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PCA Observability Concepts Practice Question

An application is emitting logs that contain '5xx' status codes when a service is unavailable. If you want to create an alert that triggers based on the rate of these errors, what is the best practice for observability?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Expose a metric incrementing on every 5xx error and alert on the rate of that metric.

Logs are useful for root cause analysis, but for alerting on rates, you should convert the error occurrence into a metric increment, as metrics are more efficient for long-term calculation and alerting.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Expose a metric incrementing on every 5xx error and alert on the rate of that metric.

    Why this is correct

    Converting log events to metrics provides a reliable, performant signal for alerting.

  • Alert directly on the log stream using a log aggregator.

    Why it's wrong here

    Alerting on raw log volume is inefficient and prone to false positives compared to metrics.

  • Use Prometheus to scrape the log file directly.

    Why it's wrong here

    Prometheus is not designed to parse and scrape raw flat-file logs.

  • Increase log verbosity to trace the request until the error is resolved.

    Why it's wrong here

    This does not provide a mechanism for automated alerting.

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JA

Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official CNCF / Linux Foundation exam blueprint

This PCA practice question is part of Courseiva's free CNCF / Linux Foundation certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PCA exam.