Prometheus / Intermediate: PromQL and rule contracts

Prometheus β€” Intermediate: PromQL and rule contracts

Build compatible aggregation, matching, classic histograms, recording rules, alerts, and relabeling designs.

6 lessons Β· No account required

What you will learn

  • Review grouping and matching from a population contract.
  • Design derived series and alerts with explicit timing and identity.

  1. Aggregation and meaningful error ratios

    Use grouping and weighted counts to derive a service ratio while preserving eligibility, units, and the distinction between absent series and measured zero.

    Start learning

  2. Vector matching and metadata enrichment

    Explain how binary operations pair series by labels, and review uniqueness before adding group modifiers or metadata to a query.

    Start learning

  3. Classic histograms and quantile estimates

    Read cumulative bucket series, preserve le during aggregation, and distinguish directly counted threshold fractions from interpolated quantile estimates.

    Start learning

  4. Recording rules and derived series contracts

    Design a recording rule as a versioned materialized measurement with explicit grouping, evaluation cadence, dependencies, and consumer expectations.

    Start learning

  5. Alert rules and state lifecycles

    Read alert activation as vector membership, distinguish pending from firing, and keep stable identity, descriptions, and notification delivery as separate concerns.

    Start learning

  6. Discovery and relabeling stages

    Distinguish target selection before scraping from metric relabeling after collection, and review internal labels, identity changes, and dropped evidence deliberately.

    Start learning
Back to course