Grafana Tempo Course: Beginner to Master
Welcome to the complete Grafana Tempo course. This path takes you from fundamentals of observability, through OpenTelemetry instrumentation, into Tempo architecture and production-grade operations. Each section includes clear objectives, a lecture summary, hands-on labs, deliverables, and resources. Use this page as the course index.
Course Roadmap
- Introduction
- Foundations of Observability & Distributed Tracing
- OpenTelemetry Ecosystem & Instrumentation
- Grafana Tempo Deep-Dive
- Setup Tempo: Quickstart with Docker
- Generating Traces with Applications
- Enriching Traces across Grafana Stack
- Advanced Tempo & Scaling to Production
- Capstone: Tracing a Microservices System
- Production: Kubernetes + Helm
- Expert Tips, Best Practices & Troubleshooting
- Bonus: Cheatsheets, Interviews, Stack Templates
How to Use This Course
- Start with Sections 1–4 to ground foundational concepts.
- Build the full local lab in Sections 5–7.
- Level up to production and scale in Sections 8–10.
- Cement learning with the Capstone in Section 9 and revisit Section 11 as a field guide.
- Use Section 12 for rapid revision and career prep.
Requirements
- Docker and Docker Compose
- Basic Linux/CLI skills
- One programming language familiarity (Node.js, Python, Go, or Java)
- Optional: Kubernetes cluster (Kind/Minikube) for Section 10
Outcomes
- Confidently instrument services with OpenTelemetry.
- Operate Grafana Tempo from dev to production.
- Troubleshoot latency and errors using TraceQL, service graphs, and log correlation.
- Design cost-conscious, scalable tracing pipelines for real systems.