swarm-observability

Add tracing dependencies to your Cargo.toml and annotate async Rust functions with the #[instrument] attribute to automatically capture function entry, exit, and contextual data for diagnostics and performance monitoring.

Collecting metrics and error context in Rust async applications is best achieved by combining tracing instrumentation with extended error types. This approach enriches errors with contextual data to improve observability dashboards and incident response.

Transition from deprecated derive macros to direct concept builders to improve your developer experience when setting up Rust observability. This Skill provides structured guidance on managing this migration for better tracing and metrics workflows.

Yes, Rust tracing works effectively with complex async services for performance monitoring and robust error reporting across components. It provides the structured diagnostics needed to understand and maintain concurrent application behavior.

Extending error types with context is needed for Rust debugging to provide robust error reporting and better diagnostic visibility. Enriching errors with contextual data helps pinpoint failures quickly across complex async components.