182-java-observability-metrics-micrometer

# Java Metrics Observability with Micrometer Implement effective Java metrics instrumentation with Micrometer by defining meaningful service-level metrics, controlling cardinality, selecting the right meter type, and exposing production-ready telemetry for dashboards and alerting. **What is covered in this Skill?** - Metrics-first observability with Micrometer in Java applications - Meter selection: Counter, Timer, DistributionSummary, Gauge, LongTaskTimer - Naming and tagging conventions with low-cardinality dimensions - Cardinality and meter lifecycle safeguards to prevent time-series explosion - Histogram/percentile strategy and SLO-oriented metrics design - Integration guidance for Actuator + Prometheus/OpenTelemetry pipelines - Testing and verification of metrics registration and values **Scope:** Application-level metrics design and instrumentation quality for Java services, with emphasis on operationally useful and cost-efficient telemetry. ## Constraints Metrics instrumentation must be operationally safe, low-cardinality, and validated. Poor tag design or excessive meter creation can degrade observability systems and increase costs. - **LOW CARDINALITY FIRST**: Never tag metrics with unbounded values (userId, UUID, raw URL, full exception message) - **RIGHT METER TYPE**: Use Counter for monotonically increasing events, Timer for latency, Gauge for point-in-time state, and DistributionSummary for sampled values - **BEFORE APPLYING**: Read the reference for good/bad instrumentation examples and anti-patterns - **VERIFY**: Run `./mvnw clean verify` or `mvn clean verify` after changes ## When to use this skill - Improve metrics - Apply Micrometer - Add metrics observability - Refactor Micrometer instrumentation ## Workflow 1. **Define measurement goals and meter contract** Identify key service indicators (throughput, latency, error ratio, saturation) and map each to stable metric names, units, and low-cardinality tags. 2. **Select meter types and instrument code paths** Apply Counter/Timer/Gauge/DistributionSummary/LongTaskTimer where appropriate, ensuring consistent naming conventions and reusable tags. 3. **Harden instrumentation for production** Control cardinality, avoid dynamic meter churn, configure histogram/percentile strategy only where needed, and align export settings with the telemetry backend. 4. **Validate and operationalize metrics** Verify metrics in tests and runtime endpoints, confirm expected labels/units, and ensure dashboards/alerts can consume the emitted series. ## Reference For detailed guidance, examples, and constraints, see [references/182-java-observability-metrics-micrometer.md](references/182-java-observability-metrics-micrometer.md).