183-java-observability-tracing-opentelemetry
This skill guides implementation of distributed tracing in Java applications using OpenTelemetry. Use it when adding or improving trace instrumentation, including span design, context propagation across service boundaries, semantic conventions, error handling, sampling strategies, and privacy safeguards. It covers testing trace correctness and integration with OTLP collectors while preventing common pitfalls like sensitive data exposure and high-cardinality attributes.
git clone --depth 1 https://github.com/jabrena/cursor-rules-java /tmp/183-java-observability-tracing-opentelemetry && cp -r /tmp/183-java-observability-tracing-opentelemetry/skills/183-java-observability-tracing-opentelemetry ~/.claude/skills/183-java-observability-tracing-opentelemetrySKILL.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 ## 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. 2. **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. 3. **Harden span data and sampling** Record status/errors/events consistently, remove sensitive data, control attribute cardinality, and configure sampling/exporters according to environment needs. 4. **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).
Use when you need to generate a checklist document with Java system prompts, following the embedded template exactly and producing INVENTORY-SKILLS-JAVA.md in the project root. This should trigger for requests such as Create Java system prompts checklist; Generate INVENTORY-SKILLS-JAVA.md; Use @001-skills-inventory. Part of cursor-rules-java project
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Use when you need to install the embedded robot agents into either .cursor/agents or .claude/agents, selecting the destination interactively and copying the embedded agent definitions from project assets. This should trigger for requests such as Install embedded agents; Bootstrap .cursor/agents; Bootstrap .claude/agents; Copy robot agents. Part of cursor-rules-java project
Guides the creation of agile epics with comprehensive definition including business value, success criteria, and breakdown into user stories. Use when the user wants to create an agile epic, define large bodies of work, break down features into user stories, or document strategic initiatives. This should trigger for requests such as Create an agile epic; Write an epic; I need to create an epic; Define an epic; Epic definition. Part of cursor-rules-java project
Guides the creation of detailed agile feature documentation from an existing epic. Use when the user wants to split an epic into feature files, derive features with scope and acceptance criteria, or plan feature documentation for stakeholders or engineering. This should trigger for requests such as Create features from an epic; Split epic into features; Feature files from epic; Derive features from epic. Part of cursor-rules-java project
Guides the creation of agile user stories and Gherkin feature files. Use when the user wants to create a user story, write acceptance criteria, define Gherkin scenarios, or author BDD feature files. This should trigger for requests such as Create a user story; Write a user story; I need to write a user story. Part of cursor-rules-java project
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