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所在平台: Udemy |
课程主页: https://www.udemy.com/course/grafana-prometheus-loki-alloy-tempo/
课程评论：没有评论
课程名称：使用Grafana、Prometheus、Loki、Alloy与Tempo进行可观察性 课程概述： 本课程旨在帮助学员深入掌握Grafana堆栈的可观察性，包括使用Grafana Loki进行日志管理、使用Grafana Tempo进行分布式追踪、使用Grafana Alloy构建遥测管道、使用OpenTelemetry收集和输出应用程序信号，以及使用Grafana Mimir进行大规模企业级指标收集。我们提供一条全面且实践导向的路径，助您建立现代可观察性系统。 课程内容从Prometheus的指标开始，逐步深入到日志、追踪、警报以及Grafana中的自定义仪表板。课程将首先介绍可观察性的核心概念、遥测数据及指标收集方法。接下来，您将学习如何专业地安装、配置和使用Prometheus。 随后，您将学习在Windows、macOS、Linux（包括Ubuntu和Amazon Linux）及Docker上部署Grafana，并探索真实案例的Grafana仪表板设计，涵盖API、基础设施和微服务。在日志部分，您将与Grafana Loki合作，获取和可视化日志数据，包括从非结构化日志中动态提取标签。 课程将深入探讨OpenTelemetry的基本原理，以及如何设置Grafana Alloy来接收、处理和导出OTel指标与追踪。您将使用Python和C#对微服务进行工具化，并将信号导出到Grafana Tempo，分析服务调用并使用TraceQL追踪服务图。 课程还包括Grafana Mimir，这是一种高度可扩展的时序数据库，用于大规模存储指标。您将学习Mimir的工作原理，以及如何在单体模式下和Kubernetes中的微服务模式下本地部署它。 为了增加实践经验，课程基于一个虚构的在线零售商ShoeHub，提供模拟数据、仪表板、警报和仿真真实的可观察性用例的服务。课程没有复杂的环境配置，您将获得由Killer Coda提供的浏览器基础的练习平台的即时访问权限，可以直接开始实验，无需安装任何东西。 课程包含： - Prometheus、Grafana、Loki、Alloy、Tempo、Mimir的Docker Compose文件、ShoeHub指标和示例微服务追踪。 - 示例仪表板和面板配置。 - 用Python编写的日志生成器脚本。 - 多平台的设置指南。 - ShoeHub及示例微服务的可执行二进制文件（如果您不想使用Docker）。 - 可选的云实验室环境（Killer Coda），提供即时实践体验。 如有任何问题或疑问，您可以通过Udemy问答系统及时与我联系。祝您学习愉快，欢迎来到可观察性世界！
Master observability with the Grafana Stack, including Grafana Loki for logs, Grafana Tempo for distributed tracing, Grafana Alloy for telemetry pipelines, OpenTelemetry (OTel) for collecting and exporting signals from your applications, and Grafana Mimir for large-scale enterprise metrics collection.This course provides a comprehensive, hands-on path to building modern observability systems. It starts with metrics using Prometheus and progresses to logs, traces, alerting, and custom dashboards in Grafana.We begin with the core concepts of observability, telemetry data, and methods for metric collection. Then, you'll dive into Prometheus - learning how to install, configure, and use it like a pro.Next, you'll deploy Grafana across Windows, macOS, Linux (including Ubuntu and Amazon Linux), and Docker. Once your stack runs, we cover Grafana dashboard design for real-world use cases: APIs, infrastructure, and microservices.In the logging section, you'll work with Grafana Loki to ingest and visualise logs, including dynamic label extraction from unstructured logs.Then we go deeper: you'll learn the fundamentals of OpenTelemetry and set up Grafana Alloy to receive, process, and export OTel metrics and traces. You'll instrument microservices (in Python and C#) and export signals to Grafana Tempo, where you'll trace distributed calls and analyze service graphs with TraceQL.Now also included is Grafana Mimir, a highly scalable time-series database for storing metrics at scale. You'll learn what Mimir is, how it works, and how to deploy it locally in monolithic mode and microservices mode into Kubernetes.To make it practical, the course is based on a fictional online retailer, ShoeHub, with mock data, dashboards, alerts, and services that simulate real-world observability use cases.No setup headaches - you'll also get instant access to a browser-based playground powered by Killer Coda, so you can start experimenting without installing anything.Included in the course:Docker Compose files for Prometheus, Grafana, Loki, Alloy, Tempo, Mimir, ShoHub metrics, and Example Microservices Tracing.Sample dashboards and panel configurations.Log generator script in Python.Set up guides for multiple platforms.Binary executable files for ShoeHub and the example microservices (if you don't want to use Docker).Optional cloud lab environment (Killer Coda) for instant hands-on practice.I will respond promptly via the Udemy Q & A system if you encounter any issues or have questions.Happy learning - and welcome to the world of observability!
