183 java observability tracing opentelemetry
Skill jabrena/plinth/skills/183-java-observability-tracing-opentelemetry
Plinth is an AI-native engineering toolkit for modern Java enterprise SDLC, built around reusable Commands, Agents, Skills, and MCP Servers.
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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
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SKILL.md
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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 verifyormvn clean verifyafter 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
- 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.
- 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.
- Harden span data and sampling
Record status/errors/events consistently, remove sensitive data, control attribute cardinality, and configure sampling/exporters according to environment needs.
- 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.