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183-java-observability-tracing-opentelemetry

183-java-observability-tracing-opentelemetry

github.com/jabrenaDevelopment456235 installsUpdated 1d ago
Repository

About 183-java-observability-tracing-opentelemetry

A skill for Java developers implementing distributed tracing with OpenTelemetry. It guides span design, context propagation, privacy-safe attributes, sampling, and end-to-end verification across application and infrastructure paths.

Key features

  1. 01OpenTelemetry tracing fundamentals
  2. 02Span boundaries and naming
  3. 03Context propagation across async paths
  4. 04Semantic conventions and attributes
  5. 05Sampling and privacy controls
  6. 06Trace testing and verification

Use cases

  1. 01Add tracing to Java services
  2. 02Propagate context across HTTP and messaging
  3. 03Review spans for sensitive or high-cardinality data
  4. 04Verify trace continuity in tests

Install

Copy the command and run it in a terminal.

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

After installing, type/183-java-observability-tracing-opentelemetryin Claude Code to confirm it loaded.

Bundled filesreferences/183-java-observability-tracing-opentelemetry.md

Details

From the project README

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.

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