183-java-observability-tracing-opentelemetry

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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. Part of cursor-rules-java project

jabrena By jabrena schedule Updated 6/15/2026

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. Part of cursor-rules-java project license: Apache-2.0 metadata: author: Juan Antonio Breña Moral version: 0.15.0

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

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.

Install via CLI
npx skills add https://github.com/jabrena/cursor-rules-java --skill 183-java-observability-tracing-opentelemetry
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