What problem does it solve?
Debugging requests across multiple Rails microservices is extremely difficult using only logs, as related events are scattered across separate services and lack a unified view. This Skill eliminates that friction by providing production-ready instructions to implement vendor-neutral distributed tracing that follows requests end-to-end.
Core Features & Use Cases
- OpenTelemetry Auto-Instrumentation: Automatically instruments Rails controllers, Active Record, Sidekiq, Kafka, and outbound HTTP calls with zero custom code for common frameworks.
- Cross-Service Context Propagation: Uses W3C traceparent headers to maintain trace continuity across HTTP, Sidekiq job queues, and Kafka topics without manual wiring.
- Configurable Sampling & Export: Supports parent-based trace sampling, tail-based sampling for errors and slow traces, and OTLP export to all major observability backends including Tempo, Jaeger, Honeycomb, and Datadog.
- Trace-Log Correlation: Includes setup to inject trace_id into every Rails log line, so you can jump from a trace directly to all related logs across services.
- Use Case: For a Rails ecommerce platform with separate order, payment, and notification services, use this Skill to trace a single checkout request across all three services to identify latency bottlenecks in the payment processing step.
Quick Start
Use the distributed-tracing-rails skill to configure OpenTelemetry tracing for your Rails application with auto-instrumentation and cross-service request visibility.
