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Metrics and Distributed Tracing with OpenTelemetry

OpenTelemetry is the industry-standard framework for collecting metrics, traces, and logs from Rust applications. This series teaches you how to instrument production-grade observability into your services: measure performance with counters, gauges, and histograms; export metrics to Prometheus; trace individual requests across service boundaries with spans; and visualize everything in Grafana dashboards and Jaeger's distributed tracing UI.

Whether you are building microservices, APIs, or long-running background workers, observability is non-negotiable. You cannot optimize what you cannot measure, and you cannot debug what you cannot trace. By the end of this series, you will have hands-on confidence instrumenting your own Rust applications with industry-standard tools that production teams rely on every day.

Each article builds on the last, starting with why observability matters and OpenTelemetry's architecture, moving through practical metric collection and export, then into distributed tracing across service boundaries, and finally a complete end-to-end example you can adapt to your own codebase.

Articles in this series​

  1. Introduction to OpenTelemetry and Observability
  2. Setting Up OpenTelemetry in Rust: Dependencies and Initialization
  3. Counters and Gauges: Essential Metric Types for Rust
  4. Building Histograms for Performance Measurement
  5. Exporting Rust Metrics to Prometheus
  6. Spans and Instrumentation: Request-Level Tracing Basics
  7. Context Propagation in Distributed Systems
  8. Visualizing Distributed Traces with Jaeger
  9. Grafana Dashboards and Alerting for Rust Metrics
  10. Building Complete End-to-End Observability