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/...