate Exam Sample Questions (Q55-Q60):NEW QUESTION # 55
What is the minimum requirement for an application to expose Prometheus metrics?
  • A. It must run on Linux.
  • B. It must be compiled for 64-bit architectures.
  • C. It must be able to serve text over HTTP.
  • D. It must be exposed to the Internet.
Answer: C
Explanation:
Prometheus collects metrics by scraping an HTTP endpoint exposed by the target application. Therefore, the only essential requirement for an application to expose metrics to Prometheus is that it serves metrics in the Prometheus text exposition format over HTTP.
This endpoint is conventionally available at /metrics and provides metrics in plain text format (e.g., Content-Type: text/plain; version=0.0.4). The application can run on any operating system, architecture, or network - as long as Prometheus can reach its endpoint.
It does not need to be Internet-accessible (it can be internal) and is not limited to Linux or any specific bitness.
Reference:
Verified from Prometheus documentation - Exposition Formats, Instrumenting Applications, and Target Scraping Requirements sections.

NEW QUESTION # 56
If the vector selector foo[5m] contains 1 1 NaN, what would max_over_time(foo[5m]) return?
  • A. No answer.
  • B. It errors out.
  • C. 0
  • D. NaN
Answer: C
Explanation:
In PromQL, range vector functions like max_over_time() compute an aggregate value (in this case, the maximum) over all samples within a specified time range. The function ignores NaN (Not-a-Number) values when computing the result.
Given the range vector foo[5m] containing samples [1, 1, NaN], the maximum value among the valid numeric samples is 1. Therefore, max_over_time(foo[5m]) returns 1.
Prometheus functions handle missing or invalid data points gracefully-ignoring NaN ensures stable calculations even when intermittent collection issues or resets occur. The function only errors if the selector is syntactically invalid or if no numeric samples exist at all.
Reference:
Verified from Prometheus documentation - PromQL Range Vector Functions, Aggregation Over Time Functions, and Handling NaN Values in PromQL sections.

NEW QUESTION # 57
What does the evaluation_interval parameter in the Prometheus configuration control?
  • A. How often Prometheus evaluates recording and alerting rules.
  • B. How often Prometheus compacts the TSDB data blocks.
  • C. How often Prometheus sends metrics to remote storage.
  • D. How often Prometheus scrapes targets.
Answer: A
Explanation:
The evaluation_interval parameter defines how frequently Prometheus evaluates its recording and alerting rules. It determines the schedule at which the rule engine runs, checking whether alert conditions are met and generating new time series for recording rules.
For example, setting:
global:
evaluation_interval: 30s
means Prometheus evaluates all configured rules every 30 seconds. This setting differs from scrape_interval, which controls how often Prometheus collects data from targets.
Having a proper evaluation interval ensures alerting latency is balanced with system performance.

NEW QUESTION # 58
Which of the following signal belongs to symptom-based alerting?
  • A. CPU usage
  • B. Database memory utilization
  • C. API latency
  • D. Disk space
Answer: C
Explanation:
Symptom-based alerting focuses on user-visible problems or service-impacting symptoms rather than low-level resource metrics. In Prometheus and Site Reliability Engineering (SRE) practices, alerts should signal conditions that affect users' experience - such as high latency, request failures, or service unavailability - instead of merely reflecting internal resource states.
Among the options, API latency directly represents the performance perceived by end users. If API response times increase, it immediately impacts user satisfaction and indicates a possible service degradation.
In contrast, metrics like disk space, CPU usage, or database memory utilization are cause-based metrics - they may correlate with problems but do not always translate into observable user impact.
Prometheus alerting best practices recommend alerting on symptoms (via RED metrics - Rate, Errors, Duration) while using cause-based metrics for deeper investigation and diagnosis, not for immediate paging alerts.
Reference:
Verified from Prometheus documentation - Alerting Best Practices, Symptom vs. Cause Alerting, and RED/USE Monitoring Principles sections.

NEW QUESTION # 59
Which Alertmanager feature allows you to temporarily stop notifications for a specific alert?
  • A. Grouping
  • B. Silence
  • C. Deduplication
  • D. Inhibition
Answer: B
Explanation:
The Silence feature in Alertmanager allows operators to mute specific alerts for a defined period. Each silence includes a matcher (labels), a creator, a comment, and an expiration time.
Silencing is useful during maintenance windows or known outages to prevent alert noise. Unlike inhibition, silences are manual and explicit.

NEW QUESTION # 60
......
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