Prometheus

1. Overview and Architecture

   Pull-based monitoring, server, exporters, Alertmanager, and time series storage.

2. Data Model

   Time series, metric names, labels, samples, and label cardinality.

3. Metric Types

   Counters, gauges, histograms, and summaries.

4. Jobs and Instances

   Scrape targets, job and instance labels, and the up metric.

5. Configuration and Scraping

   scrape_configs, service discovery, relabeling, scrape intervals, and global settings.

6. PromQL Basics

   Instant and range vectors, selectors, label matchers, offsets, and subqueries.

7. PromQL Operators and Functions

   Aggregation operators, rate, increase, histogram_quantile, vector matching, and binary operators.

8. Recording Rules

   Precomputing expensive queries and naming conventions for rules.

9. Alerting Rules

   Alert expressions, for durations, labels, annotations, and templating.

10. Alertmanager

    Routing, grouping, inhibition, silences, and receivers.

11. Exporters

    node_exporter, third-party exporters, and the exposition format.

12. Client Libraries and Instrumentation

    Instrumenting applications, exposing /metrics, and best practices for what to measure.

13. Naming and Histogram Practices

    Metric and label naming conventions, base units, and histogram vs summary choice.

14. Storage

    Local TSDB, retention, WAL, compaction, and remote read/write.

15. Federation and Remote Write

    Scaling with federation and long-term storage via remote write.

16. Pushgateway

    Short-lived batch jobs and when to push vs pull.

Each section links to the official page. Titles and summaries by Extra Credit; the docs belong to their authors.