Prometheus Certified Associate (PCA)
Demonstrate foundational proficiency in Prometheus monitoring, metrics collection, time-series data models, PromQL query language, Alertmanager notifications, and dashboard visualization.
Official Exam Specification & Quick Facts
Question Difficulty Breakdown
Exam Guidelines & Simulation Rules
Frequently Asked Questions (FAQ)
The PCA is an entry-level, multiple-choice certification created by the CNCF and Linux Foundation validating foundational knowledge of Prometheus monitoring, time-series data, and observability.
The PCA is a 90-minute multiple-choice examination consisting of 60 questions administered online with remote proctoring.
A passing scaled score of 75% is required. Results are displayed immediately upon submission.
Domains include: (1) Observability Concepts (18%), (2) Prometheus Fundamentals (20%), (3) PromQL (28%), (4) Alerting and Dashboarding (16%), and (5) Storage and Operations (18%).
Counter (cumulative monotonic increasing value), Gauge (value that can go up and down), Histogram (samples observations in configurable buckets), and Summary (samples observations and calculates quantiles).
Prometheus utilizes a pull-based model, periodically scraping HTTP endpoints (typically /metrics) exposed by target applications or exporters according to scrape_interval configurations.
PromQL is a functional query language designed for evaluating multidimensional time-series data, supporting instant vectors, range vectors, aggregations (sum, avg, count), and rate calculations.
rate() calculates the per-second average rate of increase of a counter over a specified time window, ideal for alerting. irate() calculates the instant rate based on the last two data points, ideal for volatile graphs.
Alertmanager deduplicates, groups, routes, silences, and throttles alerts received from Prometheus servers before sending notifications via email, Slack, PagerDuty, or webhooks.
An exporter (e.g. Node Exporter, Blackbox Exporter, MySQL Exporter) is a proxy that fetches telemetry from non-Prometheus systems and exposes it as Prometheus-formatted metrics.
Prometheus uses a custom time-series database (TSDB) that groups samples into 2-hour blocks consisting of chunks (compressed time-series), an index, metadata, and a Write-Ahead Log (WAL) to prevent data loss.
Recording rules pre-compute frequently needed or computationally expensive expressions and save their results as new time series. Alerting rules evaluate PromQL conditions and fire alerts to Alertmanager when true.