Уровень 0 · материалов: 4
В кластер входят руководства по внедрению и настройке стеков мониторинга на базе Prometheus и Grafana, но не входят общие обзоры ИТ-инфраструктуры без привязки к конкретным инструментам сбора и визуализации метрик.
Общие признаки: настройка систем мониторинга, использование Prometheus, визуализация данных в Grafana, инструменты сбора метрик, построение дашбордов
Группа выше: Системы мониторинга
Смысл: The main idea is to educate readers on the fundamentals of IT monitoring and provide a practical, step-by-step implementation guide for a modern monitoring stack based on Prometheus, Grafana, and VictoriaMetrics.
A comprehensive guide covering the history of IT monitoring and a practical technical tutorial on deploying the Prometheus, Alertmanager, VictoriaMetrics, and Grafana (PAVG) stack using Docker.
Смысл: The text serves as a practical introduction to building a basic server monitoring system. It explains how to integrate Node Exporter for metric collection, Prometheus for data storage and querying, and Grafana for visual representation.
A beginner's guide to setting up a server monitoring system using Node Exporter for metrics, Prometheus for storage, and Grafana for visualization.
Смысл: The text serves as a practical guide for engineers on how to implement effective monitoring and observability using Grafana and Prometheus. It emphasizes the transition from simply 'having graphs' to creating purposeful, high-performance dashboards that accelerate incident resolution.
A pragmatic guide to building efficient Grafana dashboards and managing Prometheus metrics, focusing on usability, performance, and purposeful design.
Смысл: The main idea is to guide developers and sysadmins through the transition from basic, single-server monitoring (like Munin) to a scalable, modern monitoring architecture (TIG stack) using Time Series Databases and flexible visualization tools.
A comprehensive guide on replacing the outdated Munin monitoring system with the modern Telegraf-InfluxDB-Grafana (TIG) stack for better scalability and visualization.