GithubHelp home page GithubHelp logo

opentelemetry-101's Introduction

Observability in Cloud Native apps using OpenTelemetry

Welcome to the Observability in Cloud Native apps using OpenTelemetry repository! This repository contains a demo application that is being used throughout the Udemy course. Whether you're a beginner or an experienced developer, the demo application will help you learn and understand the fundamentals of OpenTelemetry and Observability.

Following the course code examples

This course is build an a way that we start with a simple application and every section of the course we will add more functionally of OpenTelemetry.

To navigate between the different phases of the course I have used git tags. Below is a table with all the available tags (after you have cloned the repo it is recommended to checkout the first tag)

Tag name description
1 Before we install OpenTelemetry
2 Basic OpenTelemetry installation
3 Adding Metrics
4 Correlating logs with traces
5 Creating manual spans
6 Adding custom attributes
7 Debug logs
8 Define custom resources
9 Configure custom sampler
10 Using context propagation to set baggage
11 Using the OpenTelemetry Collector
12 Setting up tail sampling

How to use this repo

  1. Clone the Repository:
git clone https://github.com/habmic/opentelemetry-101.git
  1. Checkout the first tag:
git checkout 1
  1. Running it with docker:
docker-compose up

The best way to learn is by experimenting and modifying the code. Try tweaking the code to understand how different configurations and scenarios affect the telemetry data.

Feedback and Contributions

Your feedback to this repository are highly appreciated! If you encounter any issues or have ideas to improve it, please feel free to open an issue or submit a pull request. Let's make this learning resource better together!

Acknowledgments

Special thanks to all the contributors who have helped create and improve these code examples. Your dedication to sharing knowledge and helping others learn is invaluable.

Happy learning!

Michael Haberman [email protected]

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.