182 Java Observability Metrics Micrometer
Use when you need to implement or improve Java metrics observability with Micrometer — including meter design, naming/tag conventions, cardinality control, timers/counters/gauges/distribution summaries, percentiles/histograms, Actuator/Prometheus integration, and metrics validation through tests. This should trigger for requests such as Improve metrics; Apply Micrometer; Add metrics observability…
Install
$ agentstack add skill-jabrena-cursor-rules-java-182-java-observability-metrics-micrometer ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-jabrena-cursor-rules-java-182-java-observability-metrics-micrometer) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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 verifyormvn clean verifyafter changes
When to use this skill
- Improve metrics
- Apply Micrometer
- Add metrics observability
- Refactor Micrometer instrumentation
Workflow
- 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.
- Select meter types and instrument code paths
Apply Counter/Timer/Gauge/DistributionSummary/LongTaskTimer where appropriate, ensuring consistent naming conventions and reusable tags.
- 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.
- 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).
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: jabrena
- Source: jabrena/cursor-rules-java
- License: Apache-2.0
- Homepage: https://jabrena.github.io/cursor-rules-java/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.