Acquire knowledge of the fundamental components of PromQL essential for daily use: rate(), sum by(), label filters, and histogram quantiles—while avoiding typical pitfalls associated with counters and gauges. Subsequently, transform queries into meaningful signals through the development of a clear three-panel Grafana dashboard displaying RPS, error ratio, and 95th percentile latency, all equipped with appropriate units, legends, and variables. Export the dashboard as JSON and configure a noise-aware alert (error rate >5% over 5 minutes) to practice setting thresholds in relation to time windows. The emphasis is on maintaining practical panel organization and creating queries that can be clearly explained.

Implement the demo application with an OpenTelemetry (OTel) Software Development Kit (SDK), establish meaningful resource attributes, and export data via the OpenTelemetry Protocol (OTLP) to a Collector pipeline, which you will configure (receivers → processors → exporters). You will visualize traces using Grafana/Tempo and learn how to navigate from a “hot” metric dashboard directly to the related spans using exemplars. Throughout the process, you will validate the health of the pipeline, incorporate attributes and batching, and practice root-cause analysis on induced failures. The session concludes with next steps including label management, Service Level Objectives (SLOs) and burn rates, as well as retention/export strategies for production environments.