Announcement
Observability Zero to Hero: Learn Metrics, Logs, and Traces
A comprehensive, hands-on guide and repository to learn modern application observability from scratch ('zero to hero'), covering metrics, logging, and tracing with popular open-source tools like Prometheus, Grafana, ELK, and Jaeger/Tempo.
Project Introduction
Summary
This project serves as an educational resource and practical toolkit for anyone looking to master application observability using prominent open-source technologies. It guides users from basic principles to implementing sophisticated monitoring and tracing solutions.
Problem Solved
Learning application observability can be daunting due to the wide array of tools and concepts. This project provides a structured path with practical examples to bridge the gap between theory and practice.
Core Features
Hands-on Labs & Examples
Includes practical, step-by-step tutorials and code examples for setting up and configuring observability tools.
Core Concepts Explanation
Covers the fundamental concepts of metrics, logs, and traces and how they contribute to effective monitoring and debugging.
Real-world Integration Examples
Provides examples integrating observability tools with modern application architectures, including microservices.
Tech Stack
Use Cases
This repository is primarily an educational resource, but the patterns and examples demonstrated can be applied to various real-world scenarios:
Scenario 1: Implementing Application Metrics Collection
Details
Learn how to set up Prometheus and Grafana to collect and visualize custom application metrics.
User Value
Enables developers to track application health and performance indicators.
Scenario 2: Centralized Logging and Analysis
Details
Understand how to configure log aggregation using the ELK stack or Grafana's Loki for centralized log analysis.
User Value
Facilitates faster debugging and root cause analysis by having all logs in one place.
Scenario 3: Distributed Tracing for Microservices
Details
Explore how to instrument applications for distributed tracing using Jaeger or Tempo to visualize request flows across microservices.
User Value
Helps identify performance bottlenecks and failures in complex distributed systems.
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