Prometheus supports four core metric types—gauge, counter, summary, and histogram—each with distinct semantics and usage patterns; this guide explains their definitions, how to update them via client libraries, and how they appear in the Prometheus text exposition format, including example code and query tips.
This tutorial introduces five non‑traditional Plotly visualization techniques—animation, sunburst, parallel categories, parallel coordinates, and gauge/indicator charts—showing how to create dynamic, interactive, and aesthetically appealing graphics that enhance data storytelling and communication.
This tutorial demonstrates how to create a simple Go application, expose the default Prometheus metrics endpoint, add custom gauge metrics, use a custom registry, and work with counters, histograms, summaries, and label vectors to fully instrument Go services for monitoring.
This article explains Prometheus data collection by describing metric syntax, label usage, time‑series concepts, the four logical metric types (Counter, Gauge, Histogram, Summary), and provides practical naming, labeling, and selection guidelines for effective monitoring.
This article explains the four core Prometheus metric types—Counter, Gauge, Histogram, and Summary—detailing their characteristics, appropriate use cases, PromQL functions, and how they differ, while providing language-specific client library references and visual examples.
