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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

How do I install this agent skill?

npx skills add https://github.com/jabrena/plinth --skill 183-java-observability-tracing-opentelemetry
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill provides comprehensive and secure guidelines for implementing OpenTelemetry tracing in Java services, with a strong focus on preventing data leakage and ensuring context propagation.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

What does this agent skill do?

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.

  1. 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.

  1. Harden span data and sampling

Record status/errors/events consistently, remove sensitive data, control attribute cardinality, and configure sampling/exporters according to environment needs.

  1. 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.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/jabrena/plinth/183-java-observability-tracing-opentelemetry">View 183-java-observability-tracing-opentelemetry on skillZs</a>