Learn to use OpenTelemetry to build and manage unified observability, skills increasingly important to IT developers and engineers career growth.
Getting Started with OpenTelemetry (LFS148)
- Programming Knowledge: A basic understanding in programming, preferably with Python and Java
- Basic Understanding of Distributed Systems: Knowledge of how distributed systems communicate and basic concepts of APIs
- Experience with Observability Tools: While not strictly required, having some familiarity with existing observability tools like Prometheus, Grafana, or Jaeger can help understand the context and benefits of OpenTelemetry.
- Command Line Interface (CLI) Skills: Ability to navigate and execute commands in a terminal or command prompt, as many setup and configuration tasks will involve CLI usage.
- Environment Configuration: Experience with setting up and configuring development environments, including virtual environments and containerization technologies like Docker.
- Version Control System (VCS) Usage: Familiarity with version control systems like Git, which is essential for managing code and collaborating on projects.
- Docker (or any compatible container runtime)
- Visual Studio Code
- Visual Studio Code Dev Containers extension
The provided Git repository includes a Dev Container configuration that sets up Python, Java, Docker, and the necessary environment variables. The flow of the hands-on lab has been designed and tested using this configuration.
This setup has been successfully tested on macOS, Windows, and Linux. It will require up to 4GB of RAM and 5GB of hard disk space.
Alternative cloud setup:
GitHub Codespaces also supports the Dev Container specification, allowing you to run the lab in a cloud environment. This requires a GitHub account and access to personal Codespaces plans.