183-java-observability-tracing-opentelemetry
Use when you need to implement or improve distributed tracing with OpenTelemetry in Java — including trace/span modeling, context propagation, semantic conventions, span attributes/events/status, sampling strategy, baggage usage, privacy safeguards, and backend integration with OTLP collectors. This should trigger for requests such as Improve tracing; Apply OpenTelemetry tracing; Add distributed tracing; Refactor tracing instrumentation; Instrument Java services with OpenTelemetry spans. Part of Plinth Toolkit
Works with
--- name: 183-java-observability-tracing-opentelemetry description: Use when you need to implement or improve distributed tracing with OpenTelemetry in Java — including trace/span modeling, context propagation, semantic conventions, span attributes/events/status, sampling strategy, baggage usage, privacy safeguards, and backend integration with OTLP collectors. This should trigger for requests such as Improve tracing; Apply OpenTelemetry tracing; Add distributed tracing; Refactor tracing instrumentation; Instrument Java services with OpenTelemetry spans. Part of Plinth Toolkit license: Apache-2.0 --- # Java Distributed Tracing with OpenTelemetry Implement robust distributed tracing in Java with OpenTelemetry by modeling meaningful spans, preserving context propagation, and instrumenting critical business and infrastructure paths with low-overhead, privacy-safe telemetry. **What is covered in this Skill?** - OpenTelemetry tracing fundamentals for Java services - Span design: boundaries, parent/child relationships, and operation naming - Context propagation across HTTP, messaging, async tasks, and thread boundaries - Semantic conventions and stable attribute naming - Error/status/event recording best practices - Sampling strategy and performance/cost trade-offs - Privacy and security controls for trace attributes - Testing and verification of trace propagation and span correctness **Scope:** Distributed tracing quality in application and integration layers, focused on diagnosability, consistency, and operational safety. ## Constraints Tracing instrumentation must preserve context correctly and avoid leaking sensitive data. Over-instrumentation and high-cardinality attributes can harm cost and signal quality. - **PROPAGATION FIRST**: Ensure context propagation across all sync/async boundaries before adding extra span detail - **NO SENSITIVE DATA**: Never store secrets, credentials, tokens, raw payloads, or PII in span attributes/events - **LOW CARDINALITY ATTRIBUTES**: Avoid unbounded values in attributes that are used for aggregation/search - **VERIFY**: Run `./mvnw clean verify` or `mvn clean verify` after applying tracing changes ## When to use this skill - Improve tracing - Apply OpenTelemetry tracing - Add distributed tracing - Refactor tracing instrumentation - Instrument Java services with OpenTelemetry spans ## Workflow 1. **Define trace model and critical flows** Identify high-value request and async flows, define operation boundaries, and choose span names/attributes aligned with semantic conventions. 2. **Instrument and propagate context** Add OpenTelemetry spans to key boundaries and ensure trace context is propagated across HTTP clients/servers, messaging, and executor-based async work. 3. **Harden span data and sampling** Record status/errors/events consistently, remove sensitive data, control attribute cardinality, and configure sampling/exporters according to environment needs. 4. **Validate traces end-to-end** Verify parent-child relationships, propagation continuity, and backend visibility through tests and runtime checks. ## Reference For detailed guidance, examples, and constraints, see [references/183-java-observability-tracing-opentelemetry.md](references/183-java-observability-tracing-opentelemetry.md).
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