Distributed Tracing Implementation
Resources from Video Description
- GitHub Repository – All project files and configs
Key Takeaways
Why Distributed Tracing Matters: In microservices, a single slow request can touch many services. Distributed tracing with Tempo breaks requests into spans, making it possible to locate the exact operation or service causing latency.
Tempo + Alloy Architecture: The K6 trace generator simulates multi-service traffic. Alloy collects telemetry (OTLP on port 4317) and forwards it to Tempo, which stores traces and also generates Prometheus metrics like service graphs and span metrics.
Metrics + Traces Together: Tempo writes derived metrics into Prometheus with exemplar support. This bridges traces with metrics, so you can detect anomalies via metrics and drill down to the exact traces causing them.
Grafana Dashboards: Grafana connects to both Prometheus and Tempo as data sources, enabling trace drill-downs, service graphs, and span histograms. You can filter by duration, span name, or service to pinpoint bottlenecks quickly.
Service Graphs & Plugins: Service graphs reveal interdependencies and highlight failing or slow services at a glance. Grafana’s Trace Explorer and drill-down plugins let you go from system-level performance issues to root cause analysis in a few clicks.