opentelemetry
3 free lessons tagged opentelemetry across AI, Programming. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
Memory, Identity, and Seeing What the Agent Did
Three services decide whether an agent survives contact with production: what it remembers between sessions, whose authority it acts with when it calls your systems, and whether you can reconstruct what it did after the fact. This lesson covers AgentCore Memory, Identity and Observability, and the delegation problem that makes agent authentication genuinely different.
Distributed Tracing and the Art of Throwing Data Away
Tracing every request through every service produces the most useful telemetry you have and more of it than anyone can afford. This lesson covers how context propagation actually stitches a trace together, the head versus tail sampling decision and why it determines which incidents you can debug, and the collector pipeline where all of it is enforced.
LLM Observability with OpenTelemetry: GenAI Semantic Conventions
Master the OTel GenAI semantic conventions — gen_ai.* attributes, span structure for prompts/completions/tools, sampling strategies, and cost attribution — and understand why standardizing across LangSmith, Phoenix, Datadog, and Grafana matters for production AI systems.