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 o…
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.
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Version0.18.0
LicenseApache-2.0
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author
Juan Antonio Breña Moral
version
0.18.0
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skill mdSKILL.md3,369 B
docsSUMMARY.md569 B
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SKILL.md
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
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](references/183-java-observability-tracing-opentelemetry.md).